pgBadger-
Global information
- Generated on Tue Jan 21 11:00:04 2025
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2025-01-21_120000.log
- Parsed 2,136,339 log entries in 1m3s
- Log start from 2025-01-21 12:00:00 to 2025-01-21 13:00:00
-
Overview
Global Stats
- 196 Number of unique normalized queries
- 138,435 Number of queries
- 1h47m59s Total query duration
- 2025-01-21 12:00:00 First query
- 2025-01-21 12:59:59 Last query
- 3,319 queries/s at 2025-01-21 12:30:04 Query peak
- 1h47m59s Total query duration
- 7s194ms Prepare/parse total duration
- 1m27s Bind total duration
- 1h46m24s Execute total duration
- 0 Number of events
- 0 Number of unique normalized events
- 0 Max number of times the same event was reported
- 0 Number of cancellation
- 45 Total number of automatic vacuums
- 59 Total number of automatic analyzes
- 474 Number temporary file
- 142.89 MiB Max size of temporary file
- 6.23 MiB Average size of temporary file
- 3,254 Total number of sessions
- 13 sessions at 2025-01-21 12:56:13 Session peak
- 3d17h13m32s Total duration of sessions
- 1m38s Average duration of sessions
- 42 Average queries per session
- 1s991ms Average queries duration per session
- 1m36s Average idle time per session
- 3,243 Total number of connections
- 27 connections/s at 2025-01-21 12:58:48 Connection peak
- 2 Total number of databases
SQL Traffic
Key values
- 3,319 queries/s Query Peak
- 2025-01-21 12:30:04 Date
SELECT Traffic
Key values
- 3,273 queries/s Query Peak
- 2025-01-21 12:30:04 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 180 queries/s Query Peak
- 2025-01-21 12:12:08 Date
Queries duration
Key values
- 1h47m59s 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) Jan 21 12 138,435 0ms 23s971ms 46ms 2m56s 3m20s 4m22s 13 0 0ms 0ms 0ms 0ms 0ms 0ms Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jan 21 12 105,874 26 2ms 3s387ms 11s990ms 25s612ms 13 0 0 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jan 21 12 24,014 2,072 16 96 1ms 634ms 949ms 1s450ms 13 0 0 0 0 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Jan 21 12 22,251 122,779 5.52 16.31% 13 0 0 0.00 0.00% Day Hour Count Average / Second Jan 21 12 3,243 0.90/s 13 0 0.00/s Day Hour Count Average Duration Average idle time Jan 21 12 3,254 1m38s 1m36s 13 0 0ms 0ms -
Connections
Established Connections
Key values
- 27 connections Connection Peak
- 2025-01-21 12:58:48 Date
Connections per database
Key values
- acaweb_fx Main Database
- 3,243 connections Total
Connections per user
Key values
- postgres Main User
- 3,243 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 1393 connections
- 3,243 Total connections
Host Count 127.0.0.1 111 192.168.0.216 92 192.168.1.145 238 192.168.1.20 239 192.168.1.23 59 192.168.1.250 182 192.168.1.90 53 192.168.2.126 63 192.168.2.182 12 192.168.2.205 12 192.168.2.82 48 192.168.3.199 60 192.168.4.117 1 192.168.4.142 1,393 192.168.4.150 10 192.168.4.238 12 192.168.4.33 65 192.168.4.5 4 192.168.4.98 318 [local] 271 -
Sessions
Simultaneous sessions
Key values
- 13 sessions Session Peak
- 2025-01-21 12:56:13 Date
Histogram of session times
Key values
- 2,606 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 3,254 sessions Total
Sessions per user
Key values
- postgres Main User
- 3,254 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 3,254 sessions Total
Host Count Total Duration Average Duration 105.30.55.76 11 1d15m44s 2h12m20s 127.0.0.1 111 11s899ms 107ms 192.168.0.216 92 41s727ms 453ms 192.168.1.145 238 6h17m 1m35s 192.168.1.20 239 17h17m7s 4m20s 192.168.1.23 59 2h8m7s 2m10s 192.168.1.250 182 18h45m39s 6m11s 192.168.1.90 53 35s235ms 664ms 192.168.2.126 63 7s28ms 111ms 192.168.2.182 12 975ms 81ms 192.168.2.205 12 340ms 28ms 192.168.2.82 48 14s78ms 293ms 192.168.3.199 60 971ms 16ms 192.168.4.117 1 186ms 186ms 192.168.4.142 1,393 16m21s 704ms 192.168.4.150 10 20h9m17s 2h55s 192.168.4.238 12 17s504ms 1s458ms 192.168.4.33 65 17s315ms 266ms 192.168.4.5 4 30ms 7ms 192.168.4.98 318 10s961ms 34ms [local] 271 1m36s 354ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 11,051 buffers Checkpoint Peak
- 2025-01-21 12:15:46 Date
- 209.946 seconds Highest write time
- 0.022 seconds Sync time
Checkpoints Wal files
Key values
- 4 files Wal files usage Peak
- 2025-01-21 12:20:46 Date
Checkpoints distance
Key values
- 112.25 Mo Distance Peak
- 2025-01-21 12:15:46 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Jan 21 12 79,767 2,518.708s 0.065s 2,519.117s 13 0 0s 0s 0s Day Hour Added Removed Recycled Synced files Longest sync Average sync Jan 21 12 0 0 26 2,400 0.005s 0s 13 0 0 0 0 0s 0s Day Hour Count Avg time (sec) Jan 21 12 0 0s 13 0 0s Day Hour Mean distance Mean estimate Jan 21 12 36,548.75 kB 48,840.33 kB 13 0.00 kB 0.00 kB -
Temporary Files
Size of temporary files
Key values
- 135.54 MiB Temp Files size Peak
- 2025-01-21 12:10:07 Date
Number of temporary files
Key values
- 32 per second Temp Files Peak
- 2025-01-21 12:17:07 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Jan 21 12 474 2.88 GiB 6.23 MiB 13 0 0 0 Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 135 514.61 MiB 3.06 MiB 4.57 MiB 3.81 MiB with rar_max as ( ;-
WITH rar_max as ( ;
Date: 2025-01-21 12:00:10 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver
2 38 1.45 GiB 2.78 MiB 142.89 MiB 39.20 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: 2025-01-21 12:00:10 Duration: 7s243ms 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: 2025-01-21 12:30:10 Duration: 7s46ms 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: 2025-01-21 12:40:07 Duration: 4s956ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
3 16 242.73 MiB 15.16 MiB 15.17 MiB 15.17 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: 2025-01-21 12:11:12 Duration: 896ms 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: 2025-01-21 12:31:12 Duration: 891ms 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: 2025-01-21 12:01:13 Duration: 873ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
4 16 501.60 MiB 31.34 MiB 31.35 MiB 31.35 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: 2025-01-21 12:31:15 Duration: 2s372ms 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: 2025-01-21 12:01:15 Duration: 2s320ms 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: 2025-01-21 12:11:15 Duration: 2s176ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
5 4 195.23 MiB 48.74 MiB 48.90 MiB 48.81 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2025-01-21 12:17:10 Duration: 8s274ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-01-21 12:47:10 Duration: 8s78ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-01-21 12:32:09 Duration: 7s908ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
6 1 4.57 MiB 4.57 MiB 4.57 MiB 4.57 MiB 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;-
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 = $1 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 = $2 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 ($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 fr.pattern in ($228)) AND ($229 = 0 OR fr.patternlengthbars <= $230) AND ($231 = 0 OR ($232 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($233 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), 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: 2025-01-21 12:47:00 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver
Queries generating the largest temporary files
Rank Size Query 1 142.89 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: 2025-01-21 12:30:06 ]
2 135.64 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: 2025-01-21 12:10:05 ]
3 115.21 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: 2025-01-21 12:40:05 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
4 93.07 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: 2025-01-21 12:00:06 ]
5 79.95 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: 2025-01-21 12:20:04 ]
6 74.45 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: 2025-01-21 12:50:04 ]
7 67.03 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: 2025-01-21 12:50:04 ]
8 65.36 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: 2025-01-21 12:10:04 ]
9 64.31 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: 2025-01-21 12:20:04 ]
10 51.34 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: 2025-01-21 12:00:06 ]
11 49.64 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: 2025-01-21 12:40:04 ]
12 48.90 MiB select updateageforrelevantresults ();[ Date: 2025-01-21 12:17:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
13 48.83 MiB select updateageforrelevantresults ();[ Date: 2025-01-21 12:47:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
14 48.76 MiB select updateageforrelevantresults ();[ Date: 2025-01-21 12:32:03 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
15 48.74 MiB select updateageforrelevantresults ();[ Date: 2025-01-21 12:02:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
16 45.88 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: 2025-01-21 12:50:04 ]
17 43.81 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: 2025-01-21 12:30:06 ]
18 43.68 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: 2025-01-21 12:50:04 ]
19 41.98 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: 2025-01-21 12:00:07 ]
20 39.58 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: 2025-01-21 12:30:06 ]
-
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)
- 59 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 5 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.public.autochartist_symbolupdates 2 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.pg_catalog.pg_depend 2 acaweb_fx.public.relevance_bigmovement_results 2 acaweb_fx.pg_catalog.pg_index 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.relevance_consecutivecandles_results 1 acaweb_fx.public.symbollatestupdatetime 1 Total 59 Vacuums per table
Key values
- public.solr_relevance_old (19) Main table vacuumed on database acaweb_fx
- 45 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 19 16 15,809 0 57 0 0 9,699 864 4,893,626 acaweb_fx.public.datafeeds_latestrun 4 0 454 0 10 0 0 76 19 66,313 acaweb_fx.public.relevance_keylevels_results 3 3 13,610 0 504 6 234 2,874 2,067 5,230,106 acaweb_fx.public.relevance_autochartist_results 3 3 11,646 0 316 2 686 2,402 1,666 4,556,971 acaweb_fx.pg_toast.pg_toast_2619 2 2 300 0 67 0 0 216 64 246,876 acaweb_fx.pg_catalog.pg_attribute 2 2 1,725 0 339 0 128 763 309 1,773,001 acaweb_fx.public.latest_t15_candle_view 2 2 130 0 8 0 0 12 2 17,157 acaweb_fx.pg_catalog.pg_class 2 2 737 0 101 0 82 241 104 425,779 acaweb_fx.public.relevance_fibonacci_results 2 2 2,699 0 82 2 104 549 350 883,578 acaweb_fx.pg_catalog.pg_type 1 1 132 0 29 0 0 59 20 107,912 acaweb_fx.public.autochartist_symbolupdates 1 1 26,073 0 5,546 4 36,394 8,450 7,106 2,949,371 acaweb_fx.pg_catalog.pg_statistic 1 1 873 0 133 0 674 454 113 541,974 acaweb_fx.public.solr_imports 1 1 43 0 2 0 0 6 2 14,041 acaweb_fx.public.relevance_consecutivecandles_results 1 1 75 0 10 1 0 23 10 38,154 acaweb_fx.public.relevance_bigmovement_results 1 1 186 0 9 0 0 66 31 121,629 Total 45 38 74,492 51,328 7,213 15 38,302 25,890 12,727 21,866,488 Tuples removed per table
Key values
- public.solr_relevance_old (53137) Main table with removed tuples on database acaweb_fx
- 71051 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 19 16 53,137 140,491 21,678 0 4,083 acaweb_fx.public.autochartist_symbolupdates 1 1 5,674 49,103 14 0 40,691 acaweb_fx.public.relevance_autochartist_results 3 3 3,631 25,128 0 0 1,140 acaweb_fx.public.relevance_keylevels_results 3 3 3,223 34,466 0 0 837 acaweb_fx.pg_catalog.pg_attribute 2 2 2,717 18,882 0 0 484 acaweb_fx.pg_catalog.pg_statistic 1 1 724 4,495 0 0 1,194 acaweb_fx.public.relevance_fibonacci_results 2 2 665 2,811 0 0 204 acaweb_fx.pg_catalog.pg_class 2 2 272 3,890 0 0 300 acaweb_fx.public.datafeeds_latestrun 4 0 233 56 0 0 64 acaweb_fx.public.relevance_bigmovement_results 1 1 209 912 0 0 25 acaweb_fx.pg_catalog.pg_type 1 1 202 1,334 0 0 38 acaweb_fx.pg_toast.pg_toast_2619 2 2 139 341 1 3 102 acaweb_fx.public.latest_t15_candle_view 2 2 103 42 14 0 2 acaweb_fx.public.relevance_consecutivecandles_results 1 1 70 218 0 0 7 acaweb_fx.public.solr_imports 1 1 52 1 0 0 2 Total 45 38 71,051 282,170 21,707 3 49,173 Pages removed per table
Key values
- pg_toast.pg_toast_2619 (3) Main table with removed pages on database acaweb_fx
- 3 pages Total removed
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_toast.pg_toast_2619 2 2 139 3 acaweb_fx.pg_catalog.pg_type 1 1 202 0 acaweb_fx.public.autochartist_symbolupdates 1 1 5674 0 acaweb_fx.public.datafeeds_latestrun 4 0 233 0 acaweb_fx.pg_catalog.pg_statistic 1 1 724 0 acaweb_fx.public.solr_imports 1 1 52 0 acaweb_fx.pg_catalog.pg_attribute 2 2 2717 0 acaweb_fx.public.relevance_consecutivecandles_results 1 1 70 0 acaweb_fx.public.relevance_bigmovement_results 1 1 209 0 acaweb_fx.public.latest_t15_candle_view 2 2 103 0 acaweb_fx.public.relevance_keylevels_results 3 3 3223 0 acaweb_fx.public.solr_relevance_old 19 16 53137 0 acaweb_fx.pg_catalog.pg_class 2 2 272 0 acaweb_fx.public.relevance_autochartist_results 3 3 3631 0 acaweb_fx.public.relevance_fibonacci_results 2 2 665 0 Total 45 38 71,051 3 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Jan 21 12 45 59 13 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
- 105,874 Total read queries
- 30,586 Total write queries
Queries by database
Key values
- acaweb_fx Main database
- 138,282 Requests
- 1h46m24s (acaweb_fx)
- Main time consuming database
Queries by user
Key values
- postgres Main user
- 138,435 Requests
User Request type Count Duration postgres Total 138,435 1h46m24s copy from 96 7s237ms copy to 26 10s978ms cte 3,710 1h41m39s ddl 16 507ms delete 16 25ms insert 24,014 20s732ms others 1,975 6s630ms select 105,874 3m45s tcl 636 188ms update 2,072 13s561ms Duration by user
Key values
- 1h46m24s (postgres) Main time consuming user
User Request type Count Duration postgres Total 138,435 1h46m24s copy from 96 7s237ms copy to 26 10s978ms cte 3,710 1h41m39s ddl 16 507ms delete 16 25ms insert 24,014 20s732ms others 1,975 6s630ms select 105,874 3m45s tcl 636 188ms update 2,072 13s561ms Queries by host
Key values
- 192.168.1.145 Main host
- 46,728 Requests
- 35m10s (192.168.1.250)
- Main time consuming host
Host Request type Count Duration 127.0.0.1 Total 12,685 40s995ms copy to 26 10s978ms cte 24 282ms insert 10,619 10s196ms select 475 18s497ms update 1,541 1s40ms 182.165.1.42 Total 160 7m21s cte 60 7m21s select 100 85ms 192.168.0.216 Total 368 291ms others 184 16ms select 176 172ms update 8 102ms 192.168.0.239 Total 619 459ms select 619 459ms 192.168.0.42 Total 1,593 1s107ms insert 341 28ms select 1,252 1s79ms 192.168.1.135 Total 222 724ms cte 8 247ms select 214 477ms 192.168.1.145 Total 46,728 30m8s cte 918 29m2s others 476 5ms select 45,334 1m5s 192.168.1.20 Total 36,342 29m42s cte 929 28m53s others 478 5ms select 34,935 48s913ms 192.168.1.201 Total 2,478 2s119ms select 2,478 2s119ms 192.168.1.23 Total 9,794 29s952ms cte 6 12ms others 118 1ms select 9,670 29s938ms 192.168.1.250 Total 11,114 35m10s cte 1,650 35m2s others 364 3ms select 9,100 7s721ms 192.168.1.90 Total 61 33s93ms cte 6 33s8ms others 8 0ms select 47 84ms 192.168.2.126 Total 81 105ms others 18 0ms select 63 105ms 192.168.2.182 Total 48 225ms others 24 2ms select 12 10ms update 12 212ms 192.168.2.205 Total 138 93ms insert 90 7ms others 24 2ms select 20 18ms update 4 65ms 192.168.2.82 Total 819 1s555ms insert 437 729ms others 96 10ms select 173 108ms update 113 706ms 192.168.3.199 Total 240 204ms others 120 9ms select 108 90ms update 12 104ms 192.168.4.117 Total 3 51ms cte 1 51ms others 2 0ms 192.168.4.142 Total 13,424 10s301ms insert 12,479 9s705ms select 945 595ms 192.168.4.150 Total 22 1s27ms others 21 0ms select 1 1s27ms 192.168.4.238 Total 36 16s633ms cte 12 16s633ms others 24 0ms 192.168.4.33 Total 153 168ms insert 48 65ms select 95 86ms update 10 16ms 192.168.4.5 Total 12 0ms others 8 0ms select 4 0ms 192.168.4.98 Total 960 7s147ms others 6 6s328ms select 6 27ms tcl 636 188ms update 312 602ms [local] Total 335 1m35s copy from 96 7s237ms cte 96 28s627ms ddl 16 507ms delete 16 25ms others 4 243ms select 47 48s119ms update 60 10s710ms Queries by application
Key values
- PostgreSQL JDBC Driver Main application
- 108,218 Requests
- 1h35m54s (PostgreSQL JDBC Driver)
- Main time consuming application
