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Global information
- Generated on Fri May 16 09:00:15 2025
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2025-05-16_100000.log
- Parsed 2,620,804 log entries in 1m14s
- Log start from 2025-05-16 10:00:00 to 2025-05-16 10:59:59
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Overview
Global Stats
- 217 Number of unique normalized queries
- 156,388 Number of queries
- 1h50m8s Total query duration
- 2025-05-16 10:00:00 First query
- 2025-05-16 10:59:59 Last query
- 3,247 queries/s at 2025-05-16 10:45:04 Query peak
- 1h50m8s Total query duration
- 7s422ms Prepare/parse total duration
- 1m11s Bind total duration
- 1h48m50s 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
- 34 Total number of automatic vacuums
- 58 Total number of automatic analyzes
- 625 Number temporary file
- 135.59 MiB Max size of temporary file
- 5.38 MiB Average size of temporary file
- 3,717 Total number of sessions
- 31 sessions at 2025-05-16 10:41:15 Session peak
- 2d10h35m7s Total duration of sessions
- 56s741ms Average duration of sessions
- 42 Average queries per session
- 1s778ms Average queries duration per session
- 54s963ms Average idle time per session
- 3,726 Total number of connections
- 27 connections/s at 2025-05-16 10:48:48 Connection peak
- 3 Total number of databases
SQL Traffic
Key values
- 3,247 queries/s Query Peak
- 2025-05-16 10:45:04 Date
SELECT Traffic
Key values
- 3,169 queries/s Query Peak
- 2025-05-16 10:45:04 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 207 queries/s Query Peak
- 2025-05-16 10:00:56 Date
Queries duration
Key values
- 1h50m8s 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) May 16 10 156,388 0ms 36s917ms 41ms 3m 3m36s 4m23s Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) May 16 10 120,849 26 2ms 3s149ms 11s367ms 41s127ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) May 16 10 24,479 3,278 16 96 1ms 742ms 1s268ms 3s938ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare May 16 10 20,332 137,556 6.77 13.21% Day Hour Count Average / Second May 16 10 3,726 1.03/s Day Hour Count Average Duration Average idle time May 16 10 3,717 56s741ms 54s984ms -
Connections
Established Connections
Key values
- 27 connections Connection Peak
- 2025-05-16 10:48:48 Date
Connections per database
Key values
- acaweb_fx Main Database
- 3,726 connections Total
Connections per user
Key values
- postgres Main User
- 3,726 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 1562 connections
- 3,726 Total connections
Host Count 127.0.0.1 112 182.165.1.42 8 192.168.0.114 20 192.168.0.216 100 192.168.1.145 190 192.168.1.20 207 192.168.1.231 10 192.168.1.239 13 192.168.1.250 515 192.168.1.90 56 192.168.2.126 68 192.168.2.182 12 192.168.2.205 12 192.168.2.82 48 192.168.3.199 62 192.168.4.131 1 192.168.4.142 1,562 192.168.4.150 10 192.168.4.161 4 192.168.4.238 20 192.168.4.33 90 192.168.4.98 330 93.109.212.141 1 [local] 275 -
Sessions
Simultaneous sessions
Key values
- 31 sessions Session Peak
- 2025-05-16 10:41:15 Date
Histogram of session times
Key values
- 2,901 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 3,717 sessions Total
Sessions per user
Key values
- postgres Main User
- 3,717 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 3,717 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 112 7s124ms 63ms 182.165.1.42 8 38m34s 4m49s 192.168.0.114 20 1h43m20s 5m10s 192.168.0.216 100 45s474ms 454ms 192.168.1.145 190 4h16m 1m20s 192.168.1.20 207 14h13m8s 4m7s 192.168.1.239 13 130ms 10ms 192.168.1.250 515 15h21m55s 1m47s 192.168.1.90 56 38s248ms 683ms 192.168.2.126 68 7s231ms 106ms 192.168.2.182 12 1s274ms 106ms 192.168.2.205 12 470ms 39ms 192.168.2.82 48 10s719ms 223ms 192.168.3.199 62 21s861ms 352ms 192.168.4.131 1 158ms 158ms 192.168.4.142 1,562 17m41s 679ms 192.168.4.150 10 20h7m20s 2h44s 192.168.4.161 4 36ms 9ms 192.168.4.238 20 30s824ms 1s541ms 192.168.4.33 90 15s200ms 168ms 192.168.4.98 330 13s349ms 40ms 93.109.212.141 2 1h51m42s 55m51s [local] 275 2m10s 475ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 19,495 buffers Checkpoint Peak
- 2025-05-16 10:07:03 Date
- 209.845 seconds Highest write time
- 0.007 seconds Sync time
Checkpoints Wal files
Key values
- 7 files Wal files usage Peak
- 2025-05-16 10:07:03 Date
Checkpoints distance
Key values
- 240.27 Mo Distance Peak
- 2025-05-16 10:07:03 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time May 16 10 59,693 1,697.835s 0.037s 1,698.189s Day Hour Added Removed Recycled Synced files Longest sync Average sync May 16 10 0 0 26 1,857 0.005s 0s Day Hour Count Avg time (sec) May 16 10 0 0s Day Hour Mean distance Mean estimate May 16 10 36,367.42 kB 89,117.17 kB -
Temporary Files
Size of temporary files
Key values
- 125.71 MiB Temp Files size Peak
- 2025-05-16 10:10:06 Date
Number of temporary files
Key values
- 62 per second Temp Files Peak
- 2025-05-16 10:17:08 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size May 16 10 625 3.28 GiB 5.38 MiB Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 80 388.06 MiB 4.21 MiB 7.60 MiB 4.85 MiB with rar_max as ( ;-
WITH rar_max as ( ;
Date: 2025-05-16 10:00:45 Duration: 0ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown]
2 42 1.58 GiB 2.64 MiB 135.59 MiB 38.41 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: 2025-05-16 10:00:11 Duration: 8s615ms 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: 2025-05-16 10:30:10 Duration: 7s907ms 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: 2025-05-16 10:20:08 Duration: 5s503ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
