-
Global information
- Generated on Fri Apr 4 08:00:22 2025
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2025-04-04_090000.log, ..., /home/postgres/pg_data/data/pg_log/postgresql-2025-04-04_095002.log
- Parsed 2,729,275 log entries in 1m21s
- Log start from 2025-04-04 09:00:00 to 2025-04-04 10:00:00
-
Overview
Global Stats
- 232 Number of unique normalized queries
- 167,924 Number of queries
- 1h42m21s Total query duration
- 2025-04-04 09:00:00 First query
- 2025-04-04 09:59:59 Last query
- 3,457 queries/s at 2025-04-04 09:45:05 Query peak
- 1h42m21s Total query duration
- 9s212ms Prepare/parse total duration
- 1m38s Bind total duration
- 1h40m33s Execute total duration
- 1 Number of events
- 1 Number of unique normalized events
- 1 Max number of times the same event was reported
- 0 Number of cancellation
- 47 Total number of automatic vacuums
- 61 Total number of automatic analyzes
- 629 Number temporary file
- 431.59 MiB Max size of temporary file
- 5.66 MiB Average size of temporary file
- 3,697 Total number of sessions
- 12 sessions at 2025-04-04 09:46:13 Session peak
- 9d11h42m27s Total duration of sessions
- 3m41s Average duration of sessions
- 45 Average queries per session
- 1s661ms Average queries duration per session
- 3m40s Average idle time per session
- 3,695 Total number of connections
- 44 connections/s at 2025-04-04 09:45:03 Connection peak
- 2 Total number of databases
SQL Traffic
Key values
- 3,457 queries/s Query Peak
- 2025-04-04 09:45:05 Date
SELECT Traffic
Key values
- 3,445 queries/s Query Peak
- 2025-04-04 09:45:05 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 249 queries/s Query Peak
- 2025-04-04 09:00:56 Date
Queries duration
Key values
- 1h42m21s Total query duration
Prepared queries ratio
Key values
- 0.00 Ratio of bind vs prepare
- 0.00 % Ratio between prepared and "usual" statements
General Activity
↑ Back to the top of the General Activity tableDay Hour Count Min duration Max duration Avg duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Apr 04 09 167,924 0ms 29s138ms 35ms 3m 3m20s 4m24s 10 0 0ms 0ms 0ms 0ms 0ms 0ms Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Apr 04 09 133,160 26 2ms 6s844ms 17s93ms 34s13ms 10 0 0 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Apr 04 09 23,818 3,520 16 96 1ms 690ms 1s98ms 3s179ms 10 0 0 0 0 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Apr 04 09 24,200 150,108 6.20 14.67% 10 1 0 0.00 100.00% Day Hour Count Average / Second Apr 04 09 3,695 1.03/s 10 0 0.00/s Day Hour Count Average Duration Average idle time Apr 04 09 3,697 3m41s 3m40s 10 0 0ms 0ms -
Connections
Established Connections
Key values
- 44 connections Connection Peak
- 2025-04-04 09:45:03 Date
Connections per database
Key values
- acaweb_fx Main Database
- 3,695 connections Total
Connections per user
Key values
- postgres Main User
- 3,695 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 1278 connections
- 3,695 Total connections
Host Count 127.0.0.1 111 182.165.1.42 7 182.165.1.54 2 192.168.0.216 100 192.168.1.145 249 192.168.1.20 253 192.168.1.23 445 192.168.1.239 13 192.168.1.250 249 192.168.1.90 52 192.168.2.126 71 192.168.2.182 12 192.168.2.205 12 192.168.2.82 47 192.168.3.199 63 192.168.4.142 1,278 192.168.4.150 10 192.168.4.152 1 192.168.4.222 1 192.168.4.238 16 192.168.4.33 99 192.168.4.98 330 [local] 274 -
Sessions
Simultaneous sessions
Key values
- 12 sessions Session Peak
- 2025-04-04 09:46:13 Date
Histogram of session times
Key values
- 2,847 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 3,697 sessions Total
Sessions per user
Key values
- postgres Main User
- 3,697 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 3,697 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 111 17s956ms 161ms 182.165.1.42 7 2h29m44s 21m23s 182.165.1.54 2 23h27m3s 11h43m31s 192.168.0.216 100 42s743ms 427ms 192.168.1.145 249 1d7h13m37s 7m31s 192.168.1.20 254 2d5h58m45s 12m45s 192.168.1.23 445 1d7h43m18s 4m16s 192.168.1.239 13 108ms 8ms 192.168.1.250 250 2d15h56m51s 15m20s 192.168.1.90 52 36s791ms 707ms 192.168.2.126 71 16s491ms 232ms 192.168.2.182 12 717ms 59ms 192.168.2.205 12 531ms 44ms 192.168.2.82 47 58s406ms 1s242ms 192.168.3.199 63 31s714ms 503ms 192.168.4.142 1,278 16m57s 796ms 192.168.4.150 10 20h15m29s 2h1m32s 192.168.4.152 1 158ms 158ms 192.168.4.222 1 2m16s 2m16s 192.168.4.238 16 21s372ms 1s335ms 192.168.4.33 99 11m54s 7s213ms 192.168.4.98 330 12s574ms 38ms [local] 274 2m30s 550ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 12,242 buffers Checkpoint Peak
- 2025-04-04 09:08:57 Date
- 209.984 seconds Highest write time
- 0.013 seconds Sync time
Checkpoints Wal files
Key values
- 8 files Wal files usage Peak
- 2025-04-04 09:08:57 Date
Checkpoints distance
Key values
- 236.73 Mo Distance Peak
- 2025-04-04 09:08:57 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Apr 04 09 45,447 2,031.481s 0.066s 2,031.877s 10 0 0s 0s 0s Day Hour Added Removed Recycled Synced files Longest sync Average sync Apr 04 09 0 0 27 2,064 0.007s 0s 10 0 0 0 0 0s 0s Day Hour Count Avg time (sec) Apr 04 09 0 0s 10 0 0s Day Hour Mean distance Mean estimate Apr 04 09 37,030.33 kB 84,503.25 kB 10 0.00 kB 0.00 kB -
Temporary Files
Size of temporary files
Key values
- 431.59 MiB Temp Files size Peak
- 2025-04-04 09:23:43 Date
Number of temporary files
Key values
- 62 per second Temp Files Peak
- 2025-04-04 09:17:11 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Apr 04 09 629 3.48 GiB 5.66 MiB 10 0 0 0 Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 66 312.02 MiB 4.64 MiB 7.49 MiB 4.73 MiB with rar_max as ( ;-
WITH rar_max as ( ;
Date: 2025-04-04 09:50:47 Duration: 0ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown]
2 42 1.54 GiB 7.33 MiB 119.74 MiB 37.48 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-04-04 09:00:11 Duration: 8s535ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-04-04 09:30:10 Duration: 7s922ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-04-04 09:10:07 Duration: 4s614ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
3 16 363.10 MiB 22.69 MiB 22.70 MiB 22.69 MiB update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:11:13 Duration: 1s535ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:46:12 Duration: 1s62ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:31:12 Duration: 1s36ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
4 16 625.62 MiB 39.10 MiB 39.10 MiB 39.10 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:46:15 Duration: 2s659ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:11:16 Duration: 2s642ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:31:15 Duration: 2s271ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
5 4 244.62 MiB 61.11 MiB 61.21 MiB 61.16 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2025-04-04 09:32:17 Duration: 14s826ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-04-04 09:47:17 Duration: 14s227ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-04-04 09:02:16 Duration: 13s893ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
6 2 7.32 MiB 3.23 MiB 4.09 MiB 3.66 MiB select distinct patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, longname, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as relevant from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join symbolgroup sg on s.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join autochartist_results a on a.symbolid = s.symbolid inner join patterns p on a.pattern = p.patternname left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and breakout = ? and patternlengthbars >= ? and patternquality >= ?.? and initialtrend >= ?.? and symmetry >= ?.? and noise <= ?.? and volumeincrease >= ?.? and temporarypattern = ? and patternid & ? > ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and a.resultuid > ? and s.nonliquid = ? and dftt.dayofweek = ? order by relevant desc, age asc, patternendtime desc, patternquality desc limit ?;-
/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059718346308 AND breakout = - 1 AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-04-04 09:14:12 Duration: 320ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059758978308 AND breakout = - 1 AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-04-04 09:14:13 Duration: 264ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND breakout = - 1 AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-04-04 09:14:13 Duration: 120ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver
7 1 431.59 MiB 431.59 MiB 431.59 MiB 431.59 MiB select count(*) from ( select *, row_number() over (partition by whid order by id desc) r from whatshot_probability where type = ? union select *, row_number() over (partition by whid order by id desc) r from whatshot_probability where type = ? union select *, row_number() over (partition by whid order by id desc) r from whatshot_probability where type = ?) as k where r > ?;-
select count(*) from ( select *, row_number() over (partition by whid order by id desc) r from whatshot_probability where type = 'cp' union select *, row_number() over (partition by whid order by id desc) r from whatshot_probability where type = 'ekl' union select *, row_number() over (partition by whid order by id desc) r from whatshot_probability where type = 'kl') as k where r > 3;
Date: 2025-04-04 09:23:43 Duration: 4s928ms Database: acaweb_fx User: postgres Remote: 192.168.2.126 Application: [unknown]
Queries generating the largest temporary files
Rank Size Query 1 431.59 MiB select count(*) from ( select *, row_number() over (partition by whid order by id desc) r from whatshot_probability where type = 'cp' union select *, row_number() over (partition by whid order by id desc) r from whatshot_probability where type = 'ekl' union select *, row_number() over (partition by whid order by id desc) r from whatshot_probability where type = 'kl') as k where r > 3;[ Date: 2025-04-04 09:23:43 - Database: acaweb_fx - User: postgres - Remote: 192.168.2.126 - Application: [unknown] ]
2 119.74 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-04-04 09:00:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
3 110.75 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-04-04 09:30:04 ]
4 93.38 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-04-04 09:20:04 ]
5 69.81 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-04-04 09:10:04 ]
6 67.65 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-04-04 09:20:07 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
7 66.97 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-04-04 09:40:04 ]
8 63.13 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-04-04 09:10:07 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
9 61.21 MiB select updateageforrelevantresults ();[ Date: 2025-04-04 09:02:06 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
10 61.18 MiB select updateageforrelevantresults ();[ Date: 2025-04-04 09:32:07 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
11 61.12 MiB select updateageforrelevantresults ();[ Date: 2025-04-04 09:47:06 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
12 61.11 MiB select updateageforrelevantresults ();[ Date: 2025-04-04 09:17:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
13 58.16 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-04-04 09:50:05 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
14 57.83 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-04-04 09:50:04 ]
15 57.35 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-04-04 09:30:07 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
16 56.99 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-04-04 09:50:05 ]
17 56.09 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-04-04 09:40:04 ]
18 55.55 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-04-04 09:20:04 ]
19 47.57 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-04-04 09:40:05 ]
20 46.52 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-04-04 09:00:06 ]
-
Vacuums
Vacuums / Analyzes Distribution
Key values
- 0 sec Highest CPU-cost vacuum
Table
Database - Date
- 0 sec Highest CPU-cost analyze
Table
Database - Date
Analyzes per table
Key values
- public.solr_relevance_old (16) Main table analyzed (database acaweb_fx)
- 61 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 16 acaweb_fx.pg_catalog.pg_attribute 6 acaweb_fx.public.datafeeds_latestrun 4 acaweb_fx.public.relevance_keylevels_results 4 acaweb_fx.pg_catalog.pg_class 4 acaweb_fx.public.relevance_fibonacci_results 4 acaweb_fx.pg_catalog.pg_type 4 acaweb_fx.public.relevance_autochartist_results 4 acaweb_fx.pg_catalog.pg_index 2 acaweb_fx.public.autochartist_symbolupdates 2 acaweb_fx.pg_catalog.pg_depend 2 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.public.relevance_bigmovement_results 2 socialmedia.public.processes 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.relevance_consecutivecandles_results 1 acaweb_fx.public.symbollatestupdatetime 1 socialmedia.public.processstatevariables 1 Total 61 Vacuums per table
Key values
- public.solr_relevance_old (24) Main table vacuumed on database acaweb_fx
- 47 vacuums Total
Index Buffer usage Skipped WAL usage Table Vacuums scans hits misses dirtied pins frozen records full page bytes acaweb_fx.public.solr_relevance_old 24 17 19,955 0 62 0 74 10,210 16 1,902,523 acaweb_fx.public.datafeeds_latestrun 4 0 421 0 10 0 0 72 10 61,794 acaweb_fx.public.relevance_autochartist_results 3 3 10,772 0 191 4 705 1,997 161 533,913 acaweb_fx.pg_toast.pg_toast_2619 2 2 269 0 51 0 0 204 51 219,246 acaweb_fx.public.relevance_bigmovement_results 2 2 504 0 5 0 0 154 12 40,061 acaweb_fx.public.latest_t15_candle_view 2 2 130 0 2 0 0 12 2 18,110 acaweb_fx.public.relevance_keylevels_results 2 2 8,217 0 335 2 236 1,593 774 2,011,500 acaweb_fx.public.relevance_fibonacci_results 2 2 2,533 0 42 4 118 376 27 80,035 acaweb_fx.pg_catalog.pg_type 1 1 144 0 21 0 0 56 17 94,400 acaweb_fx.public.autochartist_symbolupdates 1 1 24,809 0 1,053 4 38,175 6,504 1,575 749,546 acaweb_fx.pg_catalog.pg_statistic 1 1 838 0 215 0 674 483 185 744,029 acaweb_fx.pg_catalog.pg_attribute 1 1 781 0 186 0 64 363 151 885,563 acaweb_fx.public.solr_imports 1 1 43 0 3 0 0 7 2 14,103 acaweb_fx.pg_catalog.pg_class 1 1 382 0 35 0 41 128 30 157,853 Total 47 36 69,798 46,265 2,211 14 40,087 22,159 3,013 7,512,676 Tuples removed per table
Key values
- public.solr_relevance_old (55969) Main table with removed tuples on database acaweb_fx
- 66982 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 24 17 55,969 224,018 61,887 0 5,488 acaweb_fx.public.autochartist_symbolupdates 1 1 4,658 47,848 209 0 40,691 acaweb_fx.public.relevance_keylevels_results 2 2 1,370 22,648 0 0 558 acaweb_fx.public.relevance_autochartist_results 3 3 1,197 27,526 1,783 0 1,140 acaweb_fx.pg_catalog.pg_attribute 1 1 1,178 9,628 165 0 242 acaweb_fx.public.relevance_bigmovement_results 2 2 704 3,555 0 0 98 acaweb_fx.pg_catalog.pg_statistic 1 1 681 4,466 0 0 1,194 acaweb_fx.public.relevance_fibonacci_results 2 2 392 2,667 0 0 204 acaweb_fx.public.datafeeds_latestrun 4 0 245 60 0 0 64 acaweb_fx.pg_catalog.pg_class 1 1 147 1,954 7 0 150 acaweb_fx.pg_toast.pg_toast_2619 2 2 146 349 12 0 104 acaweb_fx.public.latest_t15_candle_view 2 2 126 28 0 0 2 acaweb_fx.pg_catalog.pg_type 1 1 117 1,338 0 0 38 acaweb_fx.public.solr_imports 1 1 52 1 0 0 2 Total 47 36 66,982 346,086 64,063 0 49,975 Pages removed per table
Key values
- unknown (0) Main table with removed pages on database unknown
- 0 pages Total removed
Pages removed per tables
NO DATASET
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_toast.pg_toast_2619 2 2 146 0 acaweb_fx.pg_catalog.pg_type 1 1 117 0 acaweb_fx.public.datafeeds_latestrun 4 0 245 0 acaweb_fx.public.autochartist_symbolupdates 1 1 4658 0 acaweb_fx.pg_catalog.pg_statistic 1 1 681 0 acaweb_fx.pg_catalog.pg_attribute 1 1 1178 0 acaweb_fx.public.solr_imports 1 1 52 0 acaweb_fx.public.relevance_bigmovement_results 2 2 704 0 acaweb_fx.public.latest_t15_candle_view 2 2 126 0 acaweb_fx.public.relevance_keylevels_results 2 2 1370 0 acaweb_fx.pg_catalog.pg_class 1 1 147 0 acaweb_fx.public.solr_relevance_old 24 17 55969 0 acaweb_fx.public.relevance_autochartist_results 3 3 1197 0 acaweb_fx.public.relevance_fibonacci_results 2 2 392 0 Total 47 36 66,982 0 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Apr 04 09 47 61 10 0 0 - 0 sec Highest CPU-cost vacuum
-
Locks
Locks by types
Key values
- unknown Main Lock Type
- 0 locks Total
Most frequent waiting queries (N)
Rank Count Total time Min time Max time Avg duration Query NO DATASET
Queries that waited the most
Rank Wait time Query NO DATASET
-
Queries
Queries by type
Key values
- 133,160 Total read queries
- 31,765 Total write queries
Queries by database
Key values
- acaweb_fx Main database
- 166,951 Requests
- 1h40m32s (acaweb_fx)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 166,951 1h40m32s copy from 96 7s49ms copy to 26 17s55ms cte 3,613 1h33m49s ddl 16 496ms delete 16 24ms insert 23,349 25s34ms others 2,999 8s54ms select 132,779 5m27s tcl 660 185ms update 3,397 17s742ms socialmedia Total 973 1s348ms insert 469 830ms select 381 281ms update 123 237ms Queries by user
Key values
- postgres Main user
- 167,924 Requests
User Request type Count Duration postgres Total 167,924 1h40m33s copy from 96 7s49ms copy to 26 17s55ms cte 3,613 1h33m49s ddl 16 496ms delete 16 24ms insert 23,818 25s864ms others 2,999 8s54ms select 133,160 5m27s tcl 660 185ms update 3,520 17s979ms Duration by user
Key values
- 1h40m33s (postgres) Main time consuming user
User Request type Count Duration postgres Total 167,924 1h40m33s copy from 96 7s49ms copy to 26 17s55ms cte 3,613 1h33m49s ddl 16 496ms delete 16 24ms insert 23,818 25s864ms others 2,999 8s54ms select 133,160 5m27s tcl 660 185ms update 3,520 17s979ms Queries by host
Key values
- 192.168.1.145 Main host
- 59,039 Requests
- 34m58s (192.168.1.250)
- Main time consuming host
Host Request type Count Duration 127.0.0.1 Total 13,938 51s169ms copy to 26 17s55ms cte 24 296ms insert 10,309 14s446ms select 700 17s112ms update 2,879 2s258ms 182.165.1.42 Total 303 8m cte 80 8m others 7 0ms select 216 157ms 182.165.1.54 Total 1,237 152ms others 4 0ms select 1,233 152ms 192.168.0.216 Total 400 345ms others 200 28ms select 192 212ms update 8 104ms 192.168.0.236 Total 8 0ms cte 1 0ms select 7 0ms 192.168.0.239 Total 772 525ms select 772 525ms 192.168.0.42 Total 1,806 1s341ms insert 507 42ms select 1,299 1s299ms 192.168.1.135 Total 186 445ms cte 8 222ms select 178 222ms 192.168.1.145 Total 59,039 26m27s cte 706 25m6s others 498 5ms select 57,835 1m21s 192.168.1.20 Total 47,999 25m36s cte 685 24m23s others 506 5ms select 46,808 1m12s 192.168.1.201 Total 2,075 1s718ms select 2,075 1s718ms 192.168.1.23 Total 5,967 35s381ms cte 6 12ms others 890 9ms select 5,071 35s360ms 192.168.1.239 Total 52 30ms others 26 2ms select 26 28ms 192.168.1.250 Total 16,716 34m58s cte 1,957 34m51s others 498 4ms select 14,261 7s560ms 192.168.1.90 Total 60 34s631ms cte 6 34s590ms others 8 0ms select 46 41ms 192.168.1.97 Total 16 7ms cte 1 0ms select 15 7ms 192.168.2.126 Total 98 9s335ms others 27 0ms select 71 9s335ms 192.168.2.182 Total 48 225ms others 24 2ms select 12 10ms update 12 213ms 192.168.2.205 Total 138 130ms insert 90 7ms others 24 2ms select 20 20ms update 4 100ms 192.168.2.82 Total 771 1s498ms insert 425 784ms others 94 9ms select 154 96ms update 98 607ms 192.168.3.199 Total 252 272ms others 126 11ms select 114 121ms update 12 139ms 192.168.4.142 Total 13,546 11s184ms insert 12,018 9s753ms select 1,528 1s431ms 192.168.4.150 Total 22 1s240ms others 21 0ms select 1 1s240ms 192.168.4.152 Total 3 36ms cte 1 35ms others 2 0ms 192.168.4.222 Total 117 261ms cte 26 189ms others 2 0ms select 89 71ms 192.168.4.238 Total 48 20s414ms cte 16 20s414ms others 32 0ms 192.168.4.33 Total 973 1s348ms insert 469 830ms select 381 281ms update 123 237ms 192.168.4.98 Total 996 8s503ms others 6 7s720ms select 6 28ms tcl 660 185ms update 324 568ms [local] Total 338 2m30s copy from 96 7s49ms cte 96 32s60ms ddl 16 496ms delete 16 24ms others 4 251ms select 50 1m36s update 60 13s749ms Queries by application