Application Request type Count Duration PostgreSQL JDBC Driver Total 108,218 1h35m54s cte 3,524 1h33m16s insert 341 28ms others 746 10ms select 103,607 2m37s [unknown] Total 29,771 8m43s cte 66 7m54s insert 23,673 20s704ms others 1,225 6s377ms select 2,168 19s733ms tcl 636 188ms update 2,003 2s832ms psql Total 446 1m46s copy from 96 7s237ms copy to 26 10s978ms cte 120 28s910ms ddl 16 507ms delete 16 25ms others 4 243ms select 99 48s269ms update 69 10s729ms Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2025-01-21 12:00:10 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 81,735 0-1ms duration
Slowest individual queries
Rank Duration Query 1 23s971ms 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: 2025-01-21 12:31:17 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
2 21s233ms 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: 2025-01-21 12:55:51 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
3 20s263ms 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 = '627' 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 ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) 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 ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-01-21 12:11:24 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
4 19s729ms 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: 2025-01-21 12:31:11 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
5 18s824ms 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: 2025-01-21 12:11:13 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
6 17s437ms 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 = '627' 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 ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) 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 ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-01-21 12:41:02 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
7 17s215ms 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 ('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 ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-01-21 12:15:19 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
8 16s828ms 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: 2025-01-21 12:40:59 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
9 16s812ms 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: 2025-01-21 12:12:07 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
10 16s339ms 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: 2025-01-21 12:12:07 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
11 16s307ms 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: 2025-01-21 12:12:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
12 15s892ms 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: 2025-01-21 12:46:36 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
13 15s883ms 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: 2025-01-21 12:32:02 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
14 15s839ms 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: 2025-01-21 12:42:16 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
15 15s796ms 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: 2025-01-21 12:57:18 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
16 15s791ms 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: 2025-01-21 12:27:24 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
17 15s769ms 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: 2025-01-21 12:27:24 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
18 15s755ms 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: 2025-01-21 12:57:18 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
19 15s754ms 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: 2025-01-21 12:31:58 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
20 15s725ms 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: 2025-01-21 12:02:14 - 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 42m56s 281 1s702ms 21s233ms 9s168ms 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 Jan 21 12 281 42m56s 9s168ms [ User: postgres - Total duration: 42m56s - Times executed: 281 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 39m51s - Times executed: 269 ]
[ Application: [unknown] - Total duration: 3m4s - 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: 2025-01-21 12:55:51 Duration: 21s233ms 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 = '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 ('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 ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-01-21 12:15:19 Duration: 17s215ms 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_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: 2025-01-21 12:40:59 Duration: 16s828ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
2 42m21s 282 4s370ms 23s971ms 9s10ms 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 Jan 21 12 282 42m21s 9s10ms [ User: postgres - Total duration: 42m21s - Times executed: 282 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 39m20s - Times executed: 270 ]
[ Application: [unknown] - Total duration: 3m - 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 ('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: 2025-01-21 12:31:17 Duration: 23s971ms 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 = '627' 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 ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) 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 ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-01-21 12:11:24 Duration: 20s263ms 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: 2025-01-21 12:31:11 Duration: 19s729ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
3 12m58s 281 555ms 8s803ms 2s770ms 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 Jan 21 12 281 12m58s 2s770ms [ User: postgres - Total duration: 12m58s - Times executed: 281 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 11m52s - Times executed: 269 ]
[ Application: [unknown] - Total duration: 1m5s - 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: 2025-01-21 12:40:54 Duration: 8s803ms 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 = '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: 2025-01-21 12:10:54 Duration: 8s672ms 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 ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR fr.pattern in ('')) AND ('0' = 0 OR fr.patternlengthbars <= '0') 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: 2025-01-21 12:11:04 Duration: 5s466ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
4 1m19s 24,619 0ms 35ms 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 Jan 21 12 24,619 1m19s 3ms [ User: postgres - Total duration: 1m19s - Times executed: 24619 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m19s - Times executed: 24619 ]
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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 = 'GBPJPY' OR dss.downloadersymbol = 'GBPJPY') AND dss.enabled = 1;
Date: 2025-01-21 12:30:06 Duration: 35ms 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 = 'USDHUF' OR dss.downloadersymbol = 'USDHUF') AND dss.enabled = 1;
Date: 2025-01-21 12:15:05 Duration: 32ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 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 = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'USDSGD' OR dss.downloadersymbol = 'USDSGD') AND dss.enabled = 1;
Date: 2025-01-21 12:30:05 Duration: 31ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
5 1m10s 197 75ms 1s37ms 355ms 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 Jan 21 12 197 1m10s 355ms [ User: postgres - Total duration: 1m10s - Times executed: 197 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m1s - Times executed: 185 ]
[ Application: [unknown] - Total duration: 8s72ms - 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: 2025-01-21 12:31:12 Duration: 1s37ms 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: 2025-01-21 12:01:07 Duration: 991ms 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: 2025-01-21 12:11:15 Duration: 860ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
6 39s622ms 28,125 0ms 23ms 1ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, 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 #6
Day Hour Count Duration Avg duration Jan 21 12 28,125 39s622ms 1ms [ User: postgres - Total duration: 39s622ms - Times executed: 28125 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 39s622ms - Times executed: 28125 ]
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, 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 = '515840243235939300';
Date: 2025-01-21 12:00:04 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 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) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, 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 = '515840218041951300';
Date: 2025-01-21 12:00:06 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 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) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, 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 = '515840217490122300';
Date: 2025-01-21 12:30:04 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
7 38s276ms 90 249ms 912ms 425ms 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 #7
Day Hour Count Duration Avg duration Jan 21 12 90 38s276ms 425ms [ User: postgres - Total duration: 38s276ms - Times executed: 90 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 38s276ms - Times executed: 90 ]
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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: 2025-01-21 12:16:00 Duration: 912ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 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: 2025-01-21 12:16:00 Duration: 912ms 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 = '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: 2025-01-21 12:56:00 Duration: 853ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
8 33s8ms 6 4s203ms 7s243ms 5s501ms 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 #8
Day Hour Count Duration Avg duration Jan 21 12 6 33s8ms 5s501ms [ User: postgres - Total duration: 33s8ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 33s8ms - 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: 2025-01-21 12:00:10 Duration: 7s243ms 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: 2025-01-21 12:30:10 Duration: 7s46ms 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: 2025-01-21 12:40:07 Duration: 4s956ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
9 32s103ms 4 7s842ms 8s274ms 8s25ms select updateageforrelevantresults ();Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jan 21 12 4 32s103ms 8s25ms [ User: postgres - Total duration: 32s103ms - Times executed: 4 ]
[ Application: psql - Total duration: 32s103ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-01-21 12:17:10 Duration: 8s274ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-01-21 12:47:10 Duration: 8s78ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-01-21 12:32:09 Duration: 7s908ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
10 26s313ms 16 1s411ms 2s372ms 1s644ms 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 #10
Day Hour Count Duration Avg duration Jan 21 12 16 26s313ms 1s644ms [ User: postgres - Total duration: 26s313ms - Times executed: 16 ]
[ Application: psql - Total duration: 26s313ms - 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: 2025-01-21 12:31:15 Duration: 2s372ms 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: 2025-01-21 12:01:15 Duration: 2s320ms 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: 2025-01-21 12:11:15 Duration: 2s176ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 16s633ms 12 1s310ms 1s557ms 1s386ms 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 #11
Day Hour Count Duration Avg duration Jan 21 12 12 16s633ms 1s386ms [ User: postgres - Total duration: 16s633ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 16s633ms - Times executed: 12 ]
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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 = '692' 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 = '692')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '692' 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 = '692') 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: 2025-01-21 12:52:00 Duration: 1s557ms 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: 2025-01-21 12:51:55 Duration: 1s509ms 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: 2025-01-21 12:36:49 Duration: 1s490ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
12 13s810ms 197 12ms 282ms 70ms 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 #12
Day Hour Count Duration Avg duration Jan 21 12 197 13s810ms 70ms [ User: postgres - Total duration: 13s810ms - Times executed: 197 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 11s627ms - Times executed: 185 ]
[ Application: [unknown] - Total duration: 2s183ms - 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: 2025-01-21 12:11:16 Duration: 282ms 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: 2025-01-21 12:46:09 Duration: 251ms 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: 2025-01-21 12:31:13 Duration: 247ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
13 12s415ms 360 0ms 274ms 34ms 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 Jan 21 12 360 12s415ms 34ms [ User: postgres - Total duration: 12s415ms - Times executed: 360 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12s415ms - Times executed: 360 ]
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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 = '1' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '1321141607' 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: 2025-01-21 12:30:04 Duration: 274ms 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 > '1585688455' 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: 2025-01-21 12:01:08 Duration: 228ms 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 = 515852059758978308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '-48402537' 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: 2025-01-21 12:40:52 Duration: 204ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
14 10s885ms 146 17ms 198ms 74ms 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 #14
Day Hour Count Duration Avg duration Jan 21 12 146 10s885ms 74ms [ User: postgres - Total duration: 10s885ms - Times executed: 146 ]
[ Application: [unknown] - Total duration: 10s885ms - Times executed: 146 ]
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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: 2025-01-21 12:27:20 Duration: 198ms 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 'IQFEED_FX - 1';
Date: 2025-01-21 12:31:17 Duration: 179ms 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: 2025-01-21 12:42:25 Duration: 178ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
15 10s286ms 16 516ms 896ms 642ms 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 Jan 21 12 16 10s286ms 642ms [ User: postgres - Total duration: 10s286ms - Times executed: 16 ]
[ Application: psql - Total duration: 10s286ms - 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: 2025-01-21 12:11:12 Duration: 896ms 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: 2025-01-21 12:31:12 Duration: 891ms 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: 2025-01-21 12:01:13 Duration: 873ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
16 9s798ms 31 13ms 1s797ms 316ms select fixcandlegaps (?, false);Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Jan 21 12 31 9s798ms 316ms [ User: postgres - Total duration: 9s798ms - Times executed: 31 ]
[ Application: psql - Total duration: 9s798ms - Times executed: 31 ]
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select fixcandlegaps ('ATFX', false);
Date: 2025-01-21 12:06:04 Duration: 1s797ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('PEPPERSTONE', false);
Date: 2025-01-21 12:06:09 Duration: 1s489ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ICMARKETS', false);
Date: 2025-01-21 12:06:07 Duration: 1s331ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
17 7s950ms 13 40ms 5s265ms 611ms 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 #17
Day Hour Count Duration Avg duration Jan 21 12 13 7s950ms 611ms [ User: postgres - Total duration: 7s950ms - Times executed: 13 ]