3 16 367.85 MiB 22.98 MiB 22.99 MiB 22.99 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: 2025-05-16 10:41:13 Duration: 1s605ms 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: 2025-05-16 10:26:12 Duration: 1s191ms 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: 2025-05-16 10:16:13 Duration: 1s143ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
4 16 747.48 MiB 46.71 MiB 46.72 MiB 46.72 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: 2025-05-16 10:41:16 Duration: 2s980ms 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: 2025-05-16 10:16:16 Duration: 2s977ms 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: 2025-05-16 10:46:16 Duration: 2s953ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
5 4 245.44 MiB 61.28 MiB 61.45 MiB 61.36 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2025-05-16 10:32:11 Duration: 9s356ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-05-16 10:17:10 Duration: 8s692ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-05-16 10:47:11 Duration: 8s593ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
Queries generating the largest temporary files
Rank Size Query 1 135.59 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: 2025-05-16 10:00:07 ]
2 126.98 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: 2025-05-16 10:30:09 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
3 102.52 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-05-16 10:50:04 ]
4 100.26 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: 2025-05-16 10:40:04 ]
5 91.77 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: 2025-05-16 10:40:04 ]
6 81.60 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: 2025-05-16 10:20:05 ]
7 71.63 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: 2025-05-16 10:20:07 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
8 70.33 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: 2025-05-16 10:50:05 ]
9 69.82 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: 2025-05-16 10:20:04 ]
10 65.45 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: 2025-05-16 10:10:04 ]
11 61.45 MiB select updateageforrelevantresults ();[ Date: 2025-05-16 10:02:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
12 61.40 MiB select updateageforrelevantresults ();[ Date: 2025-05-16 10:32:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
13 61.31 MiB select updateageforrelevantresults ();[ Date: 2025-05-16 10:47:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
14 61.28 MiB select updateageforrelevantresults ();[ Date: 2025-05-16 10:17:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
15 57.94 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: 2025-05-16 10:00:09 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
16 55.91 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: 2025-05-16 10:10:04 ]
17 49.33 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: 2025-05-16 10:10:04 ]
18 48.27 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: 2025-05-16 10:10:05 ]
19 46.72 MiB 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: 2025-05-16 10:11:14 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
20 46.72 MiB 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: 2025-05-16 10:16:16 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
-
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)
- 58 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 16 acaweb_fx.pg_catalog.pg_attribute 6 acaweb_fx.public.datafeeds_latestrun 4 acaweb_fx.public.relevance_keylevels_results 4 acaweb_fx.pg_catalog.pg_class 4 acaweb_fx.public.relevance_fibonacci_results 4 acaweb_fx.pg_catalog.pg_type 4 acaweb_fx.public.relevance_autochartist_results 4 acaweb_fx.pg_catalog.pg_index 2 acaweb_fx.public.autochartist_symbolupdates 2 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.public.solr_imports 1 acaweb_fx.pg_catalog.pg_depend 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.relevance_consecutivecandles_results 1 acaweb_fx.public.symbollatestupdatetime 1 acaweb_fx.public.relevance_bigmovement_results 1 Total 58 Vacuums per table
Key values
- public.solr_relevance_old (16) Main table vacuumed on database acaweb_fx
- 34 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 16 16 14,409 0 63 0 0 10,501 1,324 6,042,656 acaweb_fx.public.datafeeds_latestrun 4 0 434 0 9 0 0 71 10 61,759 acaweb_fx.public.relevance_keylevels_results 2 2 8,479 0 320 2 151 2,268 294 763,012 acaweb_fx.public.relevance_autochartist_results 2 2 7,245 0 221 0 496 1,575 212 437,453 acaweb_fx.pg_catalog.pg_class 2 2 741 0 82 0 82 266 78 382,500 acaweb_fx.public.relevance_fibonacci_results 2 2 2,623 0 64 2 90 483 46 117,917 acaweb_fx.pg_toast.pg_toast_2619 1 1 137 0 34 0 0 105 29 117,656 acaweb_fx.pg_catalog.pg_type 1 1 130 0 28 0 0 55 22 111,431 acaweb_fx.public.autochartist_symbolupdates 1 1 26,705 0 363 2 36,928 7,695 286 629,841 acaweb_fx.pg_catalog.pg_attribute 1 1 788 0 180 0 64 376 149 872,163 acaweb_fx.pg_catalog.pg_depend 1 1 333 0 90 0 58 192 71 427,561 acaweb_fx.public.latest_t15_candle_view 1 1 65 0 1 0 0 6 1 9,073 Total 34 30 62,089 44,185 1,455 6 37,869 23,593 2,522 9,973,022 Tuples removed per table
Key values
- public.solr_relevance_old (79794) Main table with removed tuples on database acaweb_fx