Key values
- PostgreSQL JDBC Driver Main application
- 134,761 Requests
- 1h28m4s (PostgreSQL JDBC Driver)
- Main time consuming application
Application Request type Count Duration PostgreSQL JDBC Driver Total 134,761 1h28m4s cte 3,405 1h24m42s insert 507 42ms others 1,227 13ms select 129,622 3m21s [unknown] Total 32,714 9m41s cte 88 8m34s insert 23,311 25s821ms others 1,768 7s788ms select 3,436 28s726ms tcl 660 185ms update 3,451 4s211ms psql Total 449 2m47s copy from 96 7s49ms copy to 26 17s55ms cte 120 32s357ms ddl 16 496ms delete 16 24ms others 4 251ms select 102 1m36s update 69 13s768ms Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2025-04-04 09:49:02 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 102,746 0-1ms duration
Slowest individual queries
Rank Duration Query 1 29s138ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-04-04 09:00:46 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
2 27s401ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:10:57 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
3 27s67ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:05:57 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
4 26s383ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:15:56 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
5 25s609ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:20:56 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
6 22s372ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('183' = 0 OR coalesce(bim.code, s.symbol) in ('AUDUSD', 'EURUSD', 'GBPUSD', 'USDCAD', 'USDCHF', 'USDJPY', 'XAGAUD', 'XAGEUR', 'XAGUSD', 'XAUAUD', 'XAUCHF', 'XAUEUR', 'XAUGBP', 'XAUJPY', 'XAUUSD', 'XPDUSD', 'XPTUSD', 'AUS200', 'CA60', 'CHINAH', 'CN50', 'EUSTX50', 'FRA40', 'GER40', 'GERTEC30', 'HK50', 'JPN225', 'MidDE50', 'NAS100', 'NETH25', 'NOR25', 'SA40', 'SCI25', 'SPA35', 'SWI20', 'UK100', 'US2000', 'US30', 'US500', 'VIX', 'AUDCAD', 'AUDCHF', 'AUDNZD', 'AUDSGD', 'EURAUD', 'EURCHF', 'EURGBP', 'GBPAUD', 'GBPCHF', 'NZDUSD', 'CHFSGD', 'EURCZK', 'EURHUF', 'EURMXN', 'EURNOK', 'EURPLN', 'EURSEK', 'EURSGD', 'EURTRY', 'EURZAR', 'GBPMXN', 'GBPNOK', 'GBPSEK', 'GBPSGD', 'GBPTRY', 'NOKJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'SEKJPY', 'SGDJPY', 'USDCNH', 'USDCZK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTHB', 'USDTRY', 'USDZAR', 'ZARJPY', 'ADAUSD', 'AVAXUSD', 'BCHUSD', 'BNBUSD', 'BTCUSD', 'Crypto10', 'Crypto20', 'Crypto30', 'DOGEUSD', 'DOTUSD', 'EOSUSD', 'ETHUSD', 'LINKUSD', 'LTCUSD', 'MATICUSD', 'SOLUSD', 'UNIUSD', 'XLMUSD', 'XRPUSD', 'XTZUSD', 'EURX', 'JPYX', 'USDX', 'Gasoline', 'NatGas', 'SpotBrent', 'SpotCrude', 'AAPL.US', 'ABNB.US', 'AMD.US', 'AMZN.US', 'AXP.US', 'BA.US', 'BABA.US', 'BIDU.US', 'BYND.US', 'C.US', 'COIN.US', 'CRM.US', 'DIS.US', 'EA.US', 'GOOG.US', 'GS.US', 'IBM.US', 'JPM.US', 'LMT.US', 'MA.US', 'MCD.US', 'META.US', 'MRNA.US', 'MSFT.US', 'NFLX.US', 'NKE.US', 'NVDA.US', 'ORCL.US', 'PFE.US', 'PG.US', 'PLTR.US', 'PTON.US', 'PYPL.US', 'QCOM.US', 'SNAP.US', 'SPCE.US', 'SPY.US', 'T.US', 'TMUS.US', 'TSLA.US', 'UBER.US', 'V.US', 'WMT.US', 'ZM.US', 'Cattle', 'Cocoa', 'Coffee', 'Corn', 'Cotton', 'LDSugar', 'LeanHogs', 'LondonSugar', 'Lumber', 'OJ', 'Oats', 'RghRice', 'SoyMeal', 'SoyOil', 'Soybeans', 'Sugar', 'Wheat', 'AUDJPY', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURCAD', 'EURJPY', 'EURNZD', 'GBPCAD', 'GBPJPY', 'GBPNZD', 'NZDJPY')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:05:52 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
7 21s549ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:11:09 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
8 21s155ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:31:20 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
9 19s774ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:00:13 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
10 19s645ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:01:19 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
11 19s321ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('31' = 0 OR coalesce(bim.code, s.symbol) in ('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURNZD', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'JPN225', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', 'XAGUSD', 'XAUUSD')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:10:49 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
12 19s241ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('183' = 0 OR coalesce(bim.code, s.symbol) in ('AUDUSD', 'EURUSD', 'GBPUSD', 'USDCAD', 'USDCHF', 'USDJPY', 'XAGAUD', 'XAGEUR', 'XAGUSD', 'XAUAUD', 'XAUCHF', 'XAUEUR', 'XAUGBP', 'XAUJPY', 'XAUUSD', 'XPDUSD', 'XPTUSD', 'AUS200', 'CA60', 'CHINAH', 'CN50', 'EUSTX50', 'FRA40', 'GER40', 'GERTEC30', 'HK50', 'JPN225', 'MidDE50', 'NAS100', 'NETH25', 'NOR25', 'SA40', 'SCI25', 'SPA35', 'SWI20', 'UK100', 'US2000', 'US30', 'US500', 'VIX', 'AUDCAD', 'AUDCHF', 'AUDNZD', 'AUDSGD', 'EURAUD', 'EURCHF', 'EURGBP', 'GBPAUD', 'GBPCHF', 'NZDUSD', 'CHFSGD', 'EURCZK', 'EURHUF', 'EURMXN', 'EURNOK', 'EURPLN', 'EURSEK', 'EURSGD', 'EURTRY', 'EURZAR', 'GBPMXN', 'GBPNOK', 'GBPSEK', 'GBPSGD', 'GBPTRY', 'NOKJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'SEKJPY', 'SGDJPY', 'USDCNH', 'USDCZK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTHB', 'USDTRY', 'USDZAR', 'ZARJPY', 'ADAUSD', 'AVAXUSD', 'BCHUSD', 'BNBUSD', 'BTCUSD', 'Crypto10', 'Crypto20', 'Crypto30', 'DOGEUSD', 'DOTUSD', 'EOSUSD', 'ETHUSD', 'LINKUSD', 'LTCUSD', 'MATICUSD', 'SOLUSD', 'UNIUSD', 'XLMUSD', 'XRPUSD', 'XTZUSD', 'EURX', 'JPYX', 'USDX', 'Gasoline', 'NatGas', 'SpotBrent', 'SpotCrude', 'AAPL.US', 'ABNB.US', 'AMD.US', 'AMZN.US', 'AXP.US', 'BA.US', 'BABA.US', 'BIDU.US', 'BYND.US', 'C.US', 'COIN.US', 'CRM.US', 'DIS.US', 'EA.US', 'GOOG.US', 'GS.US', 'IBM.US', 'JPM.US', 'LMT.US', 'MA.US', 'MCD.US', 'META.US', 'MRNA.US', 'MSFT.US', 'NFLX.US', 'NKE.US', 'NVDA.US', 'ORCL.US', 'PFE.US', 'PG.US', 'PLTR.US', 'PTON.US', 'PYPL.US', 'QCOM.US', 'SNAP.US', 'SPCE.US', 'SPY.US', 'T.US', 'TMUS.US', 'TSLA.US', 'UBER.US', 'V.US', 'WMT.US', 'ZM.US', 'Cattle', 'Cocoa', 'Coffee', 'Corn', 'Cotton', 'LDSugar', 'LeanHogs', 'LondonSugar', 'Lumber', 'OJ', 'Oats', 'RghRice', 'SoyMeal', 'SoyOil', 'Soybeans', 'Sugar', 'Wheat', 'AUDJPY', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURCAD', 'EURJPY', 'EURNZD', 'GBPCAD', 'GBPJPY', 'GBPNZD', 'NZDJPY')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:20:49 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
13 19s135ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:21:45 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
14 19s96ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.patternlengthbars <= '400') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-04-04 09:11:27 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
15 18s986ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:21:45 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
16 18s740ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:01:23 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
17 18s597ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:21:49 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
18 18s567ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:11:14 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
19 18s440ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.patternlengthbars <= '400') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-04-04 09:46:13 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
20 17s776ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-04-04 09:11:13 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
Time consuming queries
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 44m28s 252 397ms 27s401ms 10s589ms with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ), ar as ( select a.*, rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end ), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on sg.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Apr 04 09 252 44m28s 10s589ms [ User: postgres - Total duration: 44m28s - Times executed: 252 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 40m24s - Times executed: 240 ]
[ Application: [unknown] - Total duration: 4m4s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:10:57 Duration: 27s401ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:05:57 Duration: 27s67ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:15:56 Duration: 26s383ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
2 32m53s 252 171ms 29s138ms 7s830ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Apr 04 09 252 32m53s 7s830ms [ User: postgres - Total duration: 32m53s - Times executed: 252 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 30m18s - Times executed: 240 ]
[ Application: [unknown] - Total duration: 2m35s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-04-04 09:00:46 Duration: 29s138ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.patternlengthbars <= '400') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-04-04 09:11:27 Duration: 19s96ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.patternlengthbars <= '400') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-04-04 09:46:13 Duration: 18s440ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
3 12m2s 249 592ms 8s567ms 2s900ms with rar_max as ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ? ), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end ), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp))) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Apr 04 09 249 12m2s 2s900ms [ User: postgres - Total duration: 12m2s - Times executed: 249 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 11m - Times executed: 237 ]
[ Application: [unknown] - Total duration: 1m1s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:11:07 Duration: 8s567ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:11:21 Duration: 8s181ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:21:52 Duration: 6s466ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
4 1m42s 29,091 0ms 41ms 3ms select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Apr 04 09 29,091 1m42s 3ms [ User: postgres - Total duration: 1m42s - Times executed: 29091 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m42s - Times executed: 29091 ]
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'MCD.US' OR dss.downloadersymbol = 'MCD.US') AND dss.enabled = 1;
Date: 2025-04-04 09:30:05 Duration: 41ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'AUDCAD' OR dss.downloadersymbol = 'AUDCAD') AND dss.enabled = 1;
Date: 2025-04-04 09:30:07 Duration: 39ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'EURNOK' OR dss.downloadersymbol = 'EURNOK') AND dss.enabled = 1;
Date: 2025-04-04 09:30:04 Duration: 33ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
5 1m37s 162 34ms 1s798ms 604ms with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Apr 04 09 162 1m37s 604ms [ User: postgres - Total duration: 1m37s - Times executed: 162 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m25s - Times executed: 150 ]
[ Application: [unknown] - Total duration: 12s832ms - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:46:15 Duration: 1s798ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:31:09 Duration: 1s477ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:11:26 Duration: 1s429ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
6 56s667ms 4 13s720ms 14s826ms 14s166ms select updateageforrelevantresults ();Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Apr 04 09 4 56s667ms 14s166ms [ User: postgres - Total duration: 56s667ms - Times executed: 4 ]
[ Application: psql - Total duration: 56s667ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-04-04 09:32:17 Duration: 14s826ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-04-04 09:47:17 Duration: 14s227ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-04-04 09:02:16 Duration: 13s893ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
7 47s730ms 32,330 0ms 23ms 1ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Apr 04 09 32,330 47s730ms 1ms [ User: postgres - Total duration: 47s730ms - Times executed: 32330 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 47s730ms - Times executed: 32330 ]
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840249425757300';
Date: 2025-04-04 09:00:06 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243265160300';
Date: 2025-04-04 09:00:05 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840233391195300';
Date: 2025-04-04 09:00:05 Duration: 22ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
8 43s6ms 112 90ms 881ms 383ms with last_candle as ( select acs.symbolid as symbolid, acs.latestpricedatetime as latest_candle_time, bsl.brokerid as broker_id, coalesce(bim.code, s.symbol) as symbol, bim.code as symbol_mapping, s.exchange as exchange, s.timegranularity as timegranularity from autochartist_symbolupdates acs inner join brokersymbollist bsl on acs.symbolid = bsl.symbolid inner join symbols s on acs.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bsl.brokerid = ? and s.deleted = ? and s.nonliquid = ? and acs.latestpricedatetime is not null ) select * from ( select lc.broker_id as brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / ?) + ? as sast_hh, mod(cast(psp.fromtime as int), ?) as sast_mm, current_timestamp as datetime, (powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice as closingprice, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / ?.?) as low_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / ?.?) as high_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / ?.?) as low_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / ?.?) as high_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / ?.?) as low_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / ?.?) as high_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / ?.?) as low_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / ?.?) as high_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / ?.?) as low_1440, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / ?.?) as high_1440, dtt.absolutetimezoneoffset as datafeedtimezoneoffset, dtt.timezone as datafeedtimezonename, (round((cast(? as float) - rank) / ? * ?)) as rank_rounded, ((cast(? as float) - rank) / ? * ?) as rank from last_candle lc inner join downloadersymbolsettings dss on lc.symbolid = dss.symbolid inner join datafeedstimetable dtt on trim(dss.classname) = trim(dtt.classname) and dtt.dayofweek = ? -- assuming timezone is same for whole week. inner join powerstats_symboldata psd on psd.symbolid = lc.symbolid left outer join powerstats_trumpet psp on psd.trumpetsymbolid = psp.symbolid and psp.dayofweek = extract(dow from lc.latest_candle_time) and psp.fromtime = cast(extract(? from lc.latest_candle_time) as integer) * ? + extract(? from (cast(extract(? from lc.latest_candle_time) as integer) / ?) * ? * interval ?) inner join prfsymboltree prf on psd.symbolid = prf.symbolid and date_trunc(?, prf.enddate) = date_trunc(?, psp.enddate) left join lateral ( select ph.hour, (ave + stddev) as volatility, rank() over (order by (ave + stddev) desc) as rank from powerstats_hourly ph where ph.symbolid = psd.hourlysymbolid and date_trunc(?,ph.enddate) = date_trunc(?, prf.enddate) ) rank_query on true where prf.brokerid = ? and rank_query.hour = floor((psp.fromtime) / ?) and volatility > ? order by rank desc, rank_rounded desc, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Apr 04 09 112 43s6ms 383ms [ User: postgres - Total duration: 43s6ms - Times executed: 112 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 43s6ms - Times executed: 112 ]
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-04-04 09:56:00 Duration: 881ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '538' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '538' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-04-04 09:00:07 Duration: 850ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-04-04 09:32:00 Duration: 821ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
9 34s590ms 6 4s465ms 8s535ms 5s765ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Apr 04 09 6 34s590ms 5s765ms [ User: postgres - Total duration: 34s590ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 34s590ms - Times executed: 6 ]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-04-04 09:00:11 Duration: 8s535ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-04-04 09:30:10 Duration: 7s922ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-04-04 09:10:07 Duration: 4s614ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
10 33s143ms 162 32ms 813ms 204ms with rar_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ), all_results as ( select bmr.resultuid as resultuid, ? as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, bmr.patternendtime as identified, bmr.patternlengthbars, dtt.timezone as timezone, g.basegroupname, case when rbr.age is not null then rbr.age when bmr.resultuid <= rm.resultuid then ? else ? end as age, case when rbr.relevant is not null then rbr.relevant when bmr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from bigmovement_results bmr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = bmr.symbolid inner join symbols s on bmr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on bmr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on bmr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bmr.gmttimefound > now() - interval ? and s.deleted = ? and (bmr.simulation = ? or bmr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or bmr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, interval desc;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Apr 04 09 162 33s143ms 204ms [ User: postgres - Total duration: 33s143ms - Times executed: 162 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 27s21ms - Times executed: 150 ]