[ Application: psql - Total duration: 7s950ms - 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: 2025-01-21 12:11:07 Duration: 5s265ms 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: 2025-01-21 12:16:03 Duration: 601ms 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: 2025-01-21 12:03:03 Duration: 523ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
18 7s452ms 146 15ms 164ms 51ms select distinct k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid from relevance_keylevels_results p inner join keylevels_results k on p.resultuid = k.resultuid inner join autochartist_stocklist asl on k.symbolid = asl.symbolid where k.patternclassid in (...) and asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Jan 21 12 146 7s452ms 51ms [ User: postgres - Total duration: 7s452ms - Times executed: 146 ]
[ Application: [unknown] - Total duration: 7s452ms - Times executed: 146 ]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-01-21 12:30:53 Duration: 164ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-01-21 12:46:01 Duration: 161ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-01-21 12:32:07 Duration: 159ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
19 6s817ms 434 0ms 48ms 15ms 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 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 (((s.symbol ilike ? and timegranularity <= ?))) 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 #19
Day Hour Count Duration Avg duration Jan 21 12 434 6s817ms 15ms [ User: postgres - Total duration: 6s817ms - Times executed: 434 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 6s817ms - Times executed: 434 ]
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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 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 (((s.symbol ilike '%usdcad%' AND timegranularity <= 1440))) AND breakout >= 0.1 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.5 AND initialtrend >= 0.1 AND symmetry >= 0.1 AND noise <= 0.9 AND volumeincrease >= 0.1 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 605442254361953301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-01-21 12:16:00 Duration: 48ms 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 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 (((s.symbol ilike '%usdcad%' AND timegranularity <= 1440))) AND breakout >= 0.1 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.5 AND initialtrend >= 0.1 AND symmetry >= 0.1 AND noise <= 0.9 AND volumeincrease >= 0.1 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 605442254361953301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-01-21 12:56:01 Duration: 47ms 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 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 (((s.symbol ilike '%usdcad%' AND timegranularity <= 1440))) AND breakout >= 0.1 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.5 AND initialtrend >= 0.1 AND symmetry >= 0.1 AND noise <= 0.9 AND volumeincrease >= 0.1 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 605442254361953301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-01-21 12:28:00 Duration: 42ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
20 6s791ms 5,767 0ms 9ms 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 #20
Day Hour Count Duration Avg duration Jan 21 12 5,767 6s791ms 1ms [ User: postgres - Total duration: 6s791ms - Times executed: 5767 ]
[ Application: [unknown] - Total duration: 6s791ms - Times executed: 5767 ]
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-01-21 12:30:00', '502.55', '502.86', '501.26', '501.46', '29', '515840246022907300', '0', '2025-01-21 12:57:01.681', '2025-01-21 12:57:01.628') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '502.55', high = '502.86', low = '501.26', close = '501.46', volume = '29', bsf = '0', sastdatetimewritten = '2025-01-21 12:57:01.681', sastdatetimereceived = '2025-01-21 12:57:01.628';
Date: 2025-01-21 12:57:01 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-01-21 12:15:00', '0.56728', '0.5673', '0.56701', '0.56701', '745', '515840243883296300', '0', '2025-01-21 12:30:26.935', '2025-01-21 12:30:25.28') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.56728', high = '0.5673', low = '0.56701', close = '0.56701', volume = '745', bsf = '0', sastdatetimewritten = '2025-01-21 12:30:26.935', sastdatetimereceived = '2025-01-21 12:30:25.28';
Date: 2025-01-21 12:30:26 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-01-21 12:15:00', '8526.7', '8527.7', '8519.4', '8522.7', '367', '515840233377031300', '0', '2025-01-21 12:42:09.747', '2025-01-21 12:42:09.671') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '8526.7', high = '8527.7', low = '8519.4', close = '8522.7', volume = '367', bsf = '0', sastdatetimewritten = '2025-01-21 12:42:09.747', sastdatetimereceived = '2025-01-21 12:42:09.671';
Date: 2025-01-21 12:42:09 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 41,251 165ms 0ms 2ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jan 21 12 41,251 165ms 0ms [ User: postgres - Total duration: 165ms - Times executed: 41251 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 155ms - Times executed: 41040 ]
[ Application: [unknown] - Total duration: 9ms - Times executed: 211 ]
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select 1;
Date: 2025-01-21 12:00:07 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-01-21 12:00:07 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-01-21 12:45:05 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
2 28,125 39s622ms 0ms 23ms 1ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, 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 Jan 21 12 28,125 39s622ms 1ms [ User: postgres - Total duration: 39s622ms - Times executed: 28125 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 39s622ms - Times executed: 28125 ]
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, 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 = '515840243235939300';
Date: 2025-01-21 12:00:04 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, 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 = '515840218041951300';
Date: 2025-01-21 12:00:06 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, 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 = '515840217490122300';
Date: 2025-01-21 12:30:04 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
3 24,619 1m19s 0ms 35ms 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 Jan 21 12 24,619 1m19s 3ms [ User: postgres - Total duration: 1m19s - Times executed: 24619 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m19s - Times executed: 24619 ]
-
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 = 'GBPJPY' OR dss.downloadersymbol = 'GBPJPY') AND dss.enabled = 1;
Date: 2025-01-21 12:30:06 Duration: 35ms 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 = 'USDHUF' OR dss.downloadersymbol = 'USDHUF') AND dss.enabled = 1;
Date: 2025-01-21 12:15:05 Duration: 32ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 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 = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'USDSGD' OR dss.downloadersymbol = 'USDSGD') AND dss.enabled = 1;
Date: 2025-01-21 12:30:05 Duration: 31ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
4 5,767 6s791ms 0ms 9ms 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 Jan 21 12 5,767 6s791ms 1ms [ User: postgres - Total duration: 6s791ms - Times executed: 5767 ]
[ Application: [unknown] - Total duration: 6s791ms - Times executed: 5767 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-01-21 12:30:00', '502.55', '502.86', '501.26', '501.46', '29', '515840246022907300', '0', '2025-01-21 12:57:01.681', '2025-01-21 12:57:01.628') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '502.55', high = '502.86', low = '501.26', close = '501.46', volume = '29', bsf = '0', sastdatetimewritten = '2025-01-21 12:57:01.681', sastdatetimereceived = '2025-01-21 12:57:01.628';
Date: 2025-01-21 12:57:01 Duration: 9ms 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 ('2025-01-21 12:15:00', '0.56728', '0.5673', '0.56701', '0.56701', '745', '515840243883296300', '0', '2025-01-21 12:30:26.935', '2025-01-21 12:30:25.28') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.56728', high = '0.5673', low = '0.56701', close = '0.56701', volume = '745', bsf = '0', sastdatetimewritten = '2025-01-21 12:30:26.935', sastdatetimereceived = '2025-01-21 12:30:25.28';
Date: 2025-01-21 12:30:26 Duration: 9ms 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 ('2025-01-21 12:15:00', '8526.7', '8527.7', '8519.4', '8522.7', '367', '515840233377031300', '0', '2025-01-21 12:42:09.747', '2025-01-21 12:42:09.671') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '8526.7', high = '8527.7', low = '8519.4', close = '8522.7', volume = '367', bsf = '0', sastdatetimewritten = '2025-01-21 12:42:09.747', sastdatetimereceived = '2025-01-21 12:42:09.671';
Date: 2025-01-21 12:42:09 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
5 5,635 5s725ms 0ms 12ms 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 Jan 21 12 5,635 5s725ms 1ms [ User: postgres - Total duration: 5s725ms - Times executed: 5635 ]
[ Application: [unknown] - Total duration: 5s725ms - Times executed: 5635 ]
-
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 ('515840243967797300-1|45678.125|45678.3333|45678.1667|45678.4688|0.9749|0.9738|0.9704|0.9712', 515840243967797300, 2.000000000000000000000000000000, 'Triangle', 4, '2025-01-21 09:59:07'::timestamp without time zone, 1, 0.353032661407682746300000000000, - 1.000000000000000000000000000000, 0.199046591113509585600000000000, 0.111144669284201747000000000000, 0.380060431784289609600000000000, 0.973315648328438087800000000000, 0.975003555988251391400000000000, '2025-01-21 11:45:00'::timestamp without time zone, '2025-01-21 16:07:30'::timestamp without time zone, '2025-01-20 23:45:00'::timestamp without time zone, '2025-01-21 11:45:00'::timestamp without time zone, 0.970740000000000047300000000000, 0.972300000000000053100000000000, '2025-01-21 03:00:00'::timestamp without time zone, '2025-01-21 08:00:00'::timestamp without time zone, '2025-01-21 04:00:00'::timestamp without time zone, '2025-01-21 11:15:00'::timestamp without time zone, 0.974859999999999948800000000000, 0.973840000000000038900000000000, 0.970400000000000040300000000000, 0.971239999999999992200000000000, 0.000028965517241377653120000000, - 0.000050999999999995493380000000, 2.176986734057635431000000000000, 0.540649474635923499300000000000, 'Continuation', 0.000000000000000000000000000000, '2025-01-21 11:45:00'::timestamp without time zone, 0.972110000000000029600000000000, 35, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-01-21 12:02:10 Duration: 12ms 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 ('515840243203999300-1|45678.1667|45678.4375|45678.3333|45678.5|13.9421|13.971|13.9217|13.9485', 515840243203999300, 2.000000000000000000000000000000, 'Rising Wedge', 4, '2025-01-21 10:54:02'::timestamp without time zone, 1, 0.280939990221572399900000000000, - 1.000000000000000000000000000000, 0.394449418965059250800000000000, 0.080984919364297011660000000000, 0.593155576215568136600000000000, 13.970690599164557360000000000000, 13.979217437994938320000000000000, '2025-01-21 12:30:00'::timestamp without time zone, '2025-01-21 16:45:00'::timestamp without time zone, '2025-01-21 00:30:00'::timestamp without time zone, '2025-01-21 12:30:00'::timestamp without time zone, 13.897159999999999510000000000000, 13.969049999999999300000000000000, '2025-01-21 04:00:00'::timestamp without time zone, '2025-01-21 10:30:00'::timestamp without time zone, '2025-01-21 08:00:00'::timestamp without time zone, '2025-01-21 12:00:00'::timestamp without time zone, 13.942069999999999300000000000000, 13.970990000000000460000000000000, 13.921689999999999900000000000000, 13.948549999999999120000000000000, 0.001678749999999951115000000000, 0.001112307692307737276000000000, 2.485729112386219519000000000000, 0.597703549024281133300000000000, 'Continuation', 0.000000000000000000000000000000, '2025-01-21 12:30:00'::timestamp without time zone, 13.964600000000000790000000000000, 34, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-01-21 12:57:05 Duration: 11ms 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 ('515840221151897300-1|45677.8021|45678.1458|45677.8333|45678.1771|43980|43868|43497|43812', 515840221151897300, 4.000000000000000000000000000000, 'Triangle', 4, '2025-01-21 09:57:29'::timestamp without time zone, 1, 0.153160003409549133600000000000, - 1.000000000000000000000000000000, 0.303923559979011159700000000000, 1.000000000000000000000000000000, 0.437479138963006775000000000000, 43881.546450960988300000000000000000, 43948.111482306376280000000000000000, '2025-01-21 04:30:00'::timestamp without time zone, '2025-01-21 09:07:30'::timestamp without time zone, '2025-01-20 10:45:00'::timestamp without time zone, '2025-01-21 04:30:00'::timestamp without time zone, 43743.000000000000000000000000000000, 43843.000000000000000000000000000000, '2025-01-20 19:15:00'::timestamp without time zone, '2025-01-21 03:30:00'::timestamp without time zone, '2025-01-20 20:00:00'::timestamp without time zone, '2025-01-21 04:15:00'::timestamp without time zone, 43980.000000000000000000000000000000, 43868.000000000000000000000000000000, 43497.000000000000000000000000000000, 43812.000000000000000000000000000000, 9.545454545454544970000000000000, - 3.393939393939394034000000000000, 1.245143495422339042000000000000, 0.196879714124185312100000000000, 'Continuation', 0.000000000000000000000000000000, '2025-01-21 04:30:00'::timestamp without time zone, 43834.000000000000000000000000000000, 37, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-01-21 12:00:32 Duration: 11ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
6 3,288 1s539ms 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 Jan 21 12 3,288 1s539ms 0ms [ User: postgres - Total duration: 1s539ms - Times executed: 3288 ]
[ Application: [unknown] - Total duration: 1s539ms - Times executed: 3288 ]
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-01-21 11:30:00', '3144.19', '3156.83', '3142.17', '3156.77', '6993', '515840247911613300', '0', '2025-01-21 12:11:55.601', '2025-01-21 12:11:55.566') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '3144.19', high = '3156.83', low = '3142.17', close = '3156.77', volume = '6993', bsf = '0', sastdatetimewritten = '2025-01-21 12:11:55.601', sastdatetimereceived = '2025-01-21 12:11:55.566';
Date: 2025-01-21 12:11:55 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-01-21 12:00:00', '63.0019', '63.1019', '62.9669', '63.0119', '524', '515840247905764300', '0', '2025-01-21 12:41:43.227', '2025-01-21 12:41:43.171') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '63.0019', high = '63.1019', low = '62.9669', close = '63.0119', volume = '524', bsf = '0', sastdatetimewritten = '2025-01-21 12:41:43.227', sastdatetimereceived = '2025-01-21 12:41:43.171';
Date: 2025-01-21 12:41:43 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-01-21 12:00:00', '21.4228', '21.48', '21.3628', '21.38', '178', '515840247904216300', '0', '2025-01-21 12:41:41.211', '2025-01-21 12:41:41.155') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '21.4228', high = '21.48', low = '21.3628', close = '21.38', volume = '178', bsf = '0', sastdatetimewritten = '2025-01-21 12:41:41.211', sastdatetimereceived = '2025-01-21 12:41:41.155';
Date: 2025-01-21 12:41:41 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
7 3,066 1s360ms 0ms 6ms 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 #7
Day Hour Count Duration Avg duration Jan 21 12 3,066 1s360ms 0ms [ User: postgres - Total duration: 1s360ms - Times executed: 3066 ]
[ Application: [unknown] - Total duration: 1s360ms - Times executed: 3066 ]
-