- 92785 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 16 16 79,794 104,501 0 0 3,572 acaweb_fx.public.autochartist_symbolupdates 1 1 6,895 46,333 44 0 40,691 acaweb_fx.public.relevance_keylevels_results 2 2 1,723 23,818 0 0 558 acaweb_fx.pg_catalog.pg_attribute 1 1 1,262 9,463 0 0 242 acaweb_fx.public.relevance_autochartist_results 2 2 1,213 16,366 0 0 760 acaweb_fx.pg_catalog.pg_depend 1 1 538 12,044 8 0 114 acaweb_fx.public.relevance_fibonacci_results 2 2 498 2,780 0 0 204 acaweb_fx.pg_catalog.pg_class 2 2 315 3,899 5 0 300 acaweb_fx.public.datafeeds_latestrun 4 0 257 62 2 0 64 acaweb_fx.pg_catalog.pg_type 1 1 150 1,338 0 0 38 acaweb_fx.pg_toast.pg_toast_2619 1 1 74 171 1 0 50 acaweb_fx.public.latest_t15_candle_view 1 1 66 14 0 0 1 Total 34 30 92,785 220,789 60 0 46,594 Pages removed per table
Key values
- unknown (0) Main table with removed pages on database unknown
- 0 pages Total removed
Pages removed per tables
NO DATASET
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_toast.pg_toast_2619 1 1 74 0 acaweb_fx.pg_catalog.pg_type 1 1 150 0 acaweb_fx.public.datafeeds_latestrun 4 0 257 0 acaweb_fx.public.autochartist_symbolupdates 1 1 6895 0 acaweb_fx.pg_catalog.pg_attribute 1 1 1262 0 acaweb_fx.pg_catalog.pg_depend 1 1 538 0 acaweb_fx.public.latest_t15_candle_view 1 1 66 0 acaweb_fx.public.relevance_keylevels_results 2 2 1723 0 acaweb_fx.public.solr_relevance_old 16 16 79794 0 acaweb_fx.public.relevance_autochartist_results 2 2 1213 0 acaweb_fx.pg_catalog.pg_class 2 2 315 0 acaweb_fx.public.relevance_fibonacci_results 2 2 498 0 Total 34 30 92,785 0 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs May 16 10 34 58 - 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
- 120,849 Total read queries
- 33,084 Total write queries
Queries by database
Key values
- acaweb_fx Main database
- 155,751 Requests
- 1h48m49s (acaweb_fx)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 155,751 1h48m49s copy from 96 7s497ms copy to 26 6s257ms cte 4,506 1h42m53s ddl 16 498ms delete 16 24ms insert 24,203 28s185ms others 2,455 8s376ms select 120,548 4m46s tcl 667 195ms update 3,218 18s615ms postgres Total 1 0ms select 1 0ms socialmedia Total 636 670ms insert 276 359ms select 300 215ms update 60 96ms Queries by user
Key values
- postgres Main user
- 156,388 Requests
User Request type Count Duration postgres Total 156,388 1h48m50s copy from 96 7s497ms copy to 26 6s257ms cte 4,506 1h42m53s ddl 16 498ms delete 16 24ms insert 24,479 28s544ms others 2,455 8s376ms select 120,849 4m46s tcl 667 195ms update 3,278 18s711ms Duration by user
Key values
- 1h48m50s (postgres) Main time consuming user
User Request type Count Duration postgres Total 156,388 1h48m50s copy from 96 7s497ms copy to 26 6s257ms cte 4,506 1h42m53s ddl 16 498ms delete 16 24ms insert 24,479 28s544ms others 2,455 8s376ms select 120,849 4m46s tcl 667 195ms update 3,278 18s711ms Queries by host
Key values
- 192.168.1.20 Main host
- 50,893 Requests
- 37m48s (192.168.1.250)
- Main time consuming host
Host Request type Count Duration 127.0.0.1 Total 15,015 48s693ms copy to 26 6s257ms cte 24 304ms insert 11,530 15s241ms select 750 24s789ms update 2,685 2s101ms 182.165.1.42 Total 292 6m45s cte 80 6m44s others 8 0ms select 204 226ms 182.165.1.54 Total 785 78ms select 785 78ms 192.168.0.114 Total 7 12ms others 1 0ms select 3 9ms tcl 2 1ms update 1 0ms 192.168.0.216 Total 400 416ms others 200 26ms select 192 281ms update 8 109ms 192.168.0.23 Total 6 1ms select 6 1ms 192.168.0.239 Total 510 366ms select 510 366ms 192.168.0.42 Total 1,471 1s29ms insert 325 34ms select 1,146 994ms 192.168.1.135 Total 186 533ms cte 6 268ms select 180 264ms 192.168.1.145 Total 43,244 29m41s cte 1,011 28m25s others 380 4ms select 41,853 1m16s 192.168.1.20 Total 50,893 29m55s cte 991 28m29s others 414 4ms select 49,488 1m26s 192.168.1.201 Total 1,733 1s460ms select 1,733 1s460ms 192.168.1.23 Total 2,306 2s465ms select 2,306 2s465ms 192.168.1.231 Total 24 0ms others 21 0ms select 3 0ms 192.168.1.239 Total 52 32ms others 26 2ms select 26 29ms 192.168.1.250 Total 22,279 37m48s cte 2,271 37m32s others 1,030 11ms select 18,978 15s964ms 192.168.1.45 Total 120 243ms select 120 243ms 192.168.1.90 Total 64 36s256ms cte 6 35s814ms others 8 0ms select 50 441ms 192.168.2.126 Total 90 482ms others 18 0ms select 68 482ms tcl 4 0ms 192.168.2.182 Total 48 377ms others 24 2ms select 12 12ms update 12 362ms 192.168.2.205 Total 138 122ms insert 90 8ms others 24 2ms select 20 22ms update 4 88ms 192.168.2.82 Total 1,038 2s35ms insert 662 1s296ms others 96 10ms select 168 99ms update 112 628ms 192.168.3.199 Total 248 338ms others 124 14ms select 112 135ms update 12 188ms 192.168.4.131 Total 3 35ms cte 1 35ms others 2 0ms 192.168.4.142 Total 13,368 13s199ms insert 11,596 11s603ms select 1,772 1s595ms 192.168.4.150 Total 22 1s350ms others 21 0ms select 1 1s350ms 192.168.4.161 Total 12 1ms others 8 0ms select 4 1ms 192.168.4.238 Total 60 29s615ms cte 20 29s614ms others 40 0ms 192.168.4.33 Total 636 670ms insert 276 359ms select 300 215ms update 60 96ms 192.168.4.98 Total 996 8s951ms others 6 8s52ms select 6 26ms tcl 660 193ms update 324 678ms 93.109.212.141 Total 3 0ms select 2 0ms tcl 1 0ms [local] Total 339 2m10s copy from 96 7s497ms cte 96 35s533ms ddl 16 498ms delete 16 24ms others 4 242ms select 51 1m12s update 60 14s458ms Queries by application
Key values
- PostgreSQL JDBC Driver Main application
- 122,697 Requests
- 1h38m3s (PostgreSQL JDBC Driver)
- Main time consuming application