[ Application: [unknown] - Total duration: 6s122ms - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_bigmovement_results rbr ON rbr.resultuid = bmr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR bmr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, interval DESC;
Date: 2025-04-04 09:31:10 Duration: 813ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_bigmovement_results rbr ON rbr.resultuid = bmr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR bmr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, interval DESC;
Date: 2025-04-04 09:46:17 Duration: 793ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_bigmovement_results rbr ON rbr.resultuid = bmr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR bmr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, interval DESC;
Date: 2025-04-04 09:01:12 Duration: 737ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
11 31s160ms 34 12ms 11s860ms 916ms select fixcandlegaps (?, false);Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Apr 04 09 34 31s160ms 916ms [ User: postgres - Total duration: 31s160ms - Times executed: 34 ]
[ Application: psql - Total duration: 31s160ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-04-04 09:06:32 Duration: 11s860ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-04-04 09:06:09 Duration: 3s848ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('AXIORY', false);
Date: 2025-04-04 09:06:12 Duration: 2s866ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
12 29s430ms 16 1s599ms 2s659ms 1s839ms with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Apr 04 09 16 29s430ms 1s839ms [ User: postgres - Total duration: 29s430ms - Times executed: 16 ]
[ Application: psql - Total duration: 29s430ms - Times executed: 16 ]
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:46:15 Duration: 2s659ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:11:16 Duration: 2s642ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:31:15 Duration: 2s271ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
13 22s347ms 408 0ms 280ms 54ms select distinct a.resultuid as ruid, c.symbolid as sid, c.symbol as sym, c.longname as longname, c.shortname, c.exchange as e, c.timegranularity as tg, p.patternid as pid, a.direction as d, cast(atbaridentified as timestamp) as pet, cast(patternstarttime as timestamp) as pst, patternprice as patp, breakoutprice as pe, breakoutbars as be, errormargin as erm, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, cast(x0 as timestamp) as x0, cast(x1 as timestamp) as x1, cast(x2 as timestamp) as x2, cast(( case when x3 = ? then ? else x3 end) as timestamp) as x3, cast(( case when x4 = ? then ? else x4 end) as timestamp) as x4, cast(( case when x5 = ? then ? else x5 end) as timestamp) as x5, cast(( case when x6 = ? then ? else x6 end) as timestamp) as x6, cast(( case when x7 = ? then ? else x7 end) as timestamp) as x7, cast(( case when x8 = ? then ? else x8 end) as timestamp) as x8, cast(( case when x9 = ? then ? else x9 end) as timestamp) as x9, cast(atbaridentified as timestamp) as patternendtime, cast(atbaridentified as timestamp) as atbar, cast(( case when approachingtimestamp = ? then ? else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzos, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as relevant, cast(?.? as double precision) as premium, cast(? as bigint) as instrumentid, ? as derivativeid, ? as underlyingid, ? as isunderlying from symbols c inner join brokersymbollist b on c.symbolid = b.symbolid inner join symbolgroup sg on c.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = c.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join keylevels_results a on a.symbolid = c.symbolid inner join hrspatterns p on a.patternid = p.patternid left outer join relevance_keylevels_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and patternclassid = ? and patternlengthbars >= ? and a.patternid & ? > ? and dftt.dayofweek = ? and a.qtytp >= ? and a.resultuid > ? and c.nonliquid = ? and c.deleted = ? and dss.enabled = ? order by relevant desc, age asc, patternendtime desc, qtp desc limit ?;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Apr 04 09 408 22s347ms 54ms [ User: postgres - Total duration: 22s347ms - Times executed: 408 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 22s347ms - Times executed: 408 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059718346308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '1574284935' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:46:15 Duration: 280ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059718346308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '0' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:14:12 Duration: 279ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059718346308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '768290927' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:18:13 Duration: 273ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
14 20s414ms 16 1s251ms 1s328ms 1s275ms with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = ? left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bg.brokerid and bim.type = ? where bg.brokerid = ? and basegroupname = ? and g.designation = ? and s.nonliquid = ? ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= ? and patternquality >= ?.? and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, case when direction > ? then ? else ? end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (...) and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= ? and _tmp.qtycandlesapart <= ? and ((cpresultuid > ( select coalesce(max(cpresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?)) or (klresultuid > ( select coalesce(max(klresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = ? and cs.basegroupname = ? and date_trunc(?, cs.gmttimefound) = date_trunc(?, now()) and sent is true and filtered is false ) <= ( select case when coalesce(daily_max, ?) < ? then ? else coalesce(daily_max,?) end from corr_sigs_config_v where broker_id = ? ) and extract(epoch from age(current_timestamp at time zone ?, max_patternendtime - absolutetimezoneoffset * interval ?))/? < mint*? ), maxstats as ( select max(statsid) as maxid , st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = ? then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * ? as numeric), ?) as percent, round(cast((kl_correct) / (kl_total) * ? as numeric), ?) as klpercent, round(cast((cp_correct ) / (cp_total ) * ? as numeric), ?) as cppercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), ?) as openprice, round(cast(sig.forecastprice as numeric), ?) as forecastprice, cast(round(cast(abs(sig.forecastprice - sig.openprice)/pip as numeric), ?)as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname , si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = ? then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = ? and date_part(?, sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = ? and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = ? and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = ? and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = ? and date_part(?, sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = ? and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = ? and kl_sym.name ilike si.symbol ) as tmp order by tmp.gmttimefound desc;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Apr 04 09 16 20s414ms 1s275ms [ User: postgres - Total duration: 20s414ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 20s414ms - Times executed: 16 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '617' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '617' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '617') and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-04-04 09:36:52 Duration: 1s328ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '627' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '627' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '627') and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-04-04 09:07:05 Duration: 1s298ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '617' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '617' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '617') and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-04-04 09:51:46 Duration: 1s297ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
15 13s313ms 16 602ms 1s535ms 832ms update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Apr 04 09 16 13s313ms 832ms [ User: postgres - Total duration: 13s313ms - Times executed: 16 ]
[ Application: psql - Total duration: 13s313ms - Times executed: 16 ]
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:11:13 Duration: 1s535ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:46:12 Duration: 1s62ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:31:12 Duration: 1s36ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
16 11s680ms 13 40ms 10s300ms 898ms copy ( select array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ?) as broker_ids, string_to_array(coalesce(replace(broker_symbol_mappings, ?, ?), ?), ?) as broker_symbol_mappings, replace(exchange, ?, ?) as exchange, symbol_id, replace(symbol, ?, ?) as symbol, replace(short_name, ?, ?) as short_name, replace(long_name, ?, ?) as long_name, interval, replace(timezone, ?, ?) as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ?) as search_groups, string_to_array(pattern_basegroupnames, ?) as base_groups, simulation from solr_fetch_results_bm_and_cc (?::character varying, current_timestamp::timestamp without time zone)) t) to ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Apr 04 09 13 11s680ms 898ms [ User: postgres - Total duration: 11s680ms - Times executed: 13 ]
[ Application: psql - Total duration: 11s680ms - Times executed: 13 ]
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-04-04 09:03:12 Duration: 10s300ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-04-04 09:01:02 Duration: 343ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-04-04 09:11:03 Duration: 285ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
17 11s499ms 177 16ms 282ms 64ms select distinct a.symbolid, p.resultuid, case when a.breakout >= ? then ? else ? end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient from relevance_autochartist_results p inner join autochartist_results a on p.resultuid = a.resultuid inner join autochartist_stocklist asl on a.symbolid = asl.symbolid where asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Apr 04 09 177 11s499ms 64ms [ User: postgres - Total duration: 11s499ms - Times executed: 177 ]
[ Application: [unknown] - Total duration: 11s499ms - Times executed: 177 ]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2025-04-04 09:02:49 Duration: 282ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'PEPPERSTONE - 1';
Date: 2025-04-04 09:15:40 Duration: 260ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'PEPPERSTONE - 1';
Date: 2025-04-04 09:15:45 Duration: 249ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
18 8s436ms 5,451 0ms 26ms 1ms insert into autochartist_results (resultid, symbolid, bandwidth, pattern, qtytp, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, relevancestartdistance, simulation, writtendatetime) values (?, ?, ?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Apr 04 09 5,451 8s436ms 1ms [ User: postgres - Total duration: 8s436ms - Times executed: 5451 ]
[ Application: [unknown] - Total duration: 8s436ms - Times executed: 5451 ]
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INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('515840245889894300-1|45751.1354|45751.4062|45750.8958|45751.2708|7.2828|7.2499|7.2768|7.2442', 515840245889894300, 3.000000000000000000000000000000, 'Channel Down', 4, '2025-04-04 07:11:49'::timestamp without time zone, - 1, 0.050294931785751090240000000000, - 1.000000000000000000000000000000, 1.000000000000000000000000000000, 0.207836273967373919000000000000, 0.721009840865969531200000000000, 7.237320183351147130000000000000, 7.239501743062978001000000000000, '2025-04-04 10:00:00'::timestamp without time zone, '2025-04-04 16:15:00'::timestamp without time zone, '2025-04-03 18:45:00'::timestamp without time zone, '2025-04-04 10:00:00'::timestamp without time zone, 7.290790000000000326000000000000, 7.238349999999999618000000000000, '2025-04-04 03:15:00'::timestamp without time zone, '2025-04-04 09:45:00'::timestamp without time zone, '2025-04-03 21:30:00'::timestamp without time zone, '2025-04-04 06:30:00'::timestamp without time zone, 7.282759999999999678000000000000, 7.249920000000000364000000000000, 7.276779999999999582000000000000, 7.244170000000000442000000000000, - 0.000931714285714261105700000000, - 0.001263076923076896733000000000, 2.088363532057903260000000000000, 0.521156166228115558200000000000, 'Continuation', 0.000000000000000000000000000000, '2025-04-04 10:00:00'::timestamp without time zone, 7.241060000000000052000000000000, 49, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-04-04 09:15:40 Duration: 26ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('515840245888296300-1|45749.125|45750.75|45750.4792|45751.375|4.1813|4.2266|4.1706|4.2224', 515840245888296300, 5.000000000000000000000000000000, 'Rising Wedge', 4, '2025-04-04 06:57:40'::timestamp without time zone, 1, 0.018696974613945115120000000000, - 1.000000000000000000000000000000, 1.000000000000000000000000000000, 0.403942363339449717100000000000, 0.868569561685199498200000000000, 4.233282900407003169000000000000, 4.236968960976807530000000000000, '2025-04-04 09:30:00'::timestamp without time zone, '2025-04-05 12:45:00'::timestamp without time zone, '2025-04-02 00:00:00'::timestamp without time zone, '2025-04-04 09:30:00'::timestamp without time zone, 4.173799999999999954000000000000, 4.230940000000000367000000000000, '2025-04-02 03:00:00'::timestamp without time zone, '2025-04-03 18:00:00'::timestamp without time zone, '2025-04-03 11:30:00'::timestamp without time zone, '2025-04-04 09:00:00'::timestamp without time zone, 4.181269999999999598000000000000, 4.226569999999999716000000000000, 4.170620000000000438000000000000, 4.222369999999999734000000000000, 0.001203488372093006967000000000, 0.000580769230769232250800000000, 1.978010031223551790000000000000, 0.494441390986564977000000000000, 'Continuation', 0.000000000000000000000000000000, '2025-04-04 09:30:00'::timestamp without time zone, 4.230649999999999800000000000000, 109, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-04-04 09:01:31 Duration: 13ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('515840245888296300-1|45749.125|45750.75|45750.4792|45751.375|4.1813|4.2266|4.1706|4.2224', 515840245888296300, 4.000000000000000000000000000000, 'Rising Wedge', 4, '2025-04-04 06:57:40'::timestamp without time zone, 1, 0.018696974613945115120000000000, - 1.000000000000000000000000000000, 1.000000000000000000000000000000, 0.403942363339449717100000000000, 0.868569561685199498200000000000, 4.233282900407003169000000000000, 4.236968960976807530000000000000, '2025-04-04 09:30:00'::timestamp without time zone, '2025-04-05 12:45:00'::timestamp without time zone, '2025-04-02 00:00:00'::timestamp without time zone, '2025-04-04 09:30:00'::timestamp without time zone, 4.173799999999999954000000000000, 4.230940000000000367000000000000, '2025-04-02 03:00:00'::timestamp without time zone, '2025-04-03 18:00:00'::timestamp without time zone, '2025-04-03 11:30:00'::timestamp without time zone, '2025-04-04 09:00:00'::timestamp without time zone, 4.181269999999999598000000000000, 4.226569999999999716000000000000, 4.170620000000000438000000000000, 4.222369999999999734000000000000, 0.001203488372093006967000000000, 0.000580769230769232250800000000, 1.978010031223551790000000000000, 0.494441390986564977000000000000, 'Continuation', 0.000000000000000000000000000000, '2025-04-04 09:30:00'::timestamp without time zone, 4.230649999999999800000000000000, 109, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-04-04 09:01:31 Duration: 13ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
19 7s720ms 6 1s184ms 1s453ms 1s286ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Apr 04 09 6 7s720ms 1s286ms [ User: postgres - Total duration: 7s720ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 7s720ms - Times executed: 6 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-04-04 09:46:17 Duration: 1s453ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-04-04 09:01:15 Duration: 1s445ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-04-04 09:31:17 Duration: 1s243ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
20 6s846ms 156 0ms 1s33ms 43ms select distinct patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, longname, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as relevant from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join symbolgroup sg on s.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join autochartist_results a on a.symbolid = s.symbolid inner join patterns p on a.pattern = p.patternname left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and breakout >= ?.? and patternendtime = latestbaratbreakouttime and patternlengthbars >= ? and patternquality >= ?.? and initialtrend >= ?.? and symmetry >= ?.? and noise <= ?.? and volumeincrease >= ?.? and temporarypattern = ? and patternid & ? > ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and a.resultuid > ? and s.nonliquid = ? and dftt.dayofweek = ? order by relevant desc, age asc, patternendtime desc, patternquality desc limit ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Apr 04 09 156 6s846ms 43ms [ User: postgres - Total duration: 6s846ms - Times executed: 156 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 6s846ms - Times executed: 156 ]
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 605887074825963301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-04-04 09:18:13 Duration: 1s33ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 605886779931507301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-04-04 09:18:13 Duration: 932ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 605883281612025301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-04-04 09:18:13 Duration: 868ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 52,129 270ms 0ms 19ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Apr 04 09 52,129 270ms 0ms [ User: postgres - Total duration: 270ms - Times executed: 52129 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 258ms - Times executed: 51823 ]
[ Application: [unknown] - Total duration: 11ms - Times executed: 306 ]
-
select 1;
Date: 2025-04-04 09:00:05 Duration: 19ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-04-04 09:00:04 Duration: 14ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-04-04 09:00:05 Duration: 12ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
2 32,330 47s730ms 0ms 23ms 1ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Apr 04 09 32,330 47s730ms 1ms [ User: postgres - Total duration: 47s730ms - Times executed: 32330 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 47s730ms - Times executed: 32330 ]