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 (2.000000000000000000000000000000, 'ABCD', '2025-01-21 09:59:07'::timestamp without time zone, - 1, '2025-01-21 03:00:00'::timestamp without time zone, '2025-01-21 11:45:00'::timestamp without time zone, 0.974859999999999948800000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.970400000000000040300000000000, '2025-01-21 04:00:00'::timestamp without time zone, 0.973840000000000038900000000000, '2025-01-21 08:00:00'::timestamp without time zone, 0.971239999999999992200000000000, '2025-01-21 11:15:00'::timestamp without time zone, 0.974679999999999990800000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.460257045860483438000000000000, - 1.000000000000000000000000000000, 0.377813479410306130000000000000, 45, 0.971239999999999992200000000000, 0.972553963078871985800000000000, 0.969113963078871987200000000000, 0.971975639260368007300000000000, 0.970304252405720046900000000000, 0.972960000000000047000000000000, 0.973366036921127997200000000000, 515840243967797300, 0.457299387689339309500000000000, 'BC=0.786*AB (0.756) ', 0, 'ABCD|-1|2025-01-21 03:00:00|0.97486|-1|4|45|BC=0.786*AB (0.756)|0|515840243967797300|1899-12-29 00:00:00|2025-01-21 04:00:00|2025-01-21 08:00:00|2025-01-21 11:15:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-01-21 12:02:10 Duration: 6ms 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, 'Butterfly', '2025-01-21 10:39:26'::timestamp without time zone, - 1, '2025-01-20 16:15:00'::timestamp without time zone, '2025-01-21 12:15:00'::timestamp without time zone, 230.419999999999987500000000000000, - 1.000000000000000000000000000000, 5, 230.419999999999987500000000000000, '2025-01-20 16:15:00'::timestamp without time zone, 228.800000000000011400000000000000, '2025-01-21 10:00:00'::timestamp without time zone, 230.319999999999993200000000000000, '2025-01-21 10:45:00'::timestamp without time zone, 229.400000000000005700000000000000, '2025-01-21 11:45:00'::timestamp without time zone, 230.860671832189979100000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.655025263150643466400000000000, - 1.000000000000000000000000000000, 10.363106951832085301000000000000, 22, 229.400000000000005700000000000000, 229.957926993559880200000000000000, 228.497255161369906800000000000000, 229.712362658800174100000000000000, 229.002668560173162900000000000000, 230.130335916094992400000000000000, 230.302744838630104600000000000000, 515840246017377300, 0.689949473698713178200000000000, 'BC=0.618*AB (0.605) ', 0, 'Butterfly|-1|2025-01-20 16:15:00|230.42|-1|5|22|BC=0.618*AB (0.605)|0|515840246017377300|2025-01-20 16:15:00|2025-01-21 10:00:00|2025-01-21 10:45:00|2025-01-21 11:45:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-01-21 12:42:29 Duration: 5ms 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, 'ABCD', '2025-01-21 10:28:16'::timestamp without time zone, - 1, '2025-01-16 04:00:00'::timestamp without time zone, '2025-01-21 04:00:00'::timestamp without time zone, 160.729999999999989800000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 158.914999999999992000000000000000, '2025-01-16 10:00:00'::timestamp without time zone, 163.159999999999996600000000000000, '2025-01-17 09:00:00'::timestamp without time zone, 160.539999999999992000000000000000, '2025-01-17 15:00:00'::timestamp without time zone, 164.784999999999996600000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.708442743932298668600000000000, - 1.000000000000000000000000000000, 55.686548570774967000000000000000, 32, 160.539999999999992000000000000000, 162.161445717968490500000000000000, 157.916445717968486000000000000000, 161.447787401238997500000000000000, 159.385276587872482400000000000000, 162.662499999999994300000000000000, 163.163554282031498100000000000000, 515840249534006300, 0.583114512135402662800000000000, 'BC=0.618*AB (0.617) ', 0, 'ABCD|-1|2025-01-16 04:00:00|160.73|-1|4|32|BC=0.618*AB (0.617)|0|515840249534006300|1899-12-29 00:00:00|2025-01-16 10:00:00|2025-01-17 09:00:00|2025-01-17 15:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-01-21 12:31:18 Duration: 5ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
8 2,113 652ms 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 #8
Day Hour Count Duration Avg duration Jan 21 12 2,113 652ms 0ms [ User: postgres - Total duration: 652ms - Times executed: 2113 ]
[ Application: [unknown] - Total duration: 652ms - Times executed: 2113 ]
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-01-21 11:00:00', '0.2235', '0.2291', '0.2222', '0.2244', '1862', '515840247924778300', '0', '2025-01-21 12:12:08.011', '2025-01-21 12:12:07.945') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.2235', high = '0.2291', low = '0.2222', close = '0.2244', volume = '1862', bsf = '0', sastdatetimewritten = '2025-01-21 12:12:08.011', sastdatetimereceived = '2025-01-21 12:12:07.945';
Date: 2025-01-21 12:12:08 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-01-21 11:00:00', '3132.84', '3156.83', '3129.18', '3156.77', '14340', '515840247911908300', '0', '2025-01-21 12:11:55.635', '2025-01-21 12:11:55.586') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '3132.84', high = '3156.83', low = '3129.18', close = '3156.77', volume = '14340', bsf = '0', sastdatetimewritten = '2025-01-21 12:11:55.635', sastdatetimereceived = '2025-01-21 12:11:55.586';
Date: 2025-01-21 12:11:55 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-01-21 11:00:00', '0.81335', '0.81344', '0.81193', '0.81214', '6544', '515840247886145300', '0', '2025-01-21 12:12:05.992', '2025-01-21 12:12:05.955') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.81335', high = '0.81344', low = '0.81193', close = '0.81214', volume = '6544', bsf = '0', sastdatetimewritten = '2025-01-21 12:12:05.992', sastdatetimereceived = '2025-01-21 12:12:05.955';
Date: 2025-01-21 12:12:05 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
9 1,793 2s831ms 0ms 15ms 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 Jan 21 12 1,793 2s831ms 1ms [ User: postgres - Total duration: 2s831ms - Times executed: 1793 ]
[ Application: [unknown] - Total duration: 2s831ms - Times executed: 1793 ]
-
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 (3.000000000000000000000000000000, - 1, 1, '2025-01-21 10:54:03'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 61, 13.600049999999999530000000000000, '2025-01-21 10:30:00', '2025-01-21 03:00:00', '2025-01-20 19:15:00', '', '', '', '', '', '', '', 122, 13.602581499999999440000000000000, '2025-01-21 12:30:00'::timestamp without time zone, '2025-01-21 12:30:00', 0.000000000000000000000000000000, 0.002580500000000008134000000000, - 1, 515840243205727300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840243205727300|13.60005|1|2025-01-21 12:30:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-01-20 19:15:00', 13.600049999999999530000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-01-21 12:57:05 Duration: 15ms 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 (4.000000000000000000000000000000, - 1, 1, '2025-01-21 10:54:03'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 61, 13.600049999999999530000000000000, '2025-01-21 10:30:00', '2025-01-21 03:00:00', '2025-01-20 19:15:00', '', '', '', '', '', '', '', 122, 13.602581499999999440000000000000, '2025-01-21 12:30:00'::timestamp without time zone, '2025-01-21 12:30:00', 0.000000000000000000000000000000, 0.002580500000000008134000000000, - 1, 515840243205727300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840243205727300|13.60005|1|2025-01-21 12:30:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-01-20 19:15:00', 13.600049999999999530000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-01-21 12:57:05 Duration: 13ms 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 (7.000000000000000000000000000000, - 1, 2, '2025-01-21 10:27:53'::timestamp without time zone, '2025-01-21 12:00:00', 0.005189999999999988026000000000, 5, 336, 0.617920000000000024800000000000, '2025-01-15 03:00:00', '2025-01-14 22:00:00', '2025-01-14 07:30:00', '2025-01-14 04:00:00', '2025-01-10 12:00:00', '', '', '', '', '', 378, 0.617557000000000022600000000000, '2025-01-21 12:00:00'::timestamp without time zone, '2025-01-21 12:00:00', 0.622870000000000034800000000000, 0.000362999999999997005600000000, - 1, 515840241623410300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840241623410300|0.61792|2|2025-01-21 12:00:00|2025-01-21 12:00:00|-1|-1', 0.625082200000000032200000000000, 0.007162200000000007450000000000, 2, '2025-01-10 12:00:00', 0.626029999999999975400000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-01-21 12:30:56 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
10 1,532 1s21ms 0ms 6ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Jan 21 12 1,532 1s21ms 0ms [ User: postgres - Total duration: 1s21ms - Times executed: 1532 ]
[ Application: [unknown] - Total duration: 1s21ms - Times executed: 1532 ]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-01-21 12:30:00', reason = 'Price has moved too far in the wrong direction' WHERE uniqueIndex = '|515840243202065300|8.83623|1|2025-01-21 12:00:00|2025-01-21 12:00:00|1|-1' and relevant = 1;
Date: 2025-01-21 12:57:05 Duration: 6ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-01-17 00:00:00', reason = 'Emerging pattern broke out in the wrong direction.' WHERE uniqueIndex = '515840249548031300-1|45554|45664|45611|45665|119.49|102.97|94.48|98.05' and relevant = 1;
Date: 2025-01-21 12:31:20 Duration: 5ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-01-17 00:00:00', reason = 'Price has moved too far in the wrong direction' WHERE uniqueIndex = '|515840249545352300|119.16|2|2025-01-10 00:00:00|-1|1' and relevant = 1;
Date: 2025-01-21 12:16:05 Duration: 5ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
11 1,263 618ms 0ms 8ms 0ms insert into t240 (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 Jan 21 12 1,263 618ms 0ms [ User: postgres - Total duration: 618ms - Times executed: 1263 ]
[ Application: [unknown] - Total duration: 618ms - Times executed: 1263 ]
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-01-21 08:00:00', '0.2184', '0.2314', '0.2179', '0.2244', '6713', '515840247925040300', '0', '2025-01-21 12:12:08.075', '2025-01-21 12:12:07.979') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.2184', high = '0.2314', low = '0.2179', close = '0.2244', volume = '6713', bsf = '0', sastdatetimewritten = '2025-01-21 12:12:08.075', sastdatetimereceived = '2025-01-21 12:12:07.979';
Date: 2025-01-21 12:12:08 Duration: 8ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-01-21 08:00:00', '4.10003', '4.11533', '4.09633', '4.10943', '18904', '515840247874168300', '0', '2025-01-21 12:12:10.083', '2025-01-21 12:12:10.01') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '4.10003', high = '4.11533', low = '4.09633', close = '4.10943', volume = '18904', bsf = '0', sastdatetimewritten = '2025-01-21 12:12:10.083', sastdatetimereceived = '2025-01-21 12:12:10.01';
Date: 2025-01-21 12:12:10 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-01-21 08:00:00', '1.22752', '1.22856', '1.22339', '1.22472', '21692', '515840247885326300', '0', '2025-01-21 12:12:04.089', '2025-01-21 12:12:04.006') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '1.22752', high = '1.22856', low = '1.22339', close = '1.22472', volume = '21692', bsf = '0', sastdatetimewritten = '2025-01-21 12:12:04.089', sastdatetimereceived = '2025-01-21 12:12:04.006';
Date: 2025-01-21 12:12:04 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
12 1,250 648ms 0ms 17ms 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ) select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as ruid, s.symbolid as sid, s.symbol as sym, longname, shortname, exchange as e, timegranularity as tg, a.patternid as pid, a.direction as d, a.patternprice as pp, atbaridentified as pet, case when (x9 != ?) then x9 when (x8 != ?) then x8 when (x7 != ?) then x7 when (x6 != ?) then x6 when (x5 != ?) then x5 when (x4 != ?) then x4 when (x3 != ?) then x3 when (x2 != ?) then x2 end as pst, patternprice as patp, x0, x1, x2, case when (x3 != ?) then x3 else ? end as x3, case when (x4 != ?) then x4 else ? end as x4, case when (x5 != ?) then x5 else ? end as x5, case when (x6 != ?) then x6 else ? end as x6, case when (x7 != ?) then x7 else ? end as x7, case when (x8 != ?) then x8 else ? end as x8, errormargin as erm, breakoutprice as pe, breakoutbars as be, breakout, atbaridentified as atbar, atpriceidentified as atprice, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzos, dtt.timezone as timezone, approachingtimestamp as apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, furthestprice as fp, newlevels.filtered, a.uniquepointsvalue as upv, 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 keylevels_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 hrspatterns p on a.patternid = p.patternid inner join rar_max rm on ? = ? left outer join relevance_keylevels_results rar on a.resultuid = rar.resultuid left join lateral calc_kl_signal_filter (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 #12
Day Hour Count Duration Avg duration Jan 21 12 1,250 648ms 0ms [ User: postgres - Total duration: 648ms - Times executed: 1250 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 648ms - Times executed: 1250 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '605473401128766303' THEN a.old_resultuid ELSE a.resultuid END AS ruid, s.symbolid AS sid, s.symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice AS pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '0' END AS x3, CASE WHEN (x4 != '') THEN x4 ELSE '0' END AS x4, CASE WHEN (x5 != '') THEN x5 ELSE '0' END AS x5, CASE WHEN (x6 != '') THEN x6 ELSE '0' END AS x6, CASE WHEN (x7 != '') THEN x7 ELSE '0' END AS x7, CASE WHEN (x8 != '') THEN x8 ELSE '0' END AS x8, errorMargin AS erm, breakoutprice AS pE, breakoutbars AS be, breakout, atbaridentified AS atBar, atpriceidentified AS atPrice, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname AS patternname, dtt.absolutetimezoneoffset AS tzOs, dtt.timezone AS timezone, approachingtimestamp AS apt, approachingregion AS apr, predictionpricefrom AS ppf, predictionpriceto AS ppt, predictiontimefrom AS ptf, predictiontimebars AS ptb, furthestprice AS fp, newLevels.filtered, a.uniquepointsvalue AS upv, 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 keylevels_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 hrspatterns p ON a.patternid = p.patternid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_keylevels_results rar ON a.resultuid = rar.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (a.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol WHERE (a.old_resultuid = '605473401128766303' OR a.resultuid = '605473401128766303') AND dtt.dayofweek = 3;
Date: 2025-01-21 12:11:13 Duration: 17ms 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 ) SELECT CASE WHEN a.old_resultuid = '605474598380532303' THEN a.old_resultuid ELSE a.resultuid END AS ruid, s.symbolid AS sid, s.symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice AS pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '0' END AS x3, CASE WHEN (x4 != '') THEN x4 ELSE '0' END AS x4, CASE WHEN (x5 != '') THEN x5 ELSE '0' END AS x5, CASE WHEN (x6 != '') THEN x6 ELSE '0' END AS x6, CASE WHEN (x7 != '') THEN x7 ELSE '0' END AS x7, CASE WHEN (x8 != '') THEN x8 ELSE '0' END AS x8, errorMargin AS erm, breakoutprice AS pE, breakoutbars AS be, breakout, atbaridentified AS atBar, atpriceidentified AS atPrice, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname AS patternname, dtt.absolutetimezoneoffset AS tzOs, dtt.timezone AS timezone, approachingtimestamp AS apt, approachingregion AS apr, predictionpricefrom AS ppf, predictionpriceto AS ppt, predictiontimefrom AS ptf, predictiontimebars AS ptb, furthestprice AS fp, newLevels.filtered, a.uniquepointsvalue AS upv, 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 keylevels_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 hrspatterns p ON a.patternid = p.patternid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_keylevels_results rar ON a.resultuid = rar.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (a.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol WHERE (a.old_resultuid = '605474598380532303' OR a.resultuid = '605474598380532303') AND dtt.dayofweek = 3;
Date: 2025-01-21 12:31:00 Duration: 10ms 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_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '605474339821706303' THEN a.old_resultuid ELSE a.resultuid END AS ruid, s.symbolid AS sid, s.symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice AS pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '0' END AS x3, CASE WHEN (x4 != '') THEN x4 ELSE '0' END AS x4, CASE WHEN (x5 != '') THEN x5 ELSE '0' END AS x5, CASE WHEN (x6 != '') THEN x6 ELSE '0' END AS x6, CASE WHEN (x7 != '') THEN x7 ELSE '0' END AS x7, CASE WHEN (x8 != '') THEN x8 ELSE '0' END AS x8, errorMargin AS erm, breakoutprice AS pE, breakoutbars AS be, breakout, atbaridentified AS atBar, atpriceidentified AS atPrice, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname AS patternname, dtt.absolutetimezoneoffset AS tzOs, dtt.timezone AS timezone, approachingtimestamp AS apt, approachingregion AS apr, predictionpricefrom AS ppf, predictionpriceto AS ppt, predictiontimefrom AS ptf, predictiontimebars AS ptb, furthestprice AS fp, newLevels.filtered, a.uniquepointsvalue AS upv, 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 keylevels_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 hrspatterns p ON a.patternid = p.patternid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_keylevels_results rar ON a.resultuid = rar.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (a.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol WHERE (a.old_resultuid = '605474339821706303' OR a.resultuid = '605474339821706303') AND dtt.dayofweek = 3;