Application Request type Count Duration PostgreSQL JDBC Driver Total 122,697 1h38m3s cte 4,300 1h34m57s insert 325 34ms others 959 12ms select 117,113 3m6s [unknown] Total 33,237 8m29s cte 86 7m20s insert 24,154 28s509ms others 1,492 8s121ms select 3,631 28s223ms tcl 666 195ms update 3,208 4s233ms pgAdmin 4 - CONN:3608657 Total 2 0ms select 1 0ms tcl 1 0ms pgAdmin 4 - DB:postgres Total 1 0ms select 1 0ms psql Total 451 2m17s copy from 96 7s497ms copy to 26 6s257ms cte 120 35s837ms ddl 16 498ms delete 16 24ms others 4 242ms select 103 1m12s update 70 14s478ms Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2025-05-16 10:48:43 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 86,778 0-1ms duration
Slowest individual queries
Rank Duration Query 1 36s917ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-05-16 10:21:06 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
2 31s454ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-05-16 10:17:37 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
3 30s456ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-05-16 10:06:00 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
4 28s858ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-05-16 10:54:46 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
5 28s807ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-05-16 10:48:28 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
6 28s482ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-05-16 10:28:38 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
7 28s374ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-05-16 10:11:55 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
8 28s359ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-05-16 10:34:06 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
9 28s274ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-05-16 10:39:35 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
10 28s218ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-05-16 10:24:49 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
11 27s865ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-05-16 10:43:56 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
12 23s831ms 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: 2025-05-16 10:16:04 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
13 19s716ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('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 ('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: 2025-05-16 10:41:28 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
14 17s680ms 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: 2025-05-16 10:15:48 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
15 17s161ms 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: 2025-05-16 10:41:16 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
16 16s791ms 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: 2025-05-16 10:20:47 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
17 16s245ms 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: 2025-05-16 10:22:40 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
18 16s207ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('31' = 0 OR coalesce(bim.code, s.symbol) in ('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURNZD', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'JPN225', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', 'XAGUSD', 'XAUUSD')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-05-16 10:20:46 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
19 16s109ms 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: 2025-05-16 10:23:00 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
20 16s39ms 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: 2025-05-16 10:55:52 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
Time consuming queries
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 46m2s 320 362ms 23s831ms 8s633ms 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 May 16 10 320 46m2s 8s633ms [ User: postgres - Total duration: 46m2s - Times executed: 320 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 42m55s - Times executed: 308 ]
[ Application: [unknown] - Total duration: 3m6s - 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 = '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: 2025-05-16 10:16:04 Duration: 23s831ms 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 = '529' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('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 ('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: 2025-05-16 10:41:28 Duration: 19s716ms 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 ), 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: 2025-05-16 10:15:48 Duration: 17s680ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
2 38m14s 319 124ms 36s917ms 7s192ms 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 May 16 10 319 38m14s 7s192ms [ User: postgres - Total duration: 38m14s - Times executed: 319 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 36m - Times executed: 307 ]
[ Application: [unknown] - Total duration: 2m13s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-05-16 10:21:06 Duration: 36s917ms 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 ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-05-16 10:17:37 Duration: 31s454ms 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 ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-05-16 10:06:00 Duration: 30s456ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