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840249425757300';
Date: 2025-04-04 09:00:06 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243265160300';
Date: 2025-04-04 09:00:05 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840233391195300';
Date: 2025-04-04 09:00:05 Duration: 22ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
3 29,091 1m42s 0ms 41ms 3ms select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Apr 04 09 29,091 1m42s 3ms [ User: postgres - Total duration: 1m42s - Times executed: 29091 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m42s - Times executed: 29091 ]
-
SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'MCD.US' OR dss.downloadersymbol = 'MCD.US') AND dss.enabled = 1;
Date: 2025-04-04 09:30:05 Duration: 41ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'AUDCAD' OR dss.downloadersymbol = 'AUDCAD') AND dss.enabled = 1;
Date: 2025-04-04 09:30:07 Duration: 39ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'EURNOK' OR dss.downloadersymbol = 'EURNOK') AND dss.enabled = 1;
Date: 2025-04-04 09:30:04 Duration: 33ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
4 6,169 6s829ms 0ms 21ms 1ms insert into t15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Apr 04 09 6,169 6s829ms 1ms [ User: postgres - Total duration: 6s829ms - Times executed: 6169 ]
[ Application: [unknown] - Total duration: 6s829ms - Times executed: 6169 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-04-04 10:00:00', '7674.45', '7680.35', '7663.55', '7669.95', '431', '515840248015086300', '0', '2025-04-04 09:25:38.294', '2025-04-04 09:25:38.256') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '7674.45', high = '7680.35', low = '7663.55', close = '7669.95', volume = '431', bsf = '0', sastdatetimewritten = '2025-04-04 09:25:38.294', sastdatetimereceived = '2025-04-04 09:25:38.256';
Date: 2025-04-04 09:25:38 Duration: 21ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-04-04 10:30:00', '1.30481', '1.30525', '1.30207', '1.3025', '6748', '515840245854602300', '0', '2025-04-04 09:45:04.315', '2025-04-04 09:45:04.238') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '1.30481', high = '1.30525', low = '1.30207', close = '1.3025', volume = '6748', bsf = '0', sastdatetimewritten = '2025-04-04 09:45:04.315', sastdatetimereceived = '2025-04-04 09:45:04.238';
Date: 2025-04-04 09:45:04 Duration: 17ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-04-04 10:00:00', '83032.83', '83559.97', '83010.36', '83511.08', '10424', '605679104043714300', '0', '2025-04-04 09:30:03.892', '2025-04-04 09:30:03.849') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '83032.83', high = '83559.97', low = '83010.36', close = '83511.08', volume = '10424', bsf = '0', sastdatetimewritten = '2025-04-04 09:30:03.892', sastdatetimereceived = '2025-04-04 09:30:03.849';
Date: 2025-04-04 09:30:03 Duration: 15ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
5 5,451 8s436ms 0ms 26ms 1ms insert into autochartist_results (resultid, symbolid, bandwidth, pattern, qtytp, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, relevancestartdistance, simulation, writtendatetime) values (?, ?, ?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Apr 04 09 5,451 8s436ms 1ms [ User: postgres - Total duration: 8s436ms - Times executed: 5451 ]
[ Application: [unknown] - Total duration: 8s436ms - Times executed: 5451 ]
-
INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('515840245889894300-1|45751.1354|45751.4062|45750.8958|45751.2708|7.2828|7.2499|7.2768|7.2442', 515840245889894300, 3.000000000000000000000000000000, 'Channel Down', 4, '2025-04-04 07:11:49'::timestamp without time zone, - 1, 0.050294931785751090240000000000, - 1.000000000000000000000000000000, 1.000000000000000000000000000000, 0.207836273967373919000000000000, 0.721009840865969531200000000000, 7.237320183351147130000000000000, 7.239501743062978001000000000000, '2025-04-04 10:00:00'::timestamp without time zone, '2025-04-04 16:15:00'::timestamp without time zone, '2025-04-03 18:45:00'::timestamp without time zone, '2025-04-04 10:00:00'::timestamp without time zone, 7.290790000000000326000000000000, 7.238349999999999618000000000000, '2025-04-04 03:15:00'::timestamp without time zone, '2025-04-04 09:45:00'::timestamp without time zone, '2025-04-03 21:30:00'::timestamp without time zone, '2025-04-04 06:30:00'::timestamp without time zone, 7.282759999999999678000000000000, 7.249920000000000364000000000000, 7.276779999999999582000000000000, 7.244170000000000442000000000000, - 0.000931714285714261105700000000, - 0.001263076923076896733000000000, 2.088363532057903260000000000000, 0.521156166228115558200000000000, 'Continuation', 0.000000000000000000000000000000, '2025-04-04 10:00:00'::timestamp without time zone, 7.241060000000000052000000000000, 49, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-04-04 09:15:40 Duration: 26ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('515840245888296300-1|45749.125|45750.75|45750.4792|45751.375|4.1813|4.2266|4.1706|4.2224', 515840245888296300, 5.000000000000000000000000000000, 'Rising Wedge', 4, '2025-04-04 06:57:40'::timestamp without time zone, 1, 0.018696974613945115120000000000, - 1.000000000000000000000000000000, 1.000000000000000000000000000000, 0.403942363339449717100000000000, 0.868569561685199498200000000000, 4.233282900407003169000000000000, 4.236968960976807530000000000000, '2025-04-04 09:30:00'::timestamp without time zone, '2025-04-05 12:45:00'::timestamp without time zone, '2025-04-02 00:00:00'::timestamp without time zone, '2025-04-04 09:30:00'::timestamp without time zone, 4.173799999999999954000000000000, 4.230940000000000367000000000000, '2025-04-02 03:00:00'::timestamp without time zone, '2025-04-03 18:00:00'::timestamp without time zone, '2025-04-03 11:30:00'::timestamp without time zone, '2025-04-04 09:00:00'::timestamp without time zone, 4.181269999999999598000000000000, 4.226569999999999716000000000000, 4.170620000000000438000000000000, 4.222369999999999734000000000000, 0.001203488372093006967000000000, 0.000580769230769232250800000000, 1.978010031223551790000000000000, 0.494441390986564977000000000000, 'Continuation', 0.000000000000000000000000000000, '2025-04-04 09:30:00'::timestamp without time zone, 4.230649999999999800000000000000, 109, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-04-04 09:01:31 Duration: 13ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('515840245888296300-1|45749.125|45750.75|45750.4792|45751.375|4.1813|4.2266|4.1706|4.2224', 515840245888296300, 4.000000000000000000000000000000, 'Rising Wedge', 4, '2025-04-04 06:57:40'::timestamp without time zone, 1, 0.018696974613945115120000000000, - 1.000000000000000000000000000000, 1.000000000000000000000000000000, 0.403942363339449717100000000000, 0.868569561685199498200000000000, 4.233282900407003169000000000000, 4.236968960976807530000000000000, '2025-04-04 09:30:00'::timestamp without time zone, '2025-04-05 12:45:00'::timestamp without time zone, '2025-04-02 00:00:00'::timestamp without time zone, '2025-04-04 09:30:00'::timestamp without time zone, 4.173799999999999954000000000000, 4.230940000000000367000000000000, '2025-04-02 03:00:00'::timestamp without time zone, '2025-04-03 18:00:00'::timestamp without time zone, '2025-04-03 11:30:00'::timestamp without time zone, '2025-04-04 09:00:00'::timestamp without time zone, 4.181269999999999598000000000000, 4.226569999999999716000000000000, 4.170620000000000438000000000000, 4.222369999999999734000000000000, 0.001203488372093006967000000000, 0.000580769230769232250800000000, 1.978010031223551790000000000000, 0.494441390986564977000000000000, 'Continuation', 0.000000000000000000000000000000, '2025-04-04 09:30:00'::timestamp without time zone, 4.230649999999999800000000000000, 109, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-04-04 09:01:31 Duration: 13ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
6 3,589 1s872ms 0ms 7ms 0ms insert into t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Apr 04 09 3,589 1s872ms 0ms [ User: postgres - Total duration: 1s872ms - Times executed: 3589 ]
[ Application: [unknown] - Total duration: 1s872ms - Times executed: 3589 ]
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-04-04 09:30:00', '0.94588', '0.94646', '0.94543', '0.94572', '3881', '515840247874733300', '0', '2025-04-04 09:00:44.998', '2025-04-04 09:00:44.827') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.94588', high = '0.94646', low = '0.94543', close = '0.94572', volume = '3881', bsf = '0', sastdatetimewritten = '2025-04-04 09:00:44.998', sastdatetimereceived = '2025-04-04 09:00:44.827';
Date: 2025-04-04 09:00:45 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-04-03 18:00:00', '21.2628', '21.37', '21.25', '21.26', '412', '515840247904216300', '0', '2025-04-04 09:02:28.478', '2025-04-04 09:02:28.354') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '21.2628', high = '21.37', low = '21.25', close = '21.26', volume = '412', bsf = '0', sastdatetimewritten = '2025-04-04 09:02:28.478', sastdatetimereceived = '2025-04-04 09:02:28.354';
Date: 2025-04-04 09:02:28 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-04-04 09:30:00', '14.064', '14.074', '14.031', '14.034', '1832', '515840247908557300', '0', '2025-04-04 09:00:51.096', '2025-04-04 09:00:51.03') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '14.064', high = '14.074', low = '14.031', close = '14.034', volume = '1832', bsf = '0', sastdatetimewritten = '2025-04-04 09:00:51.096', sastdatetimereceived = '2025-04-04 09:00:51.03';
Date: 2025-04-04 09:00:51 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
7 2,870 2s240ms 0ms 5ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Apr 04 09 2,870 2s240ms 0ms [ User: postgres - Total duration: 2s240ms - Times executed: 2870 ]
[ Application: [unknown] - Total duration: 2s240ms - Times executed: 2870 ]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-04-03 18:15:00', reason = 'Emerging pattern broke out in the wrong direction.' WHERE uniqueIndex = '515840233354856300-1|45749.7604|45750.6875|45747.5417|45750.4583|221.32|200.92|214.02|196.75' and relevant = 1;
Date: 2025-04-04 09:02:06 Duration: 5ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-04-04 10:00:00', reason = 'Price has entered the prediction area for a completed pattern.' WHERE uniqueIndex = '|515840247943103300|21.5808|2|2025-04-03 17:45:00|-1|1' and relevant = 1;
Date: 2025-04-04 09:16:12 Duration: 5ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-04-03 18:00:00', reason = 'Pattern has turned opposite direction' WHERE uniqueIndex = '3 Point Extension|1|2025-03-31 16:30:00|4520.14|4461.16|3|49|CD=1.618*BC (1.613)|0|515840233311028300|1899-12-29 00:00:00|1899-12-29 00:00:00|2025-03-31 16:30:00|2025-04-01 12:30:00|2025-04-03 15:30:00' and relevant = 1;
Date: 2025-04-04 09:32:16 Duration: 4ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
8 2,695 231ms 0ms 2ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Apr 04 09 2,695 231ms 0ms [ User: postgres - Total duration: 231ms - Times executed: 2695 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 231ms - Times executed: 2695 ]
-
select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = '601729875361650307' and category = lower('initialtrend') union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = '601729875361650307' and category = lower('initialtrend') order by correct desc) as summdata group by category, name having sum(total) > 0 ORDER BY name;
Date: 2025-04-04 09:01:00 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = '515852059297940307' and category = lower('direction') union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = '515852059297940307' and category = lower('direction') order by correct desc) as summdata group by category, name having sum(total) > 0 ORDER BY name;
Date: 2025-04-04 09:00:52 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = '515852059317765307' and category = lower('significant') union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = '515852059317765307' and category = lower('significant') order by correct desc) as summdata group by category, name having sum(total) > 0 ORDER BY name;
Date: 2025-04-04 09:00:49 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
9 2,288 4s133ms 0ms 11ms 1ms insert into keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errormargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestprice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) values (?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?, ?, ?.?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?.?, ?::timestamp without time zone, ?, ?.?, ?.?, ?, ?, ?.?, ?.?, ?::timestamp without time zone, ?, ?, ?.?, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Apr 04 09 2,288 4s133ms 1ms [ User: postgres - Total duration: 4s133ms - Times executed: 2288 ]
[ Application: [unknown] - Total duration: 4s133ms - Times executed: 2288 ]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, - 1, 1, '2025-04-04 06:57:47'::timestamp without time zone, '2025-04-04 09:00:00', 0.098950000000000065680000000000, 4, 60, 10.475550000000000139000000000000, '2025-04-03 01:00:00', '2025-04-02 10:00:00', '2025-04-02 04:00:00', '2025-04-01 21:00:00', '', '', '', '', '', '', 70, 10.480360499999999746000000000000, '2025-04-04 09:00:00'::timestamp without time zone, '2025-04-04 09:00:00', 10.394949999999999690000000000000, 0.005989999999999979716000000000, 1, 515840247987373300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840247987373300|10.47555|1|2025-04-04 09:00:00|2025-04-04 09:00:00|1|-1', 10.338998999999999384000000000000, 0.136551000000000755100000000000, 2, '2025-04-01 21:00:00', 10.301809999999999690000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-04-04 09:01:39 Duration: 11ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, - 1, 2, '2025-04-04 06:57:38'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 68, 401.637999999999976800000000000000, '2025-04-04 02:00:00', '2025-04-01 12:00:00', '2025-04-01 06:00:00', '', '', '', '', '', '', '', 136, 401.399249999999995000000000000000, '2025-04-04 09:00:00'::timestamp without time zone, '2025-04-04 09:00:00', 0.000000000000000000000000000000, 0.238750000000001710800000000000, 1, 515840245887452300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840245887452300|401.638|2|2025-04-04 09:00:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-04-01 06:00:00', 398.307000000000016400000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-04-04 09:01:30 Duration: 10ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (9.000000000000000000000000000000, - 1, 2, '2025-04-04 06:57:27'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 82, 37.879579999999997140000000000000, '2025-04-04 00:30:00', '2025-04-03 13:30:00', '2025-04-02 07:30:00', '', '', '', '', '', '', '', 164, 37.857925999999999080000000000000, '2025-04-04 02:30:00'::timestamp without time zone, '2025-04-04 02:30:00', 0.000000000000000000000000000000, 0.021653999999999840040000000000, 1, 515840249509618300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249509618300|37.87958|2|2025-04-04 02:30:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-04-02 07:30:00', 37.419260000000001300000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-04-04 09:01:19 Duration: 10ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
10 2,241 1s135ms 0ms 8ms 0ms insert into fibonacci_results (bandwidth, pattern, gmttimefound, direction, patternstarttime, patternendtime, patternstartprice, patternendprice, qtytp, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, patternlengthbars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) values (?.?, ?, ?::timestamp without time zone, ?, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?, ?, ?, ?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Apr 04 09 2,241 1s135ms 0ms [ User: postgres - Total duration: 1s135ms - Times executed: 2241 ]
[ Application: [unknown] - Total duration: 1s135ms - Times executed: 2241 ]
-
INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (3.000000000000000000000000000000, 'Gartley', '2025-04-04 06:57:56'::timestamp without time zone, - 1, '2025-04-02 20:00:00'::timestamp without time zone, '2025-04-04 06:00:00'::timestamp without time zone, 112.349999999999994300000000000000, - 1.000000000000000000000000000000, 5, 112.349999999999994300000000000000, '2025-04-02 20:00:00'::timestamp without time zone, 108.887500000000002800000000000000, '2025-04-03 14:00:00'::timestamp without time zone, 109.767499999999998300000000000000, '2025-04-04 02:00:00'::timestamp without time zone, 109.046999999999997000000000000000, '2025-04-04 04:00:00'::timestamp without time zone, 110.210057314126245800000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.693969879522680521700000000000, - 1.000000000000000000000000000000, 13.534282792711890050000000000000, 47, 109.046999999999997000000000000000, 109.491248363190095500000000000000, 108.328191049063846700000000000000, 109.295718204165524400000000000000, 108.730625557062964500000000000000, 109.628528657063128600000000000000, 109.765808950936147400000000000000, 515840249645418300, 0.612060240954638956600000000000, 'BC=0.786*AB (0.819) ', 0, 'Gartley|-1|2025-04-02 20:00:00|112.35|-1|5|47|BC=0.786*AB (0.819)|0|515840249645418300|2025-04-02 20:00:00|2025-04-03 14:00:00|2025-04-04 02:00:00|2025-04-04 04:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-04-04 09:01:48 Duration: 8ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (3.000000000000000000000000000000, 'Gartley', '2025-04-04 06:57:05'::timestamp without time zone, 1, '2025-04-03 21:15:00'::timestamp without time zone, '2025-04-04 09:45:00'::timestamp without time zone, 81588.574999999997090000000000000000, - 1.000000000000000000000000000000, 5, 81588.574999999997090000000000000000, '2025-04-03 21:15:00'::timestamp without time zone, 83452.725000000005820000000000000000, '2025-04-04 03:30:00'::timestamp without time zone, 82651.324999999997090000000000000000, '2025-04-04 04:45:00'::timestamp without time zone, 83276.725000000005820000000000000000, '2025-04-04 09:15:00'::timestamp without time zone, 82300.616939964893390000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.799331940030271415000000000000, - 1.000000000000000000000000000000, 9.063148919718130969000000000000, 56, 83276.725000000005820000000000000000, 82903.884897710609950000000000000000, 83879.992957745722380000000000000000, 83067.985636243189220000000000000000, 83542.245572364889080000000000000000, 82788.670969982456880000000000000000, 82673.457042254289260000000000000000, 515840249391752300, 0.401336119939457280900000000000, 'BC=0.786*AB (0.78) ', 0, 'Gartley|1|2025-04-03 21:15:00|81588.575|-1|5|56|BC=0.786*AB (0.78)|0|515840249391752300|2025-04-03 21:15:00|2025-04-04 03:30:00|2025-04-04 04:45:00|2025-04-04 09:15:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-04-04 09:00:57 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (3.000000000000000000000000000000, 'Gartley', '2025-04-04 06:56:33'::timestamp without time zone, - 1, '2025-04-02 23:00:00'::timestamp without time zone, '2025-04-04 09:00:00'::timestamp without time zone, 112.353499999999996800000000000000, - 1.000000000000000000000000000000, 5, 112.353499999999996800000000000000, '2025-04-02 23:00:00'::timestamp without time zone, 108.896000000000000800000000000000, '2025-04-03 17:00:00'::timestamp without time zone, 109.766999999999995900000000000000, '2025-04-04 05:00:00'::timestamp without time zone, 109.065500000000000100000000000000, '2025-04-04 08:00:00'::timestamp without time zone, 110.216647484069753200000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.710603661107804596200000000000, - 1.000000000000000000000000000000, 13.591154795853967130000000000000, 48, 109.065500000000000100000000000000, 109.505199212908152600000000000000, 108.354051728838399500000000000000, 109.311671303417313100000000000000, 108.752365264860543400000000000000, 109.641073742034876700000000000000, 109.776948271161600700000000000000, 605679104088799300, 0.578792677784390696700000000000, 'BC=0.786*AB (0.805) ', 0, 'Gartley|-1|2025-04-02 23:00:00|112.3535|-1|5|48|BC=0.786*AB (0.805)|0|605679104088799300|2025-04-02 23:00:00|2025-04-03 17:00:00|2025-04-04 05:00:00|2025-04-04 08:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-04-04 09:00:24 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