Date: 2025-01-21 12:11:13 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
13 812 25ms 0ms 0ms 0ms select df.absolutetimezoneoffset from datafeedstimetable df inner join downloadersymbolsettings dss on df.classname = dss.classname where dss.symbolid = ? group by df.absolutetimezoneoffset limit ?;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jan 21 12 812 25ms 0ms [ User: postgres - Total duration: 25ms - Times executed: 812 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 25ms - Times executed: 812 ]
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '500991628204074200' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-01-21 12:02:34 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.239 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '500991628284405200' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-01-21 12:32:59 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.239 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '515840245512807300' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-01-21 12:51:13 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
14 771 7ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Jan 21 12 771 7ms 0ms [ User: postgres - Total duration: 7ms - Times executed: 771 ]
[ Application: [unknown] - Total duration: 7ms - Times executed: 771 ]
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SET extra_float_digits = 3;
Date: 2025-01-21 12:00:03 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: 2025-01-21 12:30:05 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: 2025-01-21 12:45:04 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: [unknown] Bind query: yes
15 745 10ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Jan 21 12 745 10ms 0ms [ User: postgres - Total duration: 10ms - Times executed: 745 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 10ms - Times executed: 745 ]
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-01-21 12:15:04 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-01-21 12:56:52 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-01-21 12:37:32 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
16 736 718ms 0ms 5ms 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 Jan 21 12 736 718ms 0ms [ User: postgres - Total duration: 718ms - Times executed: 736 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 718ms - Times executed: 736 ]
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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 = '605474344035172301' 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 = '605474344035172301' OR a.resultuid = '605474344035172301') AND dtt.dayofweek = 3;
Date: 2025-01-21 12:01:12 Duration: 5ms 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_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 = '605474342117066301' 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 = '605474342117066301' OR a.resultuid = '605474342117066301') AND dtt.dayofweek = 3;
Date: 2025-01-21 12:00:55 Duration: 5ms 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 = '605474345900156301' 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 = '605474345900156301' OR a.resultuid = '605474345900156301') AND dtt.dayofweek = 3;
Date: 2025-01-21 12:01:12 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
17 674 3s100ms 2ms 21ms 4ms 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 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 (((c.symbol ilike ? and timegranularity <= ?))) and patternclassid = ? and patternlengthbars >= ? and a.patternid & ? > ? and dftt.dayofweek = ? 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 #17
Day Hour Count Duration Avg duration Jan 21 12 674 3s100ms 4ms [ User: postgres - Total duration: 3s100ms - Times executed: 674 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s100ms - Times executed: 674 ]
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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 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 (((c.symbol ilike '%gbpjpy%' AND timegranularity <= 1440))) AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '3' > 0 AND dftt.dayofweek = '3' AND a.resultuid > '-342364881' 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: 2025-01-21 12:00:06 Duration: 21ms 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 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 (((c.symbol ilike '%euraud%' AND timegranularity <= 1440))) AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '3' > 0 AND dftt.dayofweek = '3' AND a.resultuid > '1890597887' 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: 2025-01-21 12:52:16 Duration: 10ms 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 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 (((c.symbol ilike '%usdchf%' AND timegranularity <= 1440))) AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '3' > 0 AND dftt.dayofweek = '3' AND a.resultuid > '1523339943' 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: 2025-01-21 12:32:09 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
18 641 52ms 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 #18
Day Hour Count Duration Avg duration Jan 21 12 641 52ms 0ms [ User: postgres - Total duration: 52ms - Times executed: 641 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 52ms - Times executed: 641 ]
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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 = '605474105126680301';
Date: 2025-01-21 12:40:20 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 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 = '605474301922126301';
Date: 2025-01-21 12:24:00 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 = '605474244926350301';
Date: 2025-01-21 12:47:57 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
19 628 1s716ms 0ms 26ms 2ms select * from powerstatslatestprfprice (?, ?);Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Jan 21 12 628 1s716ms 2ms [ User: postgres - Total duration: 1s716ms - Times executed: 628 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s679ms - Times executed: 618 ]
[ Application: [unknown] - Total duration: 36ms - Times executed: 10 ]
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select * from PowerStatsLatestPRFPrice ('515840243872417300', '15');
Date: 2025-01-21 12:16:11 Duration: 26ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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select * from PowerStatsLatestPRFPrice ('515840243872417300', '15');
Date: 2025-01-21 12:31:11 Duration: 25ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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select * from PowerStatsLatestPRFPrice ('515840238072342300', '15');
Date: 2025-01-21 12:00:58 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
20 571 935ms 0ms 5ms 1ms select t.pricedatetime as pricedatetime, t.open as open, t.high as high, t.low as low, t.close "..." close, t.volume as volume, t.bsf as bsf from t60 t where t.symbolid = ? and (bsf = ? or bsf is null) and pricedatetime >= ? and pricedatetime <= ? order by pricedatetime desc limit ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Jan 21 12 571 935ms 1ms [ User: postgres - Total duration: 935ms - Times executed: 571 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 935ms - Times executed: 571 ]
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SELECT T.PriceDateTime AS pricedatetime, T.Open AS open, T.High AS high, T.Low AS low, T.Close AS close, T.Volume AS volume, T.BSF AS bsf FROM T60 T WHERE T.symbolid = '515840233914385300' AND (BSF = '0' OR BSF IS NULL) AND pricedatetime >= '1900-01-01 00:00:00' AND pricedatetime <= '2900-01-01 00:00:00' ORDER BY PriceDateTime DESC LIMIT 400;
Date: 2025-01-21 12:30:05 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT T.PriceDateTime AS pricedatetime, T.Open AS open, T.High AS high, T.Low AS low, T.Close AS close, T.Volume AS volume, T.BSF AS bsf FROM T60 T WHERE T.symbolid = '515840233328756300' AND (BSF = '0' OR BSF IS NULL) AND pricedatetime >= '1900-01-01 00:00:00' AND pricedatetime <= '2900-01-01 00:00:00' ORDER BY PriceDateTime DESC LIMIT 400;
Date: 2025-01-21 12:30:08 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT T.PriceDateTime AS pricedatetime, T.Open AS open, T.High AS high, T.Low AS low, T.Close AS close, T.Volume AS volume, T.BSF AS bsf FROM T60 T WHERE T.symbolid = '515840233914385300' AND (BSF = '0' OR BSF IS NULL) AND pricedatetime >= '1900-01-01 00:00:00' AND pricedatetime <= '2900-01-01 00:00:00' ORDER BY PriceDateTime DESC LIMIT 400;
Date: 2025-01-21 12:30:05 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 1s702ms 21s233ms 9s168ms 281 42m56s 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 Jan 21 12 281 42m56s 9s168ms [ User: postgres - Total duration: 42m56s - Times executed: 281 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 39m51s - Times executed: 269 ]
[ Application: [unknown] - Total duration: 3m4s - 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: 2025-01-21 12:55:51 Duration: 21s233ms 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 = '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 ('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 ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-01-21 12:15:19 Duration: 17s215ms 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_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: 2025-01-21 12:40:59 Duration: 16s828ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
2 4s370ms 23s971ms 9s10ms 282 42m21s 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 Jan 21 12 282 42m21s 9s10ms [ User: postgres - Total duration: 42m21s - Times executed: 282 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 39m20s - Times executed: 270 ]
[ Application: [unknown] - Total duration: 3m - 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 ('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: 2025-01-21 12:31:17 Duration: 23s971ms 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 = '627' 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 ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) 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 ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-01-21 12:11:24 Duration: 20s263ms 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: 2025-01-21 12:31:11 Duration: 19s729ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
3 7s842ms 8s274ms 8s25ms 4 32s103ms select updateageforrelevantresults ();Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jan 21 12 4 32s103ms 8s25ms [ User: postgres - Total duration: 32s103ms - Times executed: 4 ]
[ Application: psql - Total duration: 32s103ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-01-21 12:17:10 Duration: 8s274ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-01-21 12:47:10 Duration: 8s78ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-01-21 12:32:09 Duration: 7s908ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
4 4s203ms 7s243ms 5s501ms 6 33s8ms 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 Jan 21 12 6 33s8ms 5s501ms [ User: postgres - Total duration: 33s8ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 33s8ms - 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: 2025-01-21 12:00:10 Duration: 7s243ms 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: 2025-01-21 12:30:10 Duration: 7s46ms 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: 2025-01-21 12:40:07 Duration: 4s956ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
5 555ms 8s803ms 2s770ms 281 12m58s 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 Jan 21 12 281 12m58s 2s770ms [ User: postgres - Total duration: 12m58s - Times executed: 281 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 11m52s - Times executed: 269 ]
[ Application: [unknown] - Total duration: 1m5s - 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: 2025-01-21 12:40:54 Duration: 8s803ms 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 = '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: 2025-01-21 12:10:54 Duration: 8s672ms 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 ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR fr.pattern in ('')) AND ('0' = 0 OR fr.patternlengthbars <= '0') 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: 2025-01-21 12:11:04 Duration: 5s466ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
6 1s411ms 2s372ms 1s644ms 16 26s313ms 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 Jan 21 12 16 26s313ms 1s644ms [ User: postgres - Total duration: 26s313ms - Times executed: 16 ]
[ Application: psql - Total duration: 26s313ms - 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: 2025-01-21 12:31:15 Duration: 2s372ms 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: 2025-01-21 12:01:15 Duration: 2s320ms 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: 2025-01-21 12:11:15 Duration: 2s176ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
7 1s310ms 1s557ms 1s386ms 12 16s633ms 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 #7
Day Hour Count Duration Avg duration Jan 21 12 12 16s633ms 1s386ms [ User: postgres - Total duration: 16s633ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 16s633ms - Times executed: 12 ]
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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 = '692' 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 = '692')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '692' 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 = '692') 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: 2025-01-21 12:52:00 Duration: 1s557ms 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: 2025-01-21 12:51:55 Duration: 1s509ms 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: 2025-01-21 12:36:49 Duration: 1s490ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
8 516ms 896ms 642ms 16 10s286ms 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 #8
Day Hour Count Duration Avg duration Jan 21 12 16 10s286ms 642ms [ User: postgres - Total duration: 10s286ms - Times executed: 16 ]
[ Application: psql - Total duration: 10s286ms - 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: 2025-01-21 12:11:12 Duration: 896ms 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: 2025-01-21 12:31:12 Duration: 891ms 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: 2025-01-21 12:01:13 Duration: 873ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
9 40ms 5s265ms 611ms 13 7s950ms 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 #9
Day Hour Count Duration Avg duration Jan 21 12 13 7s950ms 611ms [ User: postgres - Total duration: 7s950ms - Times executed: 13 ]
[ Application: psql - Total duration: 7s950ms - 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: 2025-01-21 12:11:07 Duration: 5s265ms 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: 2025-01-21 12:16:03 Duration: 601ms 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: 2025-01-21 12:03:03 Duration: 523ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
10 249ms 912ms 425ms 90 38s276ms 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 #10
Day Hour Count Duration Avg duration Jan 21 12 90 38s276ms 425ms [ User: postgres - Total duration: 38s276ms - Times executed: 90 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 38s276ms - Times executed: 90 ]
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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: 2025-01-21 12:16:00 Duration: 912ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 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: 2025-01-21 12:16:00 Duration: 912ms 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 = '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: 2025-01-21 12:56:00 Duration: 853ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