3 13m45s 299 634ms 8s359ms 2s761ms 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 May 16 10 299 13m45s 2s761ms [ User: postgres - Total duration: 13m45s - Times executed: 299 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12m40s - Times executed: 287 ]
[ 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: 2025-05-16 10:15:10 Duration: 8s359ms 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_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: 2025-05-16 10:15:56 Duration: 7s752ms 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: 2025-05-16 10:25:53 Duration: 7s592ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
4 2m3s 186 161ms 2s85ms 663ms 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 #4
Day Hour Count Duration Avg duration May 16 10 186 2m3s 663ms [ User: postgres - Total duration: 2m3s - Times executed: 186 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m46s - Times executed: 174 ]
[ Application: [unknown] - Total duration: 16s575ms - 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: 2025-05-16 10:46:07 Duration: 2s85ms 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: 2025-05-16 10:16:12 Duration: 2s73ms 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: 2025-05-16 10:41:06 Duration: 2s68ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
5 1m57s 30,048 0ms 42ms 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 #5
Day Hour Count Duration Avg duration May 16 10 30,048 1m57s 3ms [ User: postgres - Total duration: 1m57s - Times executed: 30048 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m57s - Times executed: 30048 ]
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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 = 'GBPSEK' OR dss.downloadersymbol = 'GBPSEK') AND dss.enabled = 1;
Date: 2025-05-16 10:30:05 Duration: 42ms 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 = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'BIDU.US' OR dss.downloadersymbol = 'BIDU.US') AND dss.enabled = 1;
Date: 2025-05-16 10:30:05 Duration: 40ms 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 = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'AUS200' OR dss.downloadersymbol = 'AUS200') AND dss.enabled = 1;
Date: 2025-05-16 10:00:07 Duration: 38ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
6 56s706ms 35,412 0ms 31ms 1ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration May 16 10 35,412 56s706ms 1ms [ User: postgres - Total duration: 56s706ms - Times executed: 35412 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 56s706ms - Times executed: 35412 ]
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840216966170300';
Date: 2025-05-16 10:00:07 Duration: 31ms 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) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840248622000300';
Date: 2025-05-16 10:00:07 Duration: 26ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840249416656300';
Date: 2025-05-16 10:00:06 Duration: 26ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
7 45s926ms 131 94ms 893ms 350ms 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 May 16 10 131 45s926ms 350ms [ User: postgres - Total duration: 45s926ms - Times executed: 131 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 45s926ms - Times executed: 131 ]
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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: 2025-05-16 10:16:18 Duration: 893ms 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: 2025-05-16 10:52:14 Duration: 886ms 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: 2025-05-16 10:52:14 Duration: 884ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
8 35s814ms 6 4s429ms 8s615ms 5s969ms 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 May 16 10 6 35s814ms 5s969ms [ User: postgres - Total duration: 35s814ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 35s814ms - 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: 2025-05-16 10:00:11 Duration: 8s615ms 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: 2025-05-16 10:30:10 Duration: 7s907ms 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: 2025-05-16 10:20:08 Duration: 5s503ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
9 35s155ms 4 8s513ms 9s356ms 8s788ms select updateageforrelevantresults ();Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration May 16 10 4 35s155ms 8s788ms [ User: postgres - Total duration: 35s155ms - Times executed: 4 ]
[ Application: psql - Total duration: 35s155ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-05-16 10:32:11 Duration: 9s356ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-05-16 10:17:10 Duration: 8s692ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-05-16 10:47:11 Duration: 8s593ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
10 33s165ms 16 1s758ms 2s980ms 2s72ms 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 May 16 10 16 33s165ms 2s72ms [ User: postgres - Total duration: 33s165ms - Times executed: 16 ]
[ Application: psql - Total duration: 33s165ms - 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: 2025-05-16 10:41:16 Duration: 2s980ms 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: 2025-05-16 10:16:16 Duration: 2s977ms 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: 2025-05-16 10:46:16 Duration: 2s953ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 29s614ms 20 1s283ms 2s170ms 1s480ms 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 = ? limit ? ) 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 May 16 10 20 29s614ms 1s480ms [ User: postgres - Total duration: 29s614ms - Times executed: 20 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 29s614ms - Times executed: 20 ]