11 2,229 1s24ms 0ms 7ms 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Apr 04 09 2,229 1s24ms 0ms [ User: postgres - Total duration: 1s24ms - Times executed: 2229 ]
[ Application: [unknown] - Total duration: 1s24ms - Times executed: 2229 ]
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-04-04 09:00:00', '33.73', '33.9', '33.09', '33.47', '1783', '515840247893649300', '0', '2025-04-04 09:00:59.557', '2025-04-04 09:00:59.458') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '33.73', high = '33.9', low = '33.09', close = '33.47', volume = '1783', bsf = '0', sastdatetimewritten = '2025-04-04 09:00:59.557', sastdatetimereceived = '2025-04-04 09:00:59.458';
Date: 2025-04-04 09:00:59 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-04-04 09:00:00', '40432.65', '40441.65', '40299.65', '40317.15', '6464', '515840248000890300', '0', '2025-04-04 09:10:55.212', '2025-04-04 09:10:55.164') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '40432.65', high = '40441.65', low = '40299.65', close = '40317.15', volume = '6464', bsf = '0', sastdatetimewritten = '2025-04-04 09:10:55.212', sastdatetimereceived = '2025-04-04 09:10:55.164';
Date: 2025-04-04 09:10:55 Duration: 6ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-04-03 20:00:00', '13212.2', '13225.2', '13182.4', '13202.2', '1998', '515840248005928300', '0', '2025-04-04 09:01:42.066', '2025-04-04 09:01:41.946') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '13212.2', high = '13225.2', low = '13182.4', close = '13202.2', volume = '1998', bsf = '0', sastdatetimewritten = '2025-04-04 09:01:42.066', sastdatetimereceived = '2025-04-04 09:01:41.946';
Date: 2025-04-04 09:01:42 Duration: 6ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
12 1,996 515ms 0ms 3ms 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars as length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternstartprice, resy1, supporty1, dtt.timezone, cps.pip, newlevels.profit from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern left join currencypips cps on cps.symbol = s.symbol left join lateral calc_cp_signal (a.resultuid) newlevels on true where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Apr 04 09 1,996 515ms 0ms [ User: postgres - Total duration: 515ms - Times executed: 1996 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 513ms - Times executed: 1989 ]
[ Application: [unknown] - Total duration: 2ms - Times executed: 7 ]
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SELECT CASE WHEN a.old_resultuid = '605887311455088301' THEN a.old_resultuid ELSE a.resultuid END as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars AS length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternStartPrice, resy1, supporty1, dtt.timezone, cps.pip, newLevels.profit FROM autochartist_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid INNER JOIN patterns p ON p.patternname = a.pattern LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT JOIN LATERAL calc_cp_signal (a.resultuid) newLevels on true WHERE (a.old_resultuid = '605887311455088301' OR a.resultuid = '605887311455088301') AND dtt.dayofweek = 3;
Date: 2025-04-04 09:37:31 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '605887367747804301' THEN a.old_resultuid ELSE a.resultuid END as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars AS length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternStartPrice, resy1, supporty1, dtt.timezone, cps.pip, newLevels.profit FROM autochartist_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid INNER JOIN patterns p ON p.patternname = a.pattern LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT JOIN LATERAL calc_cp_signal (a.resultuid) newLevels on true WHERE (a.old_resultuid = '605887367747804301' OR a.resultuid = '605887367747804301') AND dtt.dayofweek = 3;
Date: 2025-04-04 09:46:47 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '605887253092105301' THEN a.old_resultuid ELSE a.resultuid END as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars AS length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternStartPrice, resy1, supporty1, dtt.timezone, cps.pip, newLevels.profit FROM autochartist_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid INNER JOIN patterns p ON p.patternname = a.pattern LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT JOIN LATERAL calc_cp_signal (a.resultuid) newLevels on true WHERE (a.old_resultuid = '605887253092105301' OR a.resultuid = '605887253092105301') AND dtt.dayofweek = 3;
Date: 2025-04-04 09:24:55 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
13 1,465 68ms 0ms 1ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Apr 04 09 1,465 68ms 0ms [ User: postgres - Total duration: 68ms - Times executed: 1465 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 68ms - Times executed: 1465 ]
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select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = '604104683407304307' and category = lower('hourofday') order by correct desc) as summdata group by category, name having sum(total) > 0 order by name;
Date: 2025-04-04 09:01:55 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = '515852059310228307' and category = lower('hourofday') order by correct desc) as summdata group by category, name having sum(total) > 0 order by name;
Date: 2025-04-04 09:01:01 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = '604544041467024307' and category = lower('direction') order by correct desc) as summdata group by category, name having sum(total) > 0 order by name;
Date: 2025-04-04 09:02:04 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
14 1,268 11ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Apr 04 09 1,268 11ms 0ms [ User: postgres - Total duration: 11ms - Times executed: 1268 ]
[ Application: [unknown] - Total duration: 11ms - Times executed: 1268 ]
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SET extra_float_digits = 3;
Date: 2025-04-04 09:45:53 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: [unknown] Bind query: yes
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SET extra_float_digits = 3;
Date: 2025-04-04 09:46:13 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: [unknown] Bind query: yes
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SET extra_float_digits = 3;
Date: 2025-04-04 09:45:53 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: [unknown] Bind query: yes
15 1,226 13ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Apr 04 09 1,226 13ms 0ms [ User: postgres - Total duration: 13ms - Times executed: 1226 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 13ms - Times executed: 1226 ]
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-04-04 09:34:13 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-04-04 09:00:07 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-04-04 09:00:07 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
16 1,192 1s60ms 0ms 15ms 0ms with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ) select a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, s.exchange, s.symbol, s.longname, s.shortname, breakout, dtt.timezone, patternstartprice, patternendprice, qtytp, newlevels.profit, newlevels.stop, newlevels.filtered, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern inner join rar_max rm on ? = ? left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid left join lateral calc_cp_signal (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Apr 04 09 1,192 1s60ms 0ms [ User: postgres - Total duration: 1s60ms - Times executed: 1192 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s47ms - Times executed: 1177 ]
[ Application: [unknown] - Total duration: 12ms - Times executed: 15 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ) SELECT a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, CASE WHEN a.old_resultuid = '605887194635833301' THEN a.old_resultuid ELSE a.resultuid END AS uid, breakout, initialtrend, volumeincrease, symmetry AS uniformity, predictionpricefrom, predictionpriceto, noise, s.exchange, s.symbol, s.longname, s.shortname, breakout, dtt.timezone, patternStartPrice, patternEndPrice, qtytp, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM autochartist_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid INNER JOIN patterns p ON p.patternname = a.pattern INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid LEFT JOIN LATERAL calc_cp_signal (a.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol WHERE (a.old_resultuid = '605887194635833301' OR a.resultuid = '605887194635833301') AND dtt.dayofweek = 3;
Date: 2025-04-04 09:31:03 Duration: 15ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ) SELECT a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, CASE WHEN a.old_resultuid = '605886013879680301' THEN a.old_resultuid ELSE a.resultuid END AS uid, breakout, initialtrend, volumeincrease, symmetry AS uniformity, predictionpricefrom, predictionpriceto, noise, s.exchange, s.symbol, s.longname, s.shortname, breakout, dtt.timezone, patternStartPrice, patternEndPrice, qtytp, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM autochartist_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid INNER JOIN patterns p ON p.patternname = a.pattern INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid LEFT JOIN LATERAL calc_cp_signal (a.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol WHERE (a.old_resultuid = '605886013879680301' OR a.resultuid = '605886013879680301') AND dtt.dayofweek = 3;
Date: 2025-04-04 09:36:00 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ) SELECT a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, CASE WHEN a.old_resultuid = '605887252382098301' THEN a.old_resultuid ELSE a.resultuid END AS uid, breakout, initialtrend, volumeincrease, symmetry AS uniformity, predictionpricefrom, predictionpriceto, noise, s.exchange, s.symbol, s.longname, s.shortname, breakout, dtt.timezone, patternStartPrice, patternEndPrice, qtytp, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM autochartist_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid INNER JOIN patterns p ON p.patternname = a.pattern INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid LEFT JOIN LATERAL calc_cp_signal (a.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol WHERE (a.old_resultuid = '605887252382098301' OR a.resultuid = '605887252382098301') AND dtt.dayofweek = 3;
Date: 2025-04-04 09:40:45 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
17 820 69ms 0ms 0ms 0ms select patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzos, dtt.timezone as tz from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Apr 04 09 820 69ms 0ms [ User: postgres - Total duration: 69ms - Times executed: 820 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 69ms - Times executed: 820 ]
-
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = '605887193991788301';
Date: 2025-04-04 09:47:33 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
-
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = '605887197515560301';
Date: 2025-04-04 09:34:16 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = '605887193542621301';
Date: 2025-04-04 09:55:35 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
18 760 3s614ms 3ms 13ms 4ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, timegranularity as interval, patternendtime, ? as direction, a.fromprice, dtt.timezone, a.patternmovement, a.patternlengthbars, cps.pip from bigmovement_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Apr 04 09 760 3s614ms 4ms [ User: postgres - Total duration: 3s614ms - Times executed: 760 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s614ms - Times executed: 760 ]
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SELECT CASE WHEN a.old_resultuid = '605887195447050306' THEN a.old_resultuid ELSE a.resultuid END AS resultuid, s.symbol, timegranularity as interval, patternendtime, 0 as direction, a.fromprice, dtt.timezone, a.patternmovement, a.patternlengthbars, cps.pip FROM bigmovement_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid LEFT JOIN currencypips cps on cps.symbol = s.symbol WHERE (a.old_resultuid = '605887195447050306' OR a.resultuid = '605887195447050306') AND dtt.dayofweek = 3;
Date: 2025-04-04 09:31:02 Duration: 13ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '605887197272418306' THEN a.old_resultuid ELSE a.resultuid END AS resultuid, s.symbol, timegranularity as interval, patternendtime, 0 as direction, a.fromprice, dtt.timezone, a.patternmovement, a.patternlengthbars, cps.pip FROM bigmovement_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid LEFT JOIN currencypips cps on cps.symbol = s.symbol WHERE (a.old_resultuid = '605887197272418306' OR a.resultuid = '605887197272418306') AND dtt.dayofweek = 3;
Date: 2025-04-04 09:31:03 Duration: 10ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '605886961372136306' THEN a.old_resultuid ELSE a.resultuid END AS resultuid, s.symbol, timegranularity as interval, patternendtime, 0 as direction, a.fromprice, dtt.timezone, a.patternmovement, a.patternlengthbars, cps.pip FROM bigmovement_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid LEFT JOIN currencypips cps on cps.symbol = s.symbol WHERE (a.old_resultuid = '605886961372136306' OR a.resultuid = '605886961372136306') AND dtt.dayofweek = 3;
Date: 2025-04-04 09:11:01 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
19 748 1s291ms 0ms 13ms 1ms select s.symbolid, dss.downloadfrequency, dss.downloadersymbol from downloadersymbolsettings dss inner join symbols s on dss.symbolid = s.symbolid where dss.classname = ? and s.deleted = ? and dss.enabled = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Apr 04 09 748 1s291ms 1ms [ User: postgres - Total duration: 1s291ms - Times executed: 748 ]
[ Application: [unknown] - Total duration: 1s291ms - Times executed: 748 ]
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'ICMARKETS-AU-MT5' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-04-04 09:45:04 Duration: 13ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'ICMARKETS-AU-MT5' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-04-04 09:30:07 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'ATFX' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-04-04 09:30:09 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
20 748 129ms 0ms 0ms 0ms select downloadersymbol, spike_threshold from price_datafeed_spike_threshold where classname = ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Apr 04 09 748 129ms 0ms [ User: postgres - Total duration: 129ms - Times executed: 748 ]
[ Application: [unknown] - Total duration: 129ms - Times executed: 748 ]
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SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'MILLENNIUMPF';
Date: 2025-04-04 09:15:37 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'PEPPERSTONE';
Date: 2025-04-04 09:15:36 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'PEPPERSTONE';
Date: 2025-04-04 09:45:40 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 13s720ms 14s826ms 14s166ms 4 56s667ms select updateageforrelevantresults ();Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Apr 04 09 4 56s667ms 14s166ms [ User: postgres - Total duration: 56s667ms - Times executed: 4 ]
[ Application: psql - Total duration: 56s667ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-04-04 09:32:17 Duration: 14s826ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-04-04 09:47:17 Duration: 14s227ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-04-04 09:02:16 Duration: 13s893ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
2 397ms 27s401ms 10s589ms 252 44m28s with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ), ar as ( select a.*, rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end ), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on sg.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Apr 04 09 252 44m28s 10s589ms [ User: postgres - Total duration: 44m28s - Times executed: 252 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 40m24s - Times executed: 240 ]
[ Application: [unknown] - Total duration: 4m4s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:10:57 Duration: 27s401ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:05:57 Duration: 27s67ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:15:56 Duration: 26s383ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
3 171ms 29s138ms 7s830ms 252 32m53s with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Apr 04 09 252 32m53s 7s830ms [ User: postgres - Total duration: 32m53s - Times executed: 252 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 30m18s - Times executed: 240 ]
[ Application: [unknown] - Total duration: 2m35s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-04-04 09:00:46 Duration: 29s138ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.patternlengthbars <= '400') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-04-04 09:11:27 Duration: 19s96ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.patternlengthbars <= '400') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-04-04 09:46:13 Duration: 18s440ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
4 4s465ms 8s535ms 5s765ms 6 34s590ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Apr 04 09 6 34s590ms 5s765ms [ User: postgres - Total duration: 34s590ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 34s590ms - Times executed: 6 ]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-04-04 09:00:11 Duration: 8s535ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-04-04 09:30:10 Duration: 7s922ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-04-04 09:10:07 Duration: 4s614ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