11 75ms 1s37ms 355ms 197 1m10s 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 #11
Day Hour Count Duration Avg duration Jan 21 12 197 1m10s 355ms [ User: postgres - Total duration: 1m10s - Times executed: 197 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m1s - Times executed: 185 ]
[ Application: [unknown] - Total duration: 8s72ms - 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: 2025-01-21 12:31:12 Duration: 1s37ms 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: 2025-01-21 12:01:07 Duration: 991ms 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: 2025-01-21 12:11:15 Duration: 860ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
12 13ms 1s797ms 316ms 31 9s798ms select fixcandlegaps (?, false);Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jan 21 12 31 9s798ms 316ms [ User: postgres - Total duration: 9s798ms - Times executed: 31 ]
[ Application: psql - Total duration: 9s798ms - Times executed: 31 ]
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select fixcandlegaps ('ATFX', false);
Date: 2025-01-21 12:06:04 Duration: 1s797ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('PEPPERSTONE', false);
Date: 2025-01-21 12:06:09 Duration: 1s489ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ICMARKETS', false);
Date: 2025-01-21 12:06:07 Duration: 1s331ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
13 17ms 198ms 74ms 146 10s885ms 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 #13
Day Hour Count Duration Avg duration Jan 21 12 146 10s885ms 74ms [ User: postgres - Total duration: 10s885ms - Times executed: 146 ]
[ Application: [unknown] - Total duration: 10s885ms - Times executed: 146 ]
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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: 2025-01-21 12:27:20 Duration: 198ms 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 'IQFEED_FX - 1';
Date: 2025-01-21 12:31:17 Duration: 179ms 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: 2025-01-21 12:42:25 Duration: 178ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
14 12ms 282ms 70ms 197 13s810ms 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 Jan 21 12 197 13s810ms 70ms [ User: postgres - Total duration: 13s810ms - Times executed: 197 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 11s627ms - Times executed: 185 ]
[ Application: [unknown] - Total duration: 2s183ms - 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: 2025-01-21 12:11:16 Duration: 282ms 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: 2025-01-21 12:46:09 Duration: 251ms 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: 2025-01-21 12:31:13 Duration: 247ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
15 15ms 164ms 51ms 146 7s452ms select distinct k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid from relevance_keylevels_results p inner join keylevels_results k on p.resultuid = k.resultuid inner join autochartist_stocklist asl on k.symbolid = asl.symbolid where k.patternclassid in (...) and asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Jan 21 12 146 7s452ms 51ms [ User: postgres - Total duration: 7s452ms - Times executed: 146 ]
[ Application: [unknown] - Total duration: 7s452ms - Times executed: 146 ]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-01-21 12:30:53 Duration: 164ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-01-21 12:46:01 Duration: 161ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-01-21 12:32:07 Duration: 159ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
16 0ms 274ms 34ms 360 12s415ms 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 Jan 21 12 360 12s415ms 34ms [ User: postgres - Total duration: 12s415ms - Times executed: 360 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12s415ms - Times executed: 360 ]
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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 = '1' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '1321141607' 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: 2025-01-21 12:30:04 Duration: 274ms 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 > '1585688455' 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: 2025-01-21 12:01:08 Duration: 228ms 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 = 515852059758978308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '-48402537' 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: 2025-01-21 12:40:52 Duration: 204ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
17 0ms 48ms 15ms 434 6s817ms 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 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 (((s.symbol ilike ? and timegranularity <= ?))) 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 Jan 21 12 434 6s817ms 15ms [ User: postgres - Total duration: 6s817ms - Times executed: 434 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 6s817ms - Times executed: 434 ]
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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 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 (((s.symbol ilike '%usdcad%' AND timegranularity <= 1440))) AND breakout >= 0.1 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.5 AND initialtrend >= 0.1 AND symmetry >= 0.1 AND noise <= 0.9 AND volumeincrease >= 0.1 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 605442254361953301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-01-21 12:16:00 Duration: 48ms 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 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 (((s.symbol ilike '%usdcad%' AND timegranularity <= 1440))) AND breakout >= 0.1 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.5 AND initialtrend >= 0.1 AND symmetry >= 0.1 AND noise <= 0.9 AND volumeincrease >= 0.1 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 605442254361953301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-01-21 12:56:01 Duration: 47ms 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 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 (((s.symbol ilike '%usdcad%' AND timegranularity <= 1440))) AND breakout >= 0.1 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.5 AND initialtrend >= 0.1 AND symmetry >= 0.1 AND noise <= 0.9 AND volumeincrease >= 0.1 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 605442254361953301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2025-01-21 12:28:00 Duration: 42ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
18 2ms 21ms 4ms 674 3s100ms 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 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 (((c.symbol ilike ? and timegranularity <= ?))) and patternclassid = ? and patternlengthbars >= ? and a.patternid & ? > ? and dftt.dayofweek = ? 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 #18
Day Hour Count Duration Avg duration Jan 21 12 674 3s100ms 4ms [ User: postgres - Total duration: 3s100ms - Times executed: 674 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s100ms - Times executed: 674 ]
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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 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 (((c.symbol ilike '%gbpjpy%' AND timegranularity <= 1440))) AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '3' > 0 AND dftt.dayofweek = '3' AND a.resultuid > '-342364881' 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: 2025-01-21 12:00:06 Duration: 21ms 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 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 (((c.symbol ilike '%euraud%' AND timegranularity <= 1440))) AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '3' > 0 AND dftt.dayofweek = '3' AND a.resultuid > '1890597887' 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: 2025-01-21 12:52:16 Duration: 10ms 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 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 (((c.symbol ilike '%usdchf%' AND timegranularity <= 1440))) AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '3' > 0 AND dftt.dayofweek = '3' AND a.resultuid > '1523339943' 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: 2025-01-21 12:32:09 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
19 0ms 35ms 3ms 24,619 1m19s 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 Jan 21 12 24,619 1m19s 3ms [ User: postgres - Total duration: 1m19s - Times executed: 24619 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m19s - Times executed: 24619 ]
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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 = 'GBPJPY' OR dss.downloadersymbol = 'GBPJPY') AND dss.enabled = 1;
Date: 2025-01-21 12:30:06 Duration: 35ms 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 = 'USDHUF' OR dss.downloadersymbol = 'USDHUF') AND dss.enabled = 1;
Date: 2025-01-21 12:15:05 Duration: 32ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 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 = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'USDSGD' OR dss.downloadersymbol = 'USDSGD') AND dss.enabled = 1;
Date: 2025-01-21 12:30:05 Duration: 31ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
20 0ms 26ms 2ms 628 1s716ms select * from powerstatslatestprfprice (?, ?);Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Jan 21 12 628 1s716ms 2ms [ User: postgres - Total duration: 1s716ms - Times executed: 628 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s679ms - Times executed: 618 ]
[ Application: [unknown] - Total duration: 36ms - Times executed: 10 ]
-
select * from PowerStatsLatestPRFPrice ('515840243872417300', '15');
Date: 2025-01-21 12:16:11 Duration: 26ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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select * from PowerStatsLatestPRFPrice ('515840243872417300', '15');
Date: 2025-01-21 12:31:11 Duration: 25ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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select * from PowerStatsLatestPRFPrice ('515840238072342300', '15');
Date: 2025-01-21 12:00:58 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 1s941ms 2,039 0ms 7ms 0ms WITH rar_max as ( ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Jan 21 12 2,039 1s941ms 0ms [ User: postgres - Total duration: 1h24m33s - Times executed: 2039 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h24m33s - Times executed: 2039 ]
-
WITH rar_max as ( ;
Date: 2025-01-21 12:43:11 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
WITH rar_max as ( ;
Date: 2025-01-21 12:01:06 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
WITH rar_max as ( ;
Date: 2025-01-21 12:45:32 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
2 1s329ms 4,062 0ms 7ms 0ms SELECT ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 12 4,062 1s329ms 0ms [ User: postgres - Total duration: 7s719ms - Times executed: 4062 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 7s625ms - Times executed: 3518 ]
[ Application: [unknown] - Total duration: 93ms - Times executed: 544 ]
-
SELECT ;
Date: 2025-01-21 12:15:04 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
SELECT ;
Date: 2025-01-21 12:15:03 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
SELECT ;
Date: 2025-01-21 12:00:03 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
3 721ms 2,209 0ms 1ms 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 #3
Day Hour Count Duration Avg duration 12 2,209 721ms 0ms [ User: postgres - Total duration: 4s817ms - Times executed: 2209 ]
[ Application: [unknown] - Total duration: 4s817ms - Times executed: 2209 ]
-
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: 2025-01-21 12:00:07 Duration: 1ms 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: 2025-01-21 12:12:08 Duration: 1ms 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: 2025-01-21 12:21:51 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
4 552ms 401 0ms 1ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 12 401 552ms 1ms [ User: postgres - Total duration: 501ms - Times executed: 401 ]
[ Application: [unknown] - Total duration: 501ms - Times executed: 401 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-01-21 12:11:19 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-01-21 12:15:35 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-01-21 12:41:24 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
5 315ms 3,154 0ms 1ms 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 12 3,154 315ms 0ms [ User: postgres - Total duration: 1s454ms - Times executed: 3154 ]
[ Application: [unknown] - Total duration: 1s454ms - Times executed: 3154 ]
-
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: 2025-01-21 12:30:56 Duration: 1ms 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: 2025-01-21 12:11:55 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: 2025-01-21 12:12:07 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
6 220ms 1,989 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 12 1,989 220ms 0ms [ User: postgres - Total duration: 591ms - Times executed: 1989 ]
[ Application: [unknown] - Total duration: 591ms - Times executed: 1989 ]
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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: 2025-01-21 12:22:46 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: 2025-01-21 12:12:42 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: 2025-01-21 12:22:48 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
7 156ms 1,106 0ms 0ms 0ms INSERT INTO T240 (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 #7
Day Hour Count Duration Avg duration 12 1,106 156ms 0ms [ User: postgres - Total duration: 546ms - Times executed: 1106 ]
[ Application: [unknown] - Total duration: 546ms - Times executed: 1106 ]
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INSERT INTO T240 (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: 2025-01-21 12:12:04 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T240 (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: 2025-01-21 12:22:01 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T240 (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: 2025-01-21 12:12:08 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
8 109ms 1,866 0ms 8ms 0ms select 1;Times Reported Time consuming prepare #8
Day Hour Count Duration Avg duration 12 1,866 109ms 0ms [ User: postgres - Total duration: 8ms - Times executed: 1866 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 8ms - Times executed: 1866 ]
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select 1;
Date: 2025-01-21 12:30:06 Duration: 8ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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select 1;
Date: 2025-01-21 12:00:04 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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select 1;
Date: 2025-01-21 12:30:03 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
9 108ms 771 0ms 1ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 12 771 108ms 0ms [ User: postgres - Total duration: 7ms - Times executed: 771 ]
[ Application: [unknown] - Total duration: 7ms - Times executed: 771 ]
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SET extra_float_digits = 3;
Date: 2025-01-21 12:00:04 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
SET extra_float_digits = 3;
Date: 2025-01-21 12:30:04 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
SET extra_float_digits = 3;
Date: 2025-01-21 12:45:05 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
10 67ms 60 0ms 3ms 1ms /*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 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 (((symbol ilike '%xauusd%' AND timegranularity <= 1440);Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 12 60 67ms 1ms [ User: postgres - Total duration: 110ms - Times executed: 60 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 110ms - Times executed: 60 ]
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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 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 (((symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2025-01-21 12:31:52 Duration: 3ms 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 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 (((symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2025-01-21 12:59:53 Duration: 3ms 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 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 (((symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2025-01-21 12:11:52 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