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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' limit 1) 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: 2025-05-16 10:17:39 Duration: 2s170ms 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' limit 1) 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: 2025-05-16 10:37:11 Duration: 1s883ms 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' limit 1) 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: 2025-05-16 10:17:33 Duration: 1s818ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
12 28s764ms 34 12ms 10s574ms 846ms select fixcandlegaps (?, false);Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration May 16 10 34 28s764ms 846ms [ User: postgres - Total duration: 28s764ms - Times executed: 34 ]
[ Application: psql - Total duration: 28s764ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-05-16 10:06:30 Duration: 10s574ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-05-16 10:06:08 Duration: 3s609ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('AXIORY', false);
Date: 2025-05-16 10:06:11 Duration: 2s710ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
13 16s590ms 186 9ms 294ms 89ms 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 #13
Day Hour Count Duration Avg duration May 16 10 186 16s590ms 89ms [ User: postgres - Total duration: 16s590ms - Times executed: 186 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14s121ms - Times executed: 174 ]
[ Application: [unknown] - Total duration: 2s468ms - 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: 2025-05-16 10:16:12 Duration: 294ms 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: 2025-05-16 10:46:07 Duration: 294ms 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: 2025-05-16 10:26:13 Duration: 294ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
14 15s723ms 211 15ms 281ms 74ms 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 #14
Day Hour Count Duration Avg duration May 16 10 211 15s723ms 74ms [ User: postgres - Total duration: 15s723ms - Times executed: 211 ]
[ Application: [unknown] - Total duration: 15s723ms - Times executed: 211 ]
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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 'ICMARKETS-AU-MT5 - 4';
Date: 2025-05-16 10:15:49 Duration: 281ms 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 'GLOBALGTMT5 - 1';
Date: 2025-05-16 10:45:12 Duration: 254ms 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 'ICMARKETS - 1';
Date: 2025-05-16 10:46:00 Duration: 249ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
15 14s23ms 16 665ms 1s605ms 876ms 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 May 16 10 16 14s23ms 876ms [ User: postgres - Total duration: 14s23ms - Times executed: 16 ]
[ Application: psql - Total duration: 14s23ms - Times executed: 16 ]
-
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: 2025-05-16 10:41:13 Duration: 1s605ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
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: 2025-05-16 10:26:12 Duration: 1s191ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
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: 2025-05-16 10:16:13 Duration: 1s143ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
16 9s134ms 6,037 0ms 14ms 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 #16
Day Hour Count Duration Avg duration May 16 10 6,037 9s134ms 1ms [ User: postgres - Total duration: 9s134ms - Times executed: 6037 ]
[ Application: [unknown] - Total duration: 9s134ms - Times executed: 6037 ]
-
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 ('515840243946342300-1|45791.9583|45792.8542|45792.4167|45793.3854|6.6813|6.677|6.6429|6.6475', 515840243946342300, 6.000000000000000000000000000000, 'Triangle', 4, '2025-05-16 08:12:06'::timestamp without time zone, 1, 0.649512326283409491200000000000, - 1.000000000000000000000000000000, 0.946234322059085530800000000000, 0.315728046181709964800000000000, 0.656221569476079791200000000000, 6.670352670790129501000000000000, 6.688192409896310586000000000000, '2025-05-16 11:00:00'::timestamp without time zone, '2025-05-17 05:00:00'::timestamp without time zone, '2025-05-14 12:45:00'::timestamp without time zone, '2025-05-16 11:00:00'::timestamp without time zone, 6.619640000000000412000000000000, 6.658109999999999750000000000000, '2025-05-14 23:00:00'::timestamp without time zone, '2025-05-15 20:30:00'::timestamp without time zone, '2025-05-15 10:00:00'::timestamp without time zone, '2025-05-16 09:15:00'::timestamp without time zone, 6.681309999999999860000000000000, 6.677010000000000112000000000000, 6.642890000000000406000000000000, 6.647479999999999834000000000000, 0.000049354838709671268740000000, - 0.000049999999999997075050000000, 2.970314232756568362000000000000, 0.663335283192593161400000000000, 'Continuation', 0.000000000000000000000000000000, '2025-05-16 11:00:00'::timestamp without time zone, 6.657610000000000028000000000000, 144, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-05-16 10:16:16 Duration: 14ms 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 ('515840249553904300-1|45791.4167|45792.5625|45791.6042|45792.6458|1152.9|1187.802|1130|1173.175', 515840249553904300, 2.000000000000000000000000000000, 'Rising