5 592ms 8s567ms 2s900ms 249 12m2s with rar_max as ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ? ), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end ), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp))) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Apr 04 09 249 12m2s 2s900ms [ User: postgres - Total duration: 12m2s - Times executed: 249 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 11m - Times executed: 237 ]
[ Application: [unknown] - Total duration: 1m1s - Times executed: 12 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:11:07 Duration: 8s567ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:11:21 Duration: 8s181ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:21:52 Duration: 6s466ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
6 1s599ms 2s659ms 1s839ms 16 29s430ms with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Apr 04 09 16 29s430ms 1s839ms [ User: postgres - Total duration: 29s430ms - Times executed: 16 ]
[ Application: psql - Total duration: 29s430ms - Times executed: 16 ]
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:46:15 Duration: 2s659ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:11:16 Duration: 2s642ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:31:15 Duration: 2s271ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
7 1s184ms 1s453ms 1s286ms 6 7s720ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Apr 04 09 6 7s720ms 1s286ms [ User: postgres - Total duration: 7s720ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 7s720ms - Times executed: 6 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-04-04 09:46:17 Duration: 1s453ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-04-04 09:01:15 Duration: 1s445ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-04-04 09:31:17 Duration: 1s243ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
8 1s251ms 1s328ms 1s275ms 16 20s414ms with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = ? left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bg.brokerid and bim.type = ? where bg.brokerid = ? and basegroupname = ? and g.designation = ? and s.nonliquid = ? ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= ? and patternquality >= ?.? and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, case when direction > ? then ? else ? end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (...) and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= ? and _tmp.qtycandlesapart <= ? and ((cpresultuid > ( select coalesce(max(cpresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?)) or (klresultuid > ( select coalesce(max(klresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = ? and cs.basegroupname = ? and date_trunc(?, cs.gmttimefound) = date_trunc(?, now()) and sent is true and filtered is false ) <= ( select case when coalesce(daily_max, ?) < ? then ? else coalesce(daily_max,?) end from corr_sigs_config_v where broker_id = ? ) and extract(epoch from age(current_timestamp at time zone ?, max_patternendtime - absolutetimezoneoffset * interval ?))/? < mint*? ), maxstats as ( select max(statsid) as maxid , st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = ? then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * ? as numeric), ?) as percent, round(cast((kl_correct) / (kl_total) * ? as numeric), ?) as klpercent, round(cast((cp_correct ) / (cp_total ) * ? as numeric), ?) as cppercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), ?) as openprice, round(cast(sig.forecastprice as numeric), ?) as forecastprice, cast(round(cast(abs(sig.forecastprice - sig.openprice)/pip as numeric), ?)as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname , si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = ? then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = ? and date_part(?, sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = ? and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = ? and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = ? and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = ? and date_part(?, sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = ? and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = ? and kl_sym.name ilike si.symbol ) as tmp order by tmp.gmttimefound desc;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Apr 04 09 16 20s414ms 1s275ms [ User: postgres - Total duration: 20s414ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 20s414ms - Times executed: 16 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '617' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '617' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '617') and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-04-04 09:36:52 Duration: 1s328ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '627' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '627' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '627') and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-04-04 09:07:05 Duration: 1s298ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '617' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '617' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '617') and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-04-04 09:51:46 Duration: 1s297ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
9 12ms 11s860ms 916ms 34 31s160ms select fixcandlegaps (?, false);Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Apr 04 09 34 31s160ms 916ms [ User: postgres - Total duration: 31s160ms - Times executed: 34 ]
[ Application: psql - Total duration: 31s160ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-04-04 09:06:32 Duration: 11s860ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-04-04 09:06:09 Duration: 3s848ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('AXIORY', false);
Date: 2025-04-04 09:06:12 Duration: 2s866ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
10 40ms 10s300ms 898ms 13 11s680ms copy ( select array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ?) as broker_ids, string_to_array(coalesce(replace(broker_symbol_mappings, ?, ?), ?), ?) as broker_symbol_mappings, replace(exchange, ?, ?) as exchange, symbol_id, replace(symbol, ?, ?) as symbol, replace(short_name, ?, ?) as short_name, replace(long_name, ?, ?) as long_name, interval, replace(timezone, ?, ?) as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ?) as search_groups, string_to_array(pattern_basegroupnames, ?) as base_groups, simulation from solr_fetch_results_bm_and_cc (?::character varying, current_timestamp::timestamp without time zone)) t) to ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Apr 04 09 13 11s680ms 898ms [ User: postgres - Total duration: 11s680ms - Times executed: 13 ]
[ Application: psql - Total duration: 11s680ms - Times executed: 13 ]
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-04-04 09:03:12 Duration: 10s300ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-04-04 09:01:02 Duration: 343ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-04-04 09:11:03 Duration: 285ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
11 602ms 1s535ms 832ms 16 13s313ms update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Apr 04 09 16 13s313ms 832ms [ User: postgres - Total duration: 13s313ms - Times executed: 16 ]
[ Application: psql - Total duration: 13s313ms - Times executed: 16 ]
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:11:13 Duration: 1s535ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:46:12 Duration: 1s62ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-04-04 09:31:12 Duration: 1s36ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
12 34ms 1s798ms 604ms 162 1m37s with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Apr 04 09 162 1m37s 604ms [ User: postgres - Total duration: 1m37s - Times executed: 162 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m25s - Times executed: 150 ]
[ Application: [unknown] - Total duration: 12s832ms - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:46:15 Duration: 1s798ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:31:09 Duration: 1s477ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-04-04 09:11:26 Duration: 1s429ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
13 90ms 881ms 383ms 112 43s6ms with last_candle as ( select acs.symbolid as symbolid, acs.latestpricedatetime as latest_candle_time, bsl.brokerid as broker_id, coalesce(bim.code, s.symbol) as symbol, bim.code as symbol_mapping, s.exchange as exchange, s.timegranularity as timegranularity from autochartist_symbolupdates acs inner join brokersymbollist bsl on acs.symbolid = bsl.symbolid inner join symbols s on acs.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bsl.brokerid = ? and s.deleted = ? and s.nonliquid = ? and acs.latestpricedatetime is not null ) select * from ( select lc.broker_id as brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / ?) + ? as sast_hh, mod(cast(psp.fromtime as int), ?) as sast_mm, current_timestamp as datetime, (powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice as closingprice, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / ?.?) as low_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / ?.?) as high_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / ?.?) as low_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / ?.?) as high_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / ?.?) as low_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / ?.?) as high_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / ?.?) as low_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / ?.?) as high_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / ?.?) as low_1440, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / ?.?) as high_1440, dtt.absolutetimezoneoffset as datafeedtimezoneoffset, dtt.timezone as datafeedtimezonename, (round((cast(? as float) - rank) / ? * ?)) as rank_rounded, ((cast(? as float) - rank) / ? * ?) as rank from last_candle lc inner join downloadersymbolsettings dss on lc.symbolid = dss.symbolid inner join datafeedstimetable dtt on trim(dss.classname) = trim(dtt.classname) and dtt.dayofweek = ? -- assuming timezone is same for whole week. inner join powerstats_symboldata psd on psd.symbolid = lc.symbolid left outer join powerstats_trumpet psp on psd.trumpetsymbolid = psp.symbolid and psp.dayofweek = extract(dow from lc.latest_candle_time) and psp.fromtime = cast(extract(? from lc.latest_candle_time) as integer) * ? + extract(? from (cast(extract(? from lc.latest_candle_time) as integer) / ?) * ? * interval ?) inner join prfsymboltree prf on psd.symbolid = prf.symbolid and date_trunc(?, prf.enddate) = date_trunc(?, psp.enddate) left join lateral ( select ph.hour, (ave + stddev) as volatility, rank() over (order by (ave + stddev) desc) as rank from powerstats_hourly ph where ph.symbolid = psd.hourlysymbolid and date_trunc(?,ph.enddate) = date_trunc(?, prf.enddate) ) rank_query on true where prf.brokerid = ? and rank_query.hour = floor((psp.fromtime) / ?) and volatility > ? order by rank desc, rank_rounded desc, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Apr 04 09 112 43s6ms 383ms [ User: postgres - Total duration: 43s6ms - Times executed: 112 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 43s6ms - Times executed: 112 ]
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-04-04 09:56:00 Duration: 881ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '538' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '538' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-04-04 09:00:07 Duration: 850ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-04-04 09:32:00 Duration: 821ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
14 32ms 813ms 204ms 162 33s143ms with rar_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ), all_results as ( select bmr.resultuid as resultuid, ? as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, bmr.patternendtime as identified, bmr.patternlengthbars, dtt.timezone as timezone, g.basegroupname, case when rbr.age is not null then rbr.age when bmr.resultuid <= rm.resultuid then ? else ? end as age, case when rbr.relevant is not null then rbr.relevant when bmr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from bigmovement_results bmr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = bmr.symbolid inner join symbols s on bmr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on bmr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on bmr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bmr.gmttimefound > now() - interval ? and s.deleted = ? and (bmr.simulation = ? or bmr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or bmr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, interval desc;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Apr 04 09 162 33s143ms 204ms [ User: postgres - Total duration: 33s143ms - Times executed: 162 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 27s21ms - Times executed: 150 ]
[ Application: [unknown] - Total duration: 6s122ms - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_bigmovement_results rbr ON rbr.resultuid = bmr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR bmr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, interval DESC;
Date: 2025-04-04 09:31:10 Duration: 813ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_bigmovement_results rbr ON rbr.resultuid = bmr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR bmr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, interval DESC;
Date: 2025-04-04 09:46:17 Duration: 793ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_bigmovement_results rbr ON rbr.resultuid = bmr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR bmr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, interval DESC;
Date: 2025-04-04 09:01:12 Duration: 737ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
15 16ms 282ms 64ms 177 11s499ms select distinct a.symbolid, p.resultuid, case when a.breakout >= ? then ? else ? end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient from relevance_autochartist_results p inner join autochartist_results a on p.resultuid = a.resultuid inner join autochartist_stocklist asl on a.symbolid = asl.symbolid where asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Apr 04 09 177 11s499ms 64ms [ User: postgres - Total duration: 11s499ms - Times executed: 177 ]
[ Application: [unknown] - Total duration: 11s499ms - Times executed: 177 ]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2025-04-04 09:02:49 Duration: 282ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'PEPPERSTONE - 1';
Date: 2025-04-04 09:15:40 Duration: 260ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'PEPPERSTONE - 1';
Date: 2025-04-04 09:15:45 Duration: 249ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
16 0ms 280ms 54ms 408 22s347ms select distinct a.resultuid as ruid, c.symbolid as sid, c.symbol as sym, c.longname as longname, c.shortname, c.exchange as e, c.timegranularity as tg, p.patternid as pid, a.direction as d, cast(atbaridentified as timestamp) as pet, cast(patternstarttime as timestamp) as pst, patternprice as patp, breakoutprice as pe, breakoutbars as be, errormargin as erm, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, cast(x0 as timestamp) as x0, cast(x1 as timestamp) as x1, cast(x2 as timestamp) as x2, cast(( case when x3 = ? then ? else x3 end) as timestamp) as x3, cast(( case when x4 = ? then ? else x4 end) as timestamp) as x4, cast(( case when x5 = ? then ? else x5 end) as timestamp) as x5, cast(( case when x6 = ? then ? else x6 end) as timestamp) as x6, cast(( case when x7 = ? then ? else x7 end) as timestamp) as x7, cast(( case when x8 = ? then ? else x8 end) as timestamp) as x8, cast(( case when x9 = ? then ? else x9 end) as timestamp) as x9, cast(atbaridentified as timestamp) as patternendtime, cast(atbaridentified as timestamp) as atbar, cast(( case when approachingtimestamp = ? then ? else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzos, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as relevant, cast(?.? as double precision) as premium, cast(? as bigint) as instrumentid, ? as derivativeid, ? as underlyingid, ? as isunderlying from symbols c inner join brokersymbollist b on c.symbolid = b.symbolid inner join symbolgroup sg on c.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = c.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join keylevels_results a on a.symbolid = c.symbolid inner join hrspatterns p on a.patternid = p.patternid left outer join relevance_keylevels_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and patternclassid = ? and patternlengthbars >= ? and a.patternid & ? > ? and dftt.dayofweek = ? and a.qtytp >= ? and a.resultuid > ? and c.nonliquid = ? and c.deleted = ? and dss.enabled = ? order by relevant desc, age asc, patternendtime desc, qtp desc limit ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Apr 04 09 408 22s347ms 54ms [ User: postgres - Total duration: 22s347ms - Times executed: 408 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 22s347ms - Times executed: 408 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059718346308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '1574284935' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:46:15 Duration: 280ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059718346308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '0' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:14:12 Duration: 279ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059718346308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '768290927' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:18:13 Duration: 273ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
17 0ms 1s33ms 43ms 156 6s846ms select distinct patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, longname, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as relevant from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join symbolgroup sg on s.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join autochartist_results a on a.symbolid = s.symbolid inner join patterns p on a.pattern = p.patternname left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and breakout >= ?.? and patternendtime = latestbaratbreakouttime and patternlengthbars >= ? and patternquality >= ?.? and initialtrend >= ?.? and symmetry >= ?.? and noise <= ?.? and volumeincrease >= ?.? and temporarypattern = ? and patternid & ? > ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and a.resultuid > ? and s.nonliquid = ? and dftt.dayofweek = ? order by relevant desc, age asc, patternendtime desc, patternquality desc limit ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Apr 04 09 156 6s846ms 43ms [ User: postgres - Total duration: 6s846ms - Times executed: 156 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 6s846ms - Times executed: 156 ]