11 63ms 12 4ms 7ms 5ms with sym_info as ( ;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 12 12 63ms 5ms [ User: postgres - Total duration: 16s633ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 16s633ms - Times executed: 12 ]
-
with sym_info as ( ;
Date: 2025-01-21 12:36:58 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
-
with sym_info as ( ;
Date: 2025-01-21 12:51:53 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
-
with sym_info as ( ;
Date: 2025-01-21 12:06:44 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
12 60ms 61 0ms 2ms 0ms WITH last_candle AS ( ;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 12 61 60ms 0ms [ User: postgres - Total duration: 27s630ms - Times executed: 61 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 27s630ms - Times executed: 61 ]
-
WITH last_candle AS ( ;
Date: 2025-01-21 12:16:01 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
WITH last_candle AS ( ;
Date: 2025-01-21 12:12:00 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
WITH last_candle AS ( ;
Date: 2025-01-21 12:20:00 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
13 54ms 30 0ms 3ms 1ms /*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 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 (((s.symbol ilike '%gbpjpy%' AND timegranularity <= 1440);Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 12 30 54ms 1ms [ User: postgres - Total duration: 220ms - Times executed: 30 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 220ms - Times executed: 30 ]
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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 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 (((s.symbol ilike '%gbpjpy%' AND timegranularity <= 1440);
Date: 2025-01-21 12:07:54 Duration: 3ms 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 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 (((s.symbol ilike '%gbpjpy%' AND timegranularity <= 1440);
Date: 2025-01-21 12:47:55 Duration: 3ms 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 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 (((s.symbol ilike '%gbpjpy%' AND timegranularity <= 1440);
Date: 2025-01-21 12:43:55 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
14 53ms 30 0ms 3ms 1ms /*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 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 (((s.symbol ilike '%gbpaud%' AND timegranularity <= 1440);Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 12 30 53ms 1ms [ User: postgres - Total duration: 308ms - Times executed: 30 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 308ms - Times executed: 30 ]
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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 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 (((s.symbol ilike '%gbpaud%' AND timegranularity <= 1440);
Date: 2025-01-21 12:31:55 Duration: 3ms 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 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 (((s.symbol ilike '%gbpaud%' AND timegranularity <= 1440);
Date: 2025-01-21 12:11:54 Duration: 3ms 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 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 (((s.symbol ilike '%gbpaud%' AND timegranularity <= 1440);
Date: 2025-01-21 12:35:55 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
15 44ms 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 #15
Day Hour Count Duration Avg duration 12 18 44ms 2ms [ User: postgres - Total duration: 29ms - Times executed: 18 ]
[ Application: [unknown] - Total duration: 29ms - 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: 2025-01-21 12:31:00 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: 2025-01-21 12:11:00 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: 2025-01-21 12:00:03 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
16 39ms 25 0ms 2ms 1ms with wh_patitioned as ( ;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 12 25 39ms 1ms [ User: postgres - Total duration: 712ms - Times executed: 25 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 712ms - Times executed: 25 ]
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with wh_patitioned as ( ;
Date: 2025-01-21 12:20:38 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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with wh_patitioned as ( ;
Date: 2025-01-21 12:02:03 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
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with wh_patitioned as ( ;
Date: 2025-01-21 12:20:41 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
17 26ms 60 0ms 3ms 0ms /*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 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 (((s.symbol ilike '%usdmxn%' AND timegranularity <= 1440);Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 12 60 26ms 0ms [ User: postgres - Total duration: 571ms - Times executed: 60 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 571ms - Times executed: 60 ]
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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 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 (((s.symbol ilike '%usdmxn%' AND timegranularity <= 1440);
Date: 2025-01-21 12:55:52 Duration: 3ms 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 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 (((s.symbol ilike '%usdmxn%' AND timegranularity <= 1440);
Date: 2025-01-21 12:59:52 Duration: 3ms 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 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 (((s.symbol ilike '%usdmxn%' AND timegranularity <= 1440);
Date: 2025-01-21 12:27:55 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
18 21ms 60 0ms 0ms 0ms /*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 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 (((symbol ilike '%gbpchf%' AND timegranularity <= 1440);Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 12 60 21ms 0ms [ User: postgres - Total duration: 535ms - Times executed: 60 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 535ms - Times executed: 60 ]
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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 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 (((symbol ilike '%gbpchf%' AND timegranularity <= 1440);
Date: 2025-01-21 12:10:51 Duration: 0ms 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 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 (((symbol ilike '%gbpchf%' AND timegranularity <= 1440);
Date: 2025-01-21 12:50:47 Duration: 0ms 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 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 (((symbol ilike '%gbpchf%' AND timegranularity <= 1440);
Date: 2025-01-21 12:18:55 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
19 21ms 60 0ms 0ms 0ms /*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 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 (((symbol ilike '%us30%' AND timegranularity <= 1440);Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 12 60 21ms 0ms [ User: postgres - Total duration: 401ms - Times executed: 60 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 401ms - Times executed: 60 ]
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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 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 (((symbol ilike '%us30%' AND timegranularity <= 1440);
Date: 2025-01-21 12:24:53 Duration: 0ms 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 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 (((symbol ilike '%us30%' AND timegranularity <= 1440);
Date: 2025-01-21 12:32:53 Duration: 0ms 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 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 (((symbol ilike '%us30%' AND timegranularity <= 1440);
Date: 2025-01-21 12:56:54 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
20 21ms 60 0ms 0ms 0ms /*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 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 (((symbol ilike '%usdjpy%' AND timegranularity <= 1440);Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 12 60 21ms 0ms [ User: postgres - Total duration: 291ms - Times executed: 60 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 291ms - Times executed: 60 ]
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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 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 (((symbol ilike '%usdjpy%' AND timegranularity <= 1440);
Date: 2025-01-21 12:02:12 Duration: 0ms 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 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 (((symbol ilike '%usdjpy%' AND timegranularity <= 1440);
Date: 2025-01-21 12:18:14 Duration: 0ms 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 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 (((symbol ilike '%usdjpy%' AND timegranularity <= 1440);
Date: 2025-01-21 12:18:12 Duration: 0ms 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 26s421ms 55,742 0ms 24ms 0ms SELECT ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Jan 21 12 55,742 26s421ms 0ms [ User: postgres - Total duration: 2m2s - Times executed: 55742 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m1s - Times executed: 55198 ]
[ Application: [unknown] - Total duration: 93ms - Times executed: 544 ]
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SELECT ;
Date: 2025-01-21 12:00:04 Duration: 24ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '0', $3 = '0', $4 = 'EURUSD', $5 = 'EURUSD'
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SELECT ;
Date: 2025-01-21 12:30:06 Duration: 23ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '0', $3 = '0', $4 = 'USDJPY', $5 = 'USDJPY'
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SELECT ;
Date: 2025-01-21 12:15:05 Duration: 22ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '0', $3 = '0', $4 = 'EURUSD', $5 = 'EURUSD'
2 23s151ms 3,404 0ms 33ms 6ms WITH rar_max as ( ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 12 3,404 23s151ms 6ms [ User: postgres - Total duration: 1h39m26s - Times executed: 3404 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h32m5s - Times executed: 3344 ]
[ Application: [unknown] - Total duration: 7m21s - Times executed: 60 ]
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WITH rar_max as ( ;
Date: 2025-01-21 12:17:50 Duration: 33ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '538', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '125', $13 = 'ANGLO', $14 = 'BARC', $15 = 'BAY', $16 = 'BPLON', $17 = 'HSBCL', $18 = 'LLOY', $19 = 'RIO', $20 = 'RollsRoyce', $21 = 'TESCO', $22 = 'VOD', $23 = 'AUDCAD', $24 = 'AUDCHF', $25 = 'AUDJPY', $26 = 'AUDNZD', $27 = 'AUDUSD', $28 = 'CADCHF', $29 = 'CADJPY', $30 = 'CHFJPY', $31 = 'EURAUD', $32 = 'EURCAD', $33 = 'EURCHF', $34 = 'EURDKK', $35 = 'EURGBP', $36 = 'EURHUF', $37 = 'EURJPY', $38 = 'EURNOK', $39 = 'EURNZD', $40 = 'EURPLN', $41 = 'EURUSD', $42 = 'GBPAUD', $43 = 'GBPCAD', $44 = 'GBPCHF', $45 = 'GBPJPY', $46 = 'GBPNZD', $47 = 'GBPUSD', $48 = 'GBPZAR', $49 = 'NZDCAD', $50 = 'NZDCHF', $51 = 'NZDJPY', $52 = 'NZDUSD', $53 = 'USDCAD', $54 = 'USDCHF', $55 = 'USDCNH', $56 = 'USDCZK', $57 = 'USDDKK', $58 = 'USDHKD', $59 = 'USDHUF', $60 = 'USDJPY', $61 = 'USDMXN', $62 = 'USDNOK', $63 = 'USDPLN', $64 = 'USDSEK', $65 = 'USDSGD', $66 = 'USDTRY', $67 = 'USDZAR', $68 = 'XAGEUR', $69 = 'XAGUSD', $70 = 'XAUEUR', $71 = 'XAUUSD', $72 = 'ZARJPY', $73 = 'Cocoa', $74 = 'Coffee', $75 = 'Copper', $76 = 'Palladium', $77 = 'Platinum', $78 = 'Sugar', $79 = 'UKOIL', $80 = 'USOIL', $81 = 'AUS200', $82 = 'FRA40', $83 = 'JPN225', $84 = 'NETH25', $85 = 'SPA35', $86 = 'SUI20', $87 = 'UK100', $88 = 'USA100', $89 = 'USA30', $90 = 'USDIndex', $91 = 'ALCOA', $92 = 'ALIBABA', $93 = 'AMAZON', $94 = 'AMEX', $95 = 'APPLE', $96 = 'BBVA', $97 = 'BOA', $98 = 'BOEING', $99 = 'CHEVRON', $100 = 'CISCO', $101 = 'COKE', $102 = 'EBAY', $103 = 'GE', $104 = 'GOOGLE', $105 = 'GS', $106 = 'HLT', $107 = 'IBM', $108 = 'ILMN', $109 = 'INTEL', $110 = 'Iberdrola', $111 = 'MCARD', $112 = 'MCDON', $113 = 'META', $114 = 'MSFT', $115 = 'Mapfre', $116 = 'Netflix', $117 = 'PFIZER', $118 = 'QCOM', $119 = 'Santander', $120 = 'TEVA', $121 = 'Telefonica', $122 = 'Tesla', $123 = 'AUDUSD', $124 = 'EURGBP', $125 = 'EURUSD', $126 = 'GBPUSD', $127 = 'NZDUSD', $128 = 'USDCAD', $129 = 'USDCHF', $130 = 'USDJPY', $131 = 'Adidas', $132 = 'Bayer', $133 = 'Daimler', $134 = 'Danone', $135 = 'LVMH', $136 = 'Lufthansa', $137 = 'Volksw', $138 = '400', $139 = '400', $140 = 't', $141 = '10', $142 = '10'
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WITH rar_max as ( ;
Date: 2025-01-21 12:01:11 Duration: 32ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '80', $13 = 'AUDSGD', $14 = 'CHFSGD', $15 = 'EURDKK', $16 = 'EURHKD', $17 = 'EURNOK', $18 = 'EURPLN', $19 = 'EURSEK', $20 = 'EURSGD', $21 = 'EURTRY', $22 = 'EURZAR', $23 = 'GBPDKK', $24 = 'GBPNOK', $25 = 'GBPSEK', $26 = 'GBPSGD', $27 = 'NOKJPY', $28 = 'NOKSEK', $29 = 'SEKJPY', $30 = 'SGDJPY', $31 = 'USDCNH', $32 = 'USDCZK', $33 = 'USDDKK', $34 = 'USDHKD', $35 = 'USDHUF', $36 = 'USDMXN', $37 = 'USDNOK', $38 = 'USDPLN', $39 = 'USDRUB', $40 = 'USDSEK', $41 = 'USDTHB', $42 = 'USDTRY', $43 = 'USDZAR', $44 = 'AUDUSD', $45 = 'EURUSD', $46 = 'GBPUSD', $47 = 'USDCAD', $48 = 'USDCHF', $49 = 'USDJPY', $50 = 'AUDCAD', $51 = 'AUDCHF', $52 = 'AUDJPY', $53 = 'AUDNZD', $54 = 'CADCHF', $55 = 'CADJPY', $56 = 'CHFJPY', $57 = 'EURAUD', $58 = 'EURCAD', $59 = 'EURCHF', $60 = 'EURGBP', $61 = 'EURJPY', $62 = 'EURNZD', $63 = 'GBPAUD', $64 = 'GBPCAD', $65 = 'GBPCHF', $66 = 'GBPJPY', $67 = 'GBPNZD', $68 = 'NZDCAD', $69 = 'NZDCHF', $70 = 'NZDJPY', $71 = 'NZDUSD', $72 = 'USDSGD', $73 = 'AUS200', $74 = 'DE30', $75 = 'ES35', $76 = 'F40', $77 = 'HK50', $78 = 'IT40', $79 = 'JP225', $80 = 'STOXX50', $81 = 'UK100', $82 = 'US2000', $83 = 'US30', $84 = 'US500', $85 = 'CHINA50', $86 = 'USTEC', $87 = 'XAGEUR', $88 = 'XAGUSD', $89 = 'XAUUSD', $90 = 'XAUEUR', $91 = 'XPDUSD', $92 = 'XPTUSD', $93 = '400', $94 = '400', $95 = 't', $96 = '10', $97 = '10'
-
WITH rar_max as ( ;
Date: 2025-01-21 12:23:50 Duration: 31ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '538', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '125', $13 = 'ANGLO', $14 = 'BARC', $15 = 'BAY', $16 = 'BPLON', $17 = 'HSBCL', $18 = 'LLOY', $19 = 'RIO', $20 = 'RollsRoyce', $21 = 'TESCO', $22 = 'VOD', $23 = 'AUDCAD', $24 = 'AUDCHF', $25 = 'AUDJPY', $26 = 'AUDNZD', $27 = 'AUDUSD', $28 = 'CADCHF', $29 = 'CADJPY', $30 = 'CHFJPY', $31 = 'EURAUD', $32 = 'EURCAD', $33 = 'EURCHF', $34 = 'EURDKK', $35 = 'EURGBP', $36 = 'EURHUF', $37 = 'EURJPY', $38 = 'EURNOK', $39 = 'EURNZD', $40 = 'EURPLN', $41 = 'EURUSD', $42 = 'GBPAUD', $43 = 'GBPCAD', $44 = 'GBPCHF', $45 = 'GBPJPY', $46 = 'GBPNZD', $47 = 'GBPUSD', $48 = 'GBPZAR', $49 = 'NZDCAD', $50 = 'NZDCHF', $51 = 'NZDJPY', $52 = 'NZDUSD', $53 = 'USDCAD', $54 = 'USDCHF', $55 = 'USDCNH', $56 = 'USDCZK', $57 = 'USDDKK', $58 = 'USDHKD', $59 = 'USDHUF', $60 = 'USDJPY', $61 = 'USDMXN', $62 = 'USDNOK', $63 = 'USDPLN', $64 = 'USDSEK', $65 = 'USDSGD', $66 = 'USDTRY', $67 = 'USDZAR', $68 = 'XAGEUR', $69 = 'XAGUSD', $70 = 'XAUEUR', $71 = 'XAUUSD', $72 = 'ZARJPY', $73 = 'Cocoa', $74 = 'Coffee', $75 = 'Copper', $76 = 'Palladium', $77 = 'Platinum', $78 = 'Sugar', $79 = 'UKOIL', $80 = 'USOIL', $81 = 'AUS200', $82 = 'FRA40', $83 = 'JPN225', $84 = 'NETH25', $85 = 'SPA35', $86 = 'SUI20', $87 = 'UK100', $88 = 'USA100', $89 = 'USA30', $90 = 'USDIndex', $91 = 'ALCOA', $92 = 'ALIBABA', $93 = 'AMAZON', $94 = 'AMEX', $95 = 'APPLE', $96 = 'BBVA', $97 = 'BOA', $98 = 'BOEING', $99 = 'CHEVRON', $100 = 'CISCO', $101 = 'COKE', $102 = 'EBAY', $103 = 'GE', $104 = 'GOOGLE', $105 = 'GS', $106 = 'HLT', $107 = 'IBM', $108 = 'ILMN', $109 = 'INTEL', $110 = 'Iberdrola', $111 = 'MCARD', $112 = 'MCDON', $113 = 'META', $114 = 'MSFT', $115 = 'Mapfre', $116 = 'Netflix', $117 = 'PFIZER', $118 = 'QCOM', $119 = 'Santander', $120 = 'TEVA', $121 = 'Telefonica', $122 = 'Tesla', $123 = 'AUDUSD', $124 = 'EURGBP', $125 = 'EURUSD', $126 = 'GBPUSD', $127 = 'NZDUSD', $128 = 'USDCAD', $129 = 'USDCHF', $130 = 'USDJPY', $131 = 'Adidas', $132 = 'Bayer', $133 = 'Daimler', $134 = 'Danone', $135 = 'LVMH', $136 = 'Lufthansa', $137 = 'Volksw', $138 = '400', $139 = '400', $140 = 't', $141 = '10', $142 = '10'
3 1s207ms 49 0ms 48ms 24ms with wh_patitioned as ( ;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 12 49 1s207ms 24ms [ User: postgres - Total duration: 1s500ms - Times executed: 49 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s500ms - Times executed: 49 ]