Wedge', 4, '2025-05-16 08:27:11'::timestamp without time zone, 1, 0.222682291747050592500000000000, - 1.000000000000000000000000000000, 0.492930510396844212600000000000, 0.791238818622722828200000000000, 0.937538207091598629900000000000, 1188.184946746157493000000000000000, 1195.499872190777978000000000000000, '2025-05-16 04:00:00'::timestamp without time zone, '2025-05-17 01:00:00'::timestamp without time zone, '2025-05-14 09:30:00'::timestamp without time zone, '2025-05-16 04:00:00'::timestamp without time zone, 1128.400000000000091000000000000000, 1182.960000000000036000000000000000, '2025-05-14 10:00:00'::timestamp without time zone, '2025-05-15 13:30:00'::timestamp without time zone, '2025-05-14 14:30:00'::timestamp without time zone, '2025-05-15 15:30:00'::timestamp without time zone, 1152.900000000000091000000000000000, 1187.801999999999907000000000000000, 1130.000000000000000000000000000000, 1173.174999999999954000000000000000, 1.199305555555554292000000000000, 0.758739130434778585800000000000, 1.839341694455744802000000000000, 0.456327226738642122200000000000, 'Continuation', 0.000000000000000000000000000000, '2025-05-16 04:00:00'::timestamp without time zone, 1182.960000000000036000000000000000, 56, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-05-16 10:31:22 Duration: 13ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('515840249509938300-1|45783.6667|45786.6667|45785.6667|45792.6667|38.6798|38.7803|37.3853|38.5793', 515840249509938300, 2.000000000000000000000000000000, 'Rising Wedge', 4, '2025-05-16 07:57:07'::timestamp without time zone, 1, 0.026996330205657351200000000000, - 1.000000000000000000000000000000, 0.808434546571298318100000000000, 1.000000000000000000000000000000, 0.509253369415535339600000000000, 38.945244085194268280000000000000, 39.107215804466257220000000000000, '2025-05-16 00:00:00'::timestamp without time zone, '2025-05-20 16:00:00'::timestamp without time zone, '2025-05-01 00:00:00'::timestamp without time zone, '2025-05-16 00:00:00'::timestamp without time zone, 38.403249999999999890000000000000, 38.861539999999997980000000000000, '2025-05-06 16:00:00'::timestamp without time zone, '2025-05-09 16:00:00'::timestamp without time zone, '2025-05-08 16:00:00'::timestamp without time zone, '2025-05-15 16:00:00'::timestamp without time zone, 38.679800000000000180000000000000, 38.780299999999996880000000000000, 37.385320000000000110000000000000, 38.579320000000002720000000000000, 0.038516129032258150660000000000, 0.005583333333333150364000000000, 1.217655863720744414000000000000, 0.178749899873730910800000000000, 'Continuation', 0.000000000000000000000000000000, '2025-05-16 00:00:00'::timestamp without time zone, 38.829549999999997570000000000000, 45, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-05-16 10:01:17 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
17 8s882ms 211 16ms 236ms 42ms select distinct a.symbolid, p.resultuid, case when a.breakout >= ? then ? else ? end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient from relevance_autochartist_results p inner join autochartist_results a on p.resultuid = a.resultuid inner join autochartist_stocklist asl on a.symbolid = asl.symbolid where asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration May 16 10 211 8s882ms 42ms [ User: postgres - Total duration: 8s882ms - Times executed: 211 ]
[ Application: [unknown] - Total duration: 8s882ms - Times executed: 211 ]
-
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 'GLOBALGTMT5 - 1';
Date: 2025-05-16 10:30:05 Duration: 236ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
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 'ICMARKETS - 1';
Date: 2025-05-16 10:46:00 Duration: 183ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
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 'ICMARKETS - 1';
Date: 2025-05-16 10:15:41 Duration: 173ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
18 8s235ms 5,975 0ms 34ms 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 #18
Day Hour Count Duration Avg duration May 16 10 5,975 8s235ms 1ms [ User: postgres - Total duration: 8s235ms - Times executed: 5975 ]
[ Application: [unknown] - Total duration: 8s235ms - Times executed: 5975 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-05-16 11:15:00', '958.03', '958.43', '956.35', '957.6', '139', '515840217484740300', '0', '2025-05-16 10:30:05.477', '2025-05-16 10:30:05.329') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '958.03', high = '958.43', low = '956.35', close = '957.6', volume = '139', bsf = '0', sastdatetimewritten = '2025-05-16 10:30:05.477', sastdatetimereceived = '2025-05-16 10:30:05.329';
Date: 2025-05-16 10:30:05 Duration: 34ms 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 ('2025-05-16 10:45:00', '22.22045', '22.2273', '22.21405', '22.2231', '1076', '605679104092484300', '0', '2025-05-16 10:00:07.201', '2025-05-16 10:00:06.985') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '22.22045', high = '22.2273', low = '22.21405', close = '22.2231', volume = '1076', bsf = '0', sastdatetimewritten = '2025-05-16 10:00:07.201', sastdatetimereceived = '2025-05-16 10:00:06.985';
Date: 2025-05-16 10:00:07 Duration: 26ms 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 ('2025-05-16 10:45:00', '3215.05', '3215.05', '3207.06', '3207.67', '3044', '515840243163260300', '0', '2025-05-16 10:00:05.908', '2025-05-16 10:00:05.809') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '3215.05', high = '3215.05', low = '3207.06', close = '3207.67', volume = '3044', bsf = '0', sastdatetimewritten = '2025-05-16 10:00:05.908', sastdatetimereceived = '2025-05-16 10:00:05.809';