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 605887074825963301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-04-04 09:18:13 Duration: 1s33ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 605886779931507301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-04-04 09:18:13 Duration: 932ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 605883281612025301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-04-04 09:18:13 Duration: 868ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
18 3ms 13ms 4ms 760 3s614ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, timegranularity as interval, patternendtime, ? as direction, a.fromprice, dtt.timezone, a.patternmovement, a.patternlengthbars, cps.pip from bigmovement_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Apr 04 09 760 3s614ms 4ms [ User: postgres - Total duration: 3s614ms - Times executed: 760 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s614ms - Times executed: 760 ]
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SELECT CASE WHEN a.old_resultuid = '605887195447050306' THEN a.old_resultuid ELSE a.resultuid END AS resultuid, s.symbol, timegranularity as interval, patternendtime, 0 as direction, a.fromprice, dtt.timezone, a.patternmovement, a.patternlengthbars, cps.pip FROM bigmovement_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid LEFT JOIN currencypips cps on cps.symbol = s.symbol WHERE (a.old_resultuid = '605887195447050306' OR a.resultuid = '605887195447050306') AND dtt.dayofweek = 3;
Date: 2025-04-04 09:31:02 Duration: 13ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '605887197272418306' THEN a.old_resultuid ELSE a.resultuid END AS resultuid, s.symbol, timegranularity as interval, patternendtime, 0 as direction, a.fromprice, dtt.timezone, a.patternmovement, a.patternlengthbars, cps.pip FROM bigmovement_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid LEFT JOIN currencypips cps on cps.symbol = s.symbol WHERE (a.old_resultuid = '605887197272418306' OR a.resultuid = '605887197272418306') AND dtt.dayofweek = 3;
Date: 2025-04-04 09:31:03 Duration: 10ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '605886961372136306' THEN a.old_resultuid ELSE a.resultuid END AS resultuid, s.symbol, timegranularity as interval, patternendtime, 0 as direction, a.fromprice, dtt.timezone, a.patternmovement, a.patternlengthbars, cps.pip FROM bigmovement_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid LEFT JOIN currencypips cps on cps.symbol = s.symbol WHERE (a.old_resultuid = '605886961372136306' OR a.resultuid = '605886961372136306') AND dtt.dayofweek = 3;
Date: 2025-04-04 09:11:01 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
19 0ms 41ms 3ms 29,091 1m42s select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Apr 04 09 29,091 1m42s 3ms [ User: postgres - Total duration: 1m42s - Times executed: 29091 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m42s - Times executed: 29091 ]
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'MCD.US' OR dss.downloadersymbol = 'MCD.US') AND dss.enabled = 1;
Date: 2025-04-04 09:30:05 Duration: 41ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'AUDCAD' OR dss.downloadersymbol = 'AUDCAD') AND dss.enabled = 1;
Date: 2025-04-04 09:30:07 Duration: 39ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'EURNOK' OR dss.downloadersymbol = 'EURNOK') AND dss.enabled = 1;
Date: 2025-04-04 09:30:04 Duration: 33ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
20 0ms 11ms 1ms 2,288 4s133ms insert into keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errormargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestprice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) values (?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?, ?, ?.?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?.?, ?::timestamp without time zone, ?, ?.?, ?.?, ?, ?, ?.?, ?.?, ?::timestamp without time zone, ?, ?, ?.?, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Apr 04 09 2,288 4s133ms 1ms [ User: postgres - Total duration: 4s133ms - Times executed: 2288 ]
[ Application: [unknown] - Total duration: 4s133ms - Times executed: 2288 ]
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INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, - 1, 1, '2025-04-04 06:57:47'::timestamp without time zone, '2025-04-04 09:00:00', 0.098950000000000065680000000000, 4, 60, 10.475550000000000139000000000000, '2025-04-03 01:00:00', '2025-04-02 10:00:00', '2025-04-02 04:00:00', '2025-04-01 21:00:00', '', '', '', '', '', '', 70, 10.480360499999999746000000000000, '2025-04-04 09:00:00'::timestamp without time zone, '2025-04-04 09:00:00', 10.394949999999999690000000000000, 0.005989999999999979716000000000, 1, 515840247987373300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840247987373300|10.47555|1|2025-04-04 09:00:00|2025-04-04 09:00:00|1|-1', 10.338998999999999384000000000000, 0.136551000000000755100000000000, 2, '2025-04-01 21:00:00', 10.301809999999999690000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-04-04 09:01:39 Duration: 11ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, - 1, 2, '2025-04-04 06:57:38'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 68, 401.637999999999976800000000000000, '2025-04-04 02:00:00', '2025-04-01 12:00:00', '2025-04-01 06:00:00', '', '', '', '', '', '', '', 136, 401.399249999999995000000000000000, '2025-04-04 09:00:00'::timestamp without time zone, '2025-04-04 09:00:00', 0.000000000000000000000000000000, 0.238750000000001710800000000000, 1, 515840245887452300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840245887452300|401.638|2|2025-04-04 09:00:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-04-01 06:00:00', 398.307000000000016400000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-04-04 09:01:30 Duration: 10ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (9.000000000000000000000000000000, - 1, 2, '2025-04-04 06:57:27'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 82, 37.879579999999997140000000000000, '2025-04-04 00:30:00', '2025-04-03 13:30:00', '2025-04-02 07:30:00', '', '', '', '', '', '', '', 164, 37.857925999999999080000000000000, '2025-04-04 02:30:00'::timestamp without time zone, '2025-04-04 02:30:00', 0.000000000000000000000000000000, 0.021653999999999840040000000000, 1, 515840249509618300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249509618300|37.87958|2|2025-04-04 02:30:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-04-02 07:30:00', 37.419260000000001300000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-04-04 09:01:19 Duration: 10ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 2s28ms 2,136 0ms 6ms 0ms WITH rar_max as ( ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Apr 04 09 2,136 2s28ms 0ms [ User: postgres - Total duration: 1h20m32s - Times executed: 2136 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h19m8s - Times executed: 2104 ]
[ Application: [unknown] - Total duration: 1m24s - Times executed: 32 ]
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WITH rar_max as ( ;
Date: 2025-04-04 09:46:15 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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WITH rar_max as ( ;
Date: 2025-04-04 09:31:03 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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WITH rar_max as ( ;
Date: 2025-04-04 09:31:03 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
2 1s891ms 5,575 0ms 20ms 0ms SELECT ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 09 5,575 1s891ms 0ms [ User: postgres - Total duration: 11s631ms - Times executed: 5575 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 11s409ms - Times executed: 4738 ]
[ Application: [unknown] - Total duration: 222ms - Times executed: 837 ]
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SELECT ;
Date: 2025-04-04 09:30:04 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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SELECT ;
Date: 2025-04-04 09:00:07 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
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SELECT ;
Date: 2025-04-04 09:00:06 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
3 1s34ms 748 0ms 6ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 09 748 1s34ms 1ms [ User: postgres - Total duration: 1s291ms - Times executed: 748 ]
[ Application: [unknown] - Total duration: 1s291ms - Times executed: 748 ]
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-04-04 09:31:01 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-04-04 09:15:04 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-04-04 09:45:58 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
4 521ms 1,839 0ms 2ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 09 1,839 521ms 0ms [ User: postgres - Total duration: 4s741ms - Times executed: 1839 ]
[ Application: [unknown] - Total duration: 4s741ms - Times executed: 1839 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-04-04 09:01:02 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-04-04 09:15:45 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-04-04 09:01:25 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
5 315ms 3,463 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 09 3,463 315ms 0ms [ User: postgres - Total duration: 1s802ms - Times executed: 3463 ]
[ Application: [unknown] - Total duration: 1s802ms - Times executed: 3463 ]
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-04-04 09:00:42 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-04-04 09:41:49 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-04-04 09:11:29 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
6 220ms 2,097 0ms 0ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #6
Day Hour Count Duration Avg duration 09 2,097 220ms 0ms [ User: postgres - Total duration: 971ms - Times executed: 2097 ]
[ Application: [unknown] - Total duration: 971ms - Times executed: 2097 ]
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-04-04 09:10:34 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-04-04 09:01:33 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-04-04 09:01:35 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
7 209ms 3,115 0ms 6ms 0ms select 1;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 09 3,115 209ms 0ms [ User: postgres - Total duration: 17ms - Times executed: 3115 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 17ms - Times executed: 3084 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 31 ]
-
select 1;
Date: 2025-04-04 09:24:43 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
select 1;
Date: 2025-04-04 09:54:14 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
-
select 1;
Date: 2025-04-04 09:22:13 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
8 180ms 1,268 0ms 3ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #8
Day Hour Count Duration Avg duration 09 1,268 180ms 0ms [ User: postgres - Total duration: 11ms - Times executed: 1268 ]
[ Application: [unknown] - Total duration: 11ms - Times executed: 1268 ]
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SET extra_float_digits = 3;
Date: 2025-04-04 09:45:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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SET extra_float_digits = 3;
Date: 2025-04-04 09:26:12 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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SET extra_float_digits = 3;
Date: 2025-04-04 09:00:05 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
9 90ms 16 4ms 7ms 5ms with sym_info as ( ;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 09 16 90ms 5ms [ User: postgres - Total duration: 20s414ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 20s414ms - Times executed: 16 ]
-
with sym_info as ( ;
Date: 2025-04-04 09:21:48 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
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with sym_info as ( ;
Date: 2025-04-04 09:07:04 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
-
with sym_info as ( ;
Date: 2025-04-04 09:22:01 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
10 87ms 34 0ms 16ms 2ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 09 34 87ms 2ms [ User: postgres - Total duration: 855ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 855ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:46:13 Duration: 16ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:22:12 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:50:13 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
11 83ms 73 0ms 4ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 09 73 83ms 1ms [ User: postgres - Total duration: 30s589ms - Times executed: 73 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 30s589ms - Times executed: 73 ]
-
WITH last_candle AS ( ;
Date: 2025-04-04 09:24:00 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
WITH last_candle AS ( ;
Date: 2025-04-04 09:00:43 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
WITH last_candle AS ( ;
Date: 2025-04-04 09:15:03 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
12 78ms 34 0ms 19ms 2ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 09 34 78ms 2ms [ User: postgres - Total duration: 1s801ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s801ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:42:13 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:18:12 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:22:12 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
13 68ms 34 0ms 18ms 2ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 09 34 68ms 2ms [ User: postgres - Total duration: 1s79ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s79ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:42:13 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:22:13 Duration: 11ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:58:14 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
14 60ms 34 0ms 16ms 1ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 09 34 60ms 1ms [ User: postgres - Total duration: 300ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 300ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:50:13 Duration: 16ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:22:12 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:26:12 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
15 53ms 360 0ms 0ms 0ms select category, ;Times Reported Time consuming prepare #15
Day Hour Count Duration Avg duration 09 360 53ms 0ms [ User: postgres - Total duration: 47ms - Times executed: 360 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 47ms - Times executed: 360 ]
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select category, ;
Date: 2025-04-04 09:00:49 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
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select category, ;
Date: 2025-04-04 09:33:05 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.54
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select category, ;
Date: 2025-04-04 09:10:50 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
16 48ms 31 0ms 4ms 1ms with wh_patitioned as ( ;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 09 31 48ms 1ms [ User: postgres - Total duration: 706ms - Times executed: 31 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 706ms - Times executed: 31 ]
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with wh_patitioned as ( ;
Date: 2025-04-04 09:00:56 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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with wh_patitioned as ( ;
Date: 2025-04-04 09:11:07 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
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with wh_patitioned as ( ;
Date: 2025-04-04 09:18:22 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
17 48ms 18 2ms 3ms 2ms select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 09 18 48ms 2ms [ User: postgres - Total duration: 33ms - Times executed: 18 ]
[ Application: [unknown] - Total duration: 33ms - Times executed: 18 ]
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select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-04-04 09:31:00 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-04-04 09:31:00 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
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select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-04-04 09:11:01 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
18 45ms 34 0ms 3ms 1ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 09 34 45ms 1ms [ User: postgres - Total duration: 2s324ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s324ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:46:14 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:38:13 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:42:14 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
19 45ms 11 0ms 13ms 4ms /*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice > - 1 AND a.resultuid > 605886604032945302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 09 11 45ms 4ms [ User: postgres - Total duration: 107ms - Times executed: 11 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 107ms - Times executed: 11 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice > - 1 AND a.resultuid > 605886604032945302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2025-04-04 09:26:12 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice > - 1 AND a.resultuid > 605886604032945302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2025-04-04 09:38:13 Duration: 9ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice > - 1 AND a.resultuid > 605886604032945302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2025-04-04 09:18:12 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
20 43ms 34 0ms 7ms 1ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 09 34 43ms 1ms [ User: postgres - Total duration: 516ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 516ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:54:13 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:26:12 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:58:14 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 32s907ms 67,950 0ms 22ms 0ms SELECT ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Apr 04 09 67,950 32s907ms 0ms [ User: postgres - Total duration: 2m37s - Times executed: 67950 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m37s - Times executed: 67111 ]
[ Application: [unknown] - Total duration: 222ms - Times executed: 839 ]
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SELECT ;
Date: 2025-04-04 09:15:04 Duration: 22ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '529', $2 = '0', $3 = '0', $4 = 'XAUCHF', $5 = 'XAUCHF'
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SELECT ;
Date: 2025-04-04 09:00:04 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '515840233386190300'
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SELECT ;
Date: 2025-04-04 09:30:05 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '0', $3 = '0', $4 = 'META.US', $5 = 'META.US'