-
with wh_patitioned as ( ;
Date: 2025-01-21 12:20:38 Duration: 48ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
-
with wh_patitioned as ( ;
Date: 2025-01-21 12:20:41 Duration: 48ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '529', $2 = '529', $3 = '529', $4 = '529', $5 = '529', $6 = '529', $7 = '529', $8 = '529', $9 = '529'
-
with wh_patitioned as ( ;
Date: 2025-01-21 12:38:34 Duration: 47ms 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'
4 813ms 41,120 0ms 20ms 0ms select 1;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 12 41,120 813ms 0ms [ User: postgres - Total duration: 156ms - Times executed: 41120 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 155ms - Times executed: 41040 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 80 ]
-
select 1;
Date: 2025-01-21 12:00:06 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
select 1;
Date: 2025-01-21 12:15:05 Duration: 15ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
select 1;
Date: 2025-01-21 12:30:04 Duration: 11ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
5 730ms 401 1ms 2ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 12 401 730ms 1ms [ User: postgres - Total duration: 501ms - Times executed: 401 ]
[ Application: [unknown] - Total duration: 501ms - Times executed: 401 ]
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-01-21 12:30:37 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'AXIORY'
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-01-21 12:30:45 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'AXIORY'
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-01-21 12:46:47 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'AXIORY'
6 642ms 90 4ms 12ms 7ms WITH last_candle AS ( ;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 12 90 642ms 7ms [ User: postgres - Total duration: 38s276ms - Times executed: 90 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 38s276ms - Times executed: 90 ]
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WITH last_candle AS ( ;
Date: 2025-01-21 12:16:00 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529'
-
WITH last_candle AS ( ;
Date: 2025-01-21 12:16:00 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '529', $2 = '529'
-
WITH last_candle AS ( ;
Date: 2025-01-21 12:32:00 Duration: 11ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529'
7 529ms 5,767 0ms 0ms 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 bind #7
Day Hour Count Duration Avg duration 12 5,767 529ms 0ms [ User: postgres - Total duration: 6s791ms - Times executed: 5767 ]
[ Application: [unknown] - Total duration: 6s791ms - Times executed: 5767 ]
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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: 2025-01-21 12:16:07 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-01-21 10:00:00', $2 = '35.62587', $3 = '35.62723', $4 = '35.6252', $5 = '35.62693', $6 = '249000000', $7 = '515840249643124300', $8 = '0', $9 = '2025-01-21 12:16:07.433', $10 = '2025-01-21 12:16:04.456', $11 = '35.62587', $12 = '35.62723', $13 = '35.6252', $14 = '35.62693', $15 = '249000000', $16 = '0', $17 = '2025-01-21 12:16:07.433', $18 = '2025-01-21 12:16:04.456'
-
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: 2025-01-21 12:42:20 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-01-21 12:15:00', $2 = '39097.6', $3 = '39113.8', $4 = '39090.1', $5 = '39111.3', $6 = '371', $7 = '515840245921261300', $8 = '0', $9 = '2025-01-21 12:42:20.733', $10 = '2025-01-21 12:42:20.69', $11 = '39097.6', $12 = '39113.8', $13 = '39090.1', $14 = '39111.3', $15 = '371', $16 = '0', $17 = '2025-01-21 12:42:20.733', $18 = '2025-01-21 12:42:20.69'
-
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: 2025-01-21 12:08:07 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-01-21 11:45:00', $2 = '43564.86', $3 = '43623.11', $4 = '43561.11', $5 = '43621.11', $6 = '831', $7 = '515840248000537300', $8 = '0', $9 = '2025-01-21 12:08:07.633', $10 = '2025-01-21 12:08:07.586', $11 = '43564.86', $12 = '43623.11', $13 = '43561.11', $14 = '43621.11', $15 = '831', $16 = '0', $17 = '2025-01-21 12:08:07.633', $18 = '2025-01-21 12:08:07.586'
8 494ms 60 5ms 15ms 8ms /*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 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 (((symbol ilike '%xauusd%' AND timegranularity <= 1440);Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 12 60 494ms 8ms [ User: postgres - Total duration: 110ms - Times executed: 60 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 110ms - Times executed: 60 ]
-
/*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 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 (((symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2025-01-21 12:31:52 Duration: 15ms 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 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 (((symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2025-01-21 12:43:52 Duration: 15ms 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 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 (((symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2025-01-21 12:47:52 Duration: 15ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
9 441ms 30 10ms 20ms 14ms /*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 #9
Day Hour Count Duration Avg duration 12 30 441ms 14ms [ User: postgres - Total duration: 604ms - Times executed: 30 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 604ms - Times executed: 30 ]
-
/*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: 2025-01-21 12:00:03 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '2052589783', $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: 2025-01-21 12:32:04 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '2052589783', $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: 2025-01-21 12:56:04 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '2052589783', $7 = '0'
10 429ms 30 10ms 22ms 14ms /*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 #10
Day Hour Count Duration Avg duration 12 30 429ms 14ms [ User: postgres - Total duration: 387ms - Times executed: 30 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 387ms - Times executed: 30 ]
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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: 2025-01-21 12:47:57 Duration: 22ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1767991927', $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: 2025-01-21 12:55:57 Duration: 22ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1767991927', $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: 2025-01-21 12:43:57 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1767991927', $7 = '0'
11 428ms 30 10ms 19ms 14ms /*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 #11
Day Hour Count Duration Avg duration 12 30 428ms 14ms [ User: postgres - Total duration: 280ms - Times executed: 30 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 280ms - Times executed: 30 ]
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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: 2025-01-21 12:09:32 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-146248889', $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: 2025-01-21 12:16:09 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1921912353', $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: 2025-01-21 12:12:09 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1921912353', $7 = '0'
12 424ms 60 5ms 9ms 7ms /*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 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 (((symbol ilike '%gbpchf%' AND timegranularity <= 1440);Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 12 60 424ms 7ms [ User: postgres - Total duration: 535ms - Times executed: 60 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 535ms - Times executed: 60 ]
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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 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 (((symbol ilike '%gbpchf%' AND timegranularity <= 1440);
Date: 2025-01-21 12:42:57 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 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 (((symbol ilike '%gbpchf%' AND timegranularity <= 1440);
Date: 2025-01-21 12:18:51 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 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 (((symbol ilike '%gbpchf%' AND timegranularity <= 1440);
Date: 2025-01-21 12:50:57 Duration: 9ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
13 422ms 30 10ms 18ms 14ms /*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 #13
Day Hour Count Duration Avg duration 12 30 422ms 14ms [ User: postgres - Total duration: 965ms - Times executed: 30 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 965ms - Times executed: 30 ]
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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: 2025-01-21 12:05:36 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1845008503', $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: 2025-01-21 12:17:37 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1845008503', $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: 2025-01-21 12:56:39 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-663583681', $7 = '0'
14 417ms 60 4ms 14ms 6ms /*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 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 (((s.symbol ilike '%usdmxn%' AND timegranularity <= 1440);Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 12 60 417ms 6ms [ User: postgres - Total duration: 571ms - Times executed: 60 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 571ms - Times executed: 60 ]
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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 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 (((s.symbol ilike '%usdmxn%' AND timegranularity <= 1440);
Date: 2025-01-21 12:55:52 Duration: 14ms 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 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 (((s.symbol ilike '%usdmxn%' AND timegranularity <= 1440);
Date: 2025-01-21 12:59:52 Duration: 10ms 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 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 (((s.symbol ilike '%usdmxn%' AND timegranularity <= 1440);
Date: 2025-01-21 12:47:55 Duration: 9ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
15 416ms 30 10ms 19ms 13ms /*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 #15
Day Hour Count Duration Avg duration 12 30 416ms 13ms [ User: postgres - Total duration: 705ms - Times executed: 30 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 705ms - Times executed: 30 ]
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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: 2025-01-21 12:17:35 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1339353463', $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: 2025-01-21 12:05:35 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1902307249', $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: 2025-01-21 12:24:34 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1575581463', $7 = '0'
16 416ms 30 10ms 19ms 13ms /*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 #16
Day Hour Count Duration Avg duration 12 30 416ms 13ms [ User: postgres - Total duration: 566ms - Times executed: 30 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 566ms - Times executed: 30 ]
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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: 2025-01-21 12:32:12 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-937606353', $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: 2025-01-21 12:17:34 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-2039787409', $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: 2025-01-21 12:12:11 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-937606353', $7 = '0'
17 413ms 60 5ms 11ms 6ms /*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 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 (((symbol ilike '%us30%' AND timegranularity <= 1440);Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 12 60 413ms 6ms [ User: postgres - Total duration: 401ms - Times executed: 60 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 401ms - Times executed: 60 ]
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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 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 (((symbol ilike '%us30%' AND timegranularity <= 1440);
Date: 2025-01-21 12:15:05 Duration: 11ms 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 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 (((symbol ilike '%us30%' AND timegranularity <= 1440);
Date: 2025-01-21 12:24:53 Duration: 10ms 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 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 (((symbol ilike '%us30%' AND timegranularity <= 1440);
Date: 2025-01-21 12:56:54 Duration: 9ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
18 403ms 30 10ms 31ms 13ms /*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 = $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 12 30 403ms 13ms [ User: postgres - Total duration: 3s226ms - Times executed: 30 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s226ms - Times executed: 30 ]
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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 = $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: 2025-01-21 12:30:04 Duration: 31ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '1321141607', $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 = 515852059718346308 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: 2025-01-21 12:25:09 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '763671463', $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 = 515852059718346308 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: 2025-01-21 12:41:10 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1103097681', $7 = '0'
19 399ms 60 5ms 9ms 6ms /*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 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 (((symbol ilike '%usdjpy%' AND timegranularity <= 1440);Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 12 60 399ms 6ms [ User: postgres - Total duration: 291ms - Times executed: 60 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 291ms - Times executed: 60 ]
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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 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 (((symbol ilike '%usdjpy%' AND timegranularity <= 1440);
Date: 2025-01-21 12:46:13 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 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 (((symbol ilike '%usdjpy%' AND timegranularity <= 1440);
Date: 2025-01-21 12:18:12 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 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 (((symbol ilike '%usdjpy%' AND timegranularity <= 1440);
Date: 2025-01-21 12:02:12 Duration: 9ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
20 398ms 30 10ms 19ms 13ms /*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 #20
Day Hour Count Duration Avg duration 12 30 398ms 13ms [ User: postgres - Total duration: 882ms - Times executed: 30 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 882ms - Times executed: 30 ]
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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: 2025-01-21 12:24:25 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-184602537', $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: 2025-01-21 12:56:26 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-1373153681', $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: 2025-01-21 12:05:36 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '235006607', $7 = '0'
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Events
Log levels
Key values
- 449,422 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 0 ERROR entries
- 0 WARNING entries
Errors per 5 minutes
NO DATASET
Most Frequent Errors/Events
Key values
- 0 Max number of times the same event was reported
- 0 Total events found
Rank Times reported Error NO DATASET