Date: 2025-05-16 10:00:05 Duration: 24ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
19 8s52ms 6 1s46ms 1s767ms 1s342ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration May 16 10 6 8s52ms 1s342ms [ User: postgres - Total duration: 8s52ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 8s52ms - Times executed: 6 ]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-05-16 10:16:16 Duration: 1s767ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-05-16 10:46:18 Duration: 1s746ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-05-16 10:31:17 Duration: 1s345ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
20 6s860ms 80 0ms 479ms 85ms copy solr_relevance_old (uuid, relevant, age, result_uid) from stdin with ( format csv, header);Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration May 16 10 80 6s860ms 85ms [ User: postgres - Total duration: 6s860ms - Times executed: 80 ]
[ Application: psql - Total duration: 6s860ms - Times executed: 80 ]
-
COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2025-05-16 10:18:12 Duration: 479ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2025-05-16 10:11:15 Duration: 464ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2025-05-16 10:56:13 Duration: 379ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 45,832 234ms 0ms 20ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration May 16 10 45,832 234ms 0ms [ User: postgres - Total duration: 234ms - Times executed: 45832 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 221ms - Times executed: 45542 ]
[ Application: [unknown] - Total duration: 12ms - Times executed: 290 ]
-
select 1;
Date: 2025-05-16 10:45:05 Duration: 20ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-05-16 10:00:04 Duration: 11ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-05-16 10:45:05 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
2 35,412 56s706ms 0ms 31ms 1ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration May 16 10 35,412 56s706ms 1ms [ User: postgres - Total duration: 56s706ms - Times executed: 35412 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 56s706ms - Times executed: 35412 ]
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840216966170300';
Date: 2025-05-16 10:00:07 Duration: 31ms 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) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840248622000300';
Date: 2025-05-16 10:00:07 Duration: 26ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840249416656300';
Date: 2025-05-16 10:00:06 Duration: 26ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
3 30,048 1m57s 0ms 42ms 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 May 16 10 30,048 1m57s 3ms [ User: postgres - Total duration: 1m57s - Times executed: 30048 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m57s - Times executed: 30048 ]
-
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 = 'GBPSEK' OR dss.downloadersymbol = 'GBPSEK') AND dss.enabled = 1;
Date: 2025-05-16 10:30:05 Duration: 42ms 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 = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'BIDU.US' OR dss.downloadersymbol = 'BIDU.US') AND dss.enabled = 1;
Date: 2025-05-16 10:30:05 Duration: 40ms 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 = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'AUS200' OR dss.downloadersymbol = 'AUS200') AND dss.enabled = 1;
Date: 2025-05-16 10:00:07 Duration: 38ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
4 6,037 9s134ms 0ms 14ms 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 #4
Day Hour Count Duration Avg duration May 16 10 6,037 9s134ms 1ms [ User: postgres - Total duration: 9s134ms - Times executed: 6037 ]
[ Application: [unknown] - Total duration: 9s134ms - Times executed: 6037 ]
-
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 ('515840243946342300-1|45791.9583|45792.8542|45792.4167|45793.3854|6.6813|6.677|6.6429|6.6475', 515840243946342300, 6.000000000000000000000000000000, 'Triangle', 4, '2025-05-16 08:12:06'::timestamp without time zone, 1, 0.649512326283409491200000000000, - 1.000000000000000000000000000000, 0.946234322059085530800000000000, 0.315728046181709964800000000000, 0.656221569476079791200000000000, 6.670352670790129501000000000000, 6.688192409896310586000000000000, '2025-05-16 11:00:00'::timestamp without time zone, '2025-05-17 05:00:00'::timestamp without time zone, '2025-05-14 12:45:00'::timestamp without time zone, '2025-05-16 11:00:00'::timestamp without time zone, 6.619640000000000412000000000000, 6.658109999999999750000000000000, '2025-05-14 23:00:00'::timestamp without time zone, '2025-05-15 20:30:00'::timestamp without time zone, '2025-05-15 10:00:00'::timestamp without time zone, '2025-05-16 09:15:00'::timestamp without time zone, 6.681309999999999860000000000000, 6.677010000000000112000000000000, 6.642890000000000406000000000000, 6.647479999999999834000000000000, 0.000049354838709671268740000000, - 0.000049999999999997075050000000, 2.970314232756568362000000000000, 0.663335283192593161400000000000, 'Continuation', 0.000000000000000000000000000000, '2025-05-16 11:00:00'::timestamp without time zone, 6.657610000000000028000000000000, 144, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-05-16 10:16:16 Duration: 14ms 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 ('515840