2 22s617ms 3,270 0ms 35ms 6ms WITH rar_max as ( ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 09 3,270 22s617ms 6ms [ User: postgres - Total duration: 1h31m12s - Times executed: 3270 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h23m12s - Times executed: 3188 ]
[ Application: [unknown] - Total duration: 8m - Times executed: 82 ]
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WITH rar_max as ( ;
Date: 2025-04-04 09:01:26 Duration: 35ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = 't', $2 = '529', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '31', $14 = 'AUDCAD', $15 = 'AUDCHF', $16 = 'AUDJPY', $17 = 'AUDNZD', $18 = 'AUDUSD', $19 = 'CADJPY', $20 = 'CHFJPY', $21 = 'EURAUD', $22 = 'EURCAD', $23 = 'EURCHF', $24 = 'EURGBP', $25 = 'EURJPY', $26 = 'EURNZD', $27 = 'EURUSD', $28 = 'GBPAUD', $29 = 'GBPCAD', $30 = 'GBPCHF', $31 = 'GBPJPY', $32 = 'GBPNZD', $33 = 'GBPUSD', $34 = 'JPN225', $35 = 'NAS100', $36 = 'NZDCAD', $37 = 'NZDCHF', $38 = 'NZDJPY', $39 = 'NZDUSD', $40 = 'USDCAD', $41 = 'USDCHF', $42 = 'USDJPY', $43 = 'XAGUSD', $44 = 'XAUUSD', $45 = '0', $46 = '', $47 = '0', $48 = '0', $49 = '0', $50 = '0', $51 = '0', $52 = 't', $53 = '10', $54 = '10'
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WITH rar_max as ( ;
Date: 2025-04-04 09:55:56 Duration: 35ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = 't', $2 = '958', $3 = '3', $4 = '60', $5 = '240', $6 = '1440', $7 = '0', $8 = '', $9 = '50', $10 = 'AUDCAD', $11 = 'AUDJPY', $12 = 'AUDUSD', $13 = 'EURAUD', $14 = 'EURCHF', $15 = 'EURGBP', $16 = 'EURJPY', $17 = 'EURMXN', $18 = 'EURUSD', $19 = 'GBPJPY', $20 = 'GBPUSD', $21 = 'NZDUSD', $22 = 'USDCAD', $23 = 'USDCHF', $24 = 'USDJPY', $25 = 'USDMXN', $26 = 'BTCUSD', $27 = 'ETHUSD', $28 = 'LTCUSD', $29 = 'AAPL.US', $30 = 'AMD.US', $31 = 'AMZN.US', $32 = 'BABA.US', $33 = 'BRK.B.US', $34 = 'GOOG.US', $35 = 'INTC.US', $36 = 'META.US', $37 = 'MSFT.US', $38 = 'NFLX.US', $39 = 'NKE.US', $40 = 'NVDA.US', $41 = 'PYPL.US', $42 = 'TSLA.US', $43 = 'V.US', $44 = 'Cocoa', $45 = 'Coffee', $46 = 'NatGas', $47 = 'SpotBrent', $48 = 'XAGUSD', $49 = 'XAUUSD', $50 = 'AUS200', $51 = 'EUSTX50', $52 = 'FRA40', $53 = 'GER40', $54 = 'HK50', $55 = 'JPN225', $56 = 'NAS100', $57 = 'UK100', $58 = 'US30', $59 = 'US500', $60 = '0', $61 = '', $62 = '0', $63 = '0', $64 = '0', $65 = '400', $66 = '400', $67 = 't', $68 = '10', $69 = '10'
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WITH rar_max as ( ;
Date: 2025-04-04 09:11:08 Duration: 34ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = 't', $2 = '529', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '31', $14 = 'AUDCAD', $15 = 'AUDCHF', $16 = 'AUDJPY', $17 = 'AUDNZD', $18 = 'AUDUSD', $19 = 'CADJPY', $20 = 'CHFJPY', $21 = 'EURAUD', $22 = 'EURCAD', $23 = 'EURCHF', $24 = 'EURGBP', $25 = 'EURJPY', $26 = 'EURNZD', $27 = 'EURUSD', $28 = 'GBPAUD', $29 = 'GBPCAD', $30 = 'GBPCHF', $31 = 'GBPJPY', $32 = 'GBPNZD', $33 = 'GBPUSD', $34 = 'JPN225', $35 = 'NAS100', $36 = 'NZDCAD', $37 = 'NZDCHF', $38 = 'NZDJPY', $39 = 'NZDUSD', $40 = 'USDCAD', $41 = 'USDCHF', $42 = 'USDJPY', $43 = 'XAGUSD', $44 = 'XAUUSD', $45 = '0', $46 = '', $47 = '0', $48 = '0', $49 = '0', $50 = '0', $51 = '0', $52 = 't', $53 = '10', $54 = '10'
3 1s418ms 748 1ms 12ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 09 748 1s418ms 1ms [ User: postgres - Total duration: 1s291ms - Times executed: 748 ]
[ Application: [unknown] - Total duration: 1s291ms - Times executed: 748 ]
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-04-04 09:30:13 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'FPMARKETS'
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-04-04 09:00:27 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'GLOBALGTMT5'
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-04-04 09:15:05 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'MILLENNIUMPF'
4 1s384ms 52 0ms 46ms 26ms with wh_patitioned as ( ;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 09 52 1s384ms 26ms [ User: postgres - Total duration: 1s310ms - Times executed: 52 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s310ms - Times executed: 52 ]
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with wh_patitioned as ( ;
Date: 2025-04-04 09:01:28 Duration: 46ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529', $3 = '529', $4 = '529', $5 = '529', $6 = '529', $7 = '529', $8 = '529', $9 = '529'
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with wh_patitioned as ( ;
Date: 2025-04-04 09:45:52 Duration: 45ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
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with wh_patitioned as ( ;
Date: 2025-04-04 09:47:08 Duration: 43ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529', $3 = '529', $4 = '529', $5 = '529', $6 = '529', $7 = '529', $8 = '529', $9 = '529'
5 993ms 34 10ms 60ms 29ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 09 34 993ms 29ms [ User: postgres - Total duration: 855ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 855ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:22:12 Duration: 60ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-224370089', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:42:13 Duration: 59ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1341196361', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059711596308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:46:13 Duration: 55ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1341196361', $7 = '0'
6 907ms 51,983 0ms 18ms 0ms select 1;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 09 51,983 907ms 0ms [ User: postgres - Total duration: 259ms - Times executed: 51983 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 258ms - Times executed: 51823 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 160 ]
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select 1;
Date: 2025-04-04 09:00:07 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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select 1;
Date: 2025-04-04 09:15:05 Duration: 16ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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select 1;
Date: 2025-04-04 09:00:05 Duration: 14ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
7 819ms 34 10ms 47ms 24ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 09 34 819ms 24ms [ User: postgres - Total duration: 1s801ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s801ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:22:12 Duration: 47ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-2118044961', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:34:13 Duration: 43ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-503007081', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:38:13 Duration: 41ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-503007081', $7 = '0'
8 794ms 34 10ms 78ms 23ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 09 34 794ms 23ms [ User: postgres - Total duration: 300ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 300ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:42:13 Duration: 78ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '3', $4 = '3', $5 = '-1017399033', $6 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:26:12 Duration: 58ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '3', $4 = '3', $5 = '-1017399033', $6 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059710817308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.resultuid > $5 AND c.nonliquid = $6 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:22:12 Duration: 48ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '3', $4 = '3', $5 = '-1017399033', $6 = '0'
9 778ms 34 10ms 55ms 22ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059722409308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 09 34 778ms 22ms [ User: postgres - Total duration: 1s742ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s742ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059722409308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:42:13 Duration: 55ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1809005935', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059722409308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:42:13 Duration: 41ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1373506361', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059722409308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:18:12 Duration: 41ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-2071183369', $7 = '0'
10 775ms 112 4ms 14ms 6ms WITH last_candle AS ( ;Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 09 112 775ms 6ms [ User: postgres - Total duration: 43s6ms - Times executed: 112 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 43s6ms - Times executed: 112 ]
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WITH last_candle AS ( ;
Date: 2025-04-04 09:00:43 Duration: 14ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '529', $2 = '529'
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WITH last_candle AS ( ;
Date: 2025-04-04 09:15:03 Duration: 14ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '958', $2 = '958'
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WITH last_candle AS ( ;
Date: 2025-04-04 09:24:00 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529'
11 748ms 34 10ms 53ms 22ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #11
Day Hour Count Duration Avg duration 09 34 748ms 22ms [ User: postgres - Total duration: 1s79ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s79ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:42:13 Duration: 53ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '129726215', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:46:14 Duration: 52ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1877909223', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059704165308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:42:13 Duration: 42ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1877909223', $7 = '0'
12 735ms 34 10ms 38ms 21ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059759428308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 09 34 735ms 21ms [ User: postgres - Total duration: 768ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 768ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059759428308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:34:13 Duration: 38ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1307654425', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059759428308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:46:13 Duration: 37ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1943817049', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059759428308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:46:13 Duration: 35ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1307654425', $7 = '0'
13 718ms 34 10ms 49ms 21ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 09 34 718ms 21ms [ User: postgres - Total duration: 1s578ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s578ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:46:14 Duration: 49ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1408404927', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:26:13 Duration: 49ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1408404927', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:38:13 Duration: 45ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1408404927', $7 = '0'
14 694ms 34 10ms 51ms 20ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 09 34 694ms 20ms [ User: postgres - Total duration: 516ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 516ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:30:13 Duration: 51ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-293992801', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:50:13 Duration: 46ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-293992801', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059720124308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:42:13 Duration: 44ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-293992801', $7 = '0'
15 693ms 99 0ms 23ms 7ms select distinct s.statsid as statsid, sy.exchange as name;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 09 99 693ms 7ms [ User: postgres - Total duration: 522ms - Times executed: 99 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 522ms - Times executed: 99 ]
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select distinct s.statsid as statsid, sy.exchange as name;
Date: 2025-04-04 09:00:49 Duration: 23ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '489', $2 = '489'
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select distinct s.statsid as statsid, sy.exchange as name;
Date: 2025-04-04 09:10:55 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '538', $2 = '538'
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select distinct s.statsid as statsid, sy.exchange as name;
Date: 2025-04-04 09:10:50 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '489', $2 = '489'
16 654ms 34 10ms 51ms 19ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 09 34 654ms 19ms [ User: postgres - Total duration: 2s324ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s324ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:38:13 Duration: 51ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1474770361', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:46:14 Duration: 40ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1474770361', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:30:13 Duration: 36ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1434580921', $7 = '0'
17 647ms 34 10ms 41ms 19ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059709228308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 09 34 647ms 19ms [ User: postgres - Total duration: 1s877ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s877ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059709228308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:22:12 Duration: 41ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '194989519', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059709228308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:34:13 Duration: 41ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '194989519', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059709228308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:42:13 Duration: 37ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1944952935', $7 = '0'
18 622ms 34 10ms 37ms 18ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059758978308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 09 34 622ms 18ms [ User: postgres - Total duration: 4s432ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 4s432ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059758978308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:22:12 Duration: 37ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '670930375', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059758978308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:26:13 Duration: 36ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '670930375', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059758978308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:22:13 Duration: 30ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-661683921', $7 = '0'
19 614ms 34 10ms 44ms 18ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 09 34 614ms 18ms [ User: postgres - Total duration: 8ms - Times executed: 34 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 8ms - Times executed: 34 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:50:13 Duration: 44ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '0', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:18:12 Duration: 33ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '0', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2025-04-04 09:22:12 Duration: 33ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '0', $7 = '0'
20 607ms 12 27ms 95ms 50ms /*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 09 12 607ms 50ms [ User: postgres - Total duration: 4ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 4ms - Times executed: 12 ]
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-04-04 09:42:13 Duration: 95ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-04-04 09:50:13 Duration: 75ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059725121308 AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-04-04 09:46:13 Duration: 61ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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Events
Log levels
Key values
- 544,256 Log entries
Events distribution
Key values
- 0 PANIC entries
- 1 FATAL entries
- 0 ERROR entries
- 0 WARNING entries
Most Frequent Errors/Events
Key values
- 1 Max number of times the same event was reported
- 1 Total events found
Rank Times reported Error 1 1 FATAL: connection to client lost
Times Reported Most Frequent Error / Event #1
Day Hour Count Apr 04 09 1 - FATAL: connection to client lost
Statement: WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > (select min(resultuid) from relevance_autochartist_results) END ), all_results AS (SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code,s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal(ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4,$5,$6,$7,$8,$9,$10)) AND ($11 = 0 OR s.exchange in ($12)) AND ($13 = 0 OR coalesce(bim.code, s.symbol) in ($14,$15,$16,$17,$18,$19,$20,$21,$22,$23,$24,$25,$26,$27,$28,$29,$30,$31,$32,$33,$34,$35,$36,$37,$38,$39,$40,$41,$42,$43,$44,$45,$46,$47,$48,$49,$50,$51,$52,$53,$54,$55,$56,$57,$58,$59,$60,$61,$62,$63,$64,$65,$66,$67,$68,$69,$70,$71,$72,$73,$74,$75,$76,$77,$78,$79,$80,$81,$82,$83,$84,$85,$86,$87,$88,$89,$90,$91,$92,$93,$94,$95,$96,$97,$98,$99,$100,$101,$102,$103,$104,$105,$106,$107,$108,$109,$110,$111,$112,$113,$114,$115,$116,$117,$118,$119,$120,$121,$122,$123,$124,$125,$126,$127,$128,$129,$130,$131,$132,$133,$134,$135,$136,$137,$138,$139,$140,$141,$142,$143,$144,$145,$146,$147,$148,$149,$150,$151,$152,$153,$154,$155,$156,$157,$158,$159,$160,$161,$162,$163,$164,$165,$166,$167,$168,$169,$170,$171,$172,$173,$174,$175,$176,$177,$178,$179,$180,$181,$182,$183,$184,$185,$186,$187,$188,$189,$190,$191,$192,$193,$194,$195,$196,$197,$198,$199,$200,$201,$202,$203,$204,$205,$206,$207,$208,$209,$210,$211,$212,$213,$214,$215,$216,$217,$218,$219,$220,$221,$222,$223,$224,$225,$226)) AND ($227 = 0 OR ar.pattern in ($228)) AND ($229 = 0 OR ($230 = 1 AND ar.breakout >= 0) OR ($231 = 2 AND ar.breakout < 0)) AND ($232 = 0 OR ar.patternlengthbars <= $233) and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime,'1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $234 OR relevant = 1) AND ($235 = 0 OR age <= $236) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC
Date: 2025-04-04 09:10:22 Database: acaweb_fx Application: PostgreSQL JDBC Driver User: postgres Remote: 192.168.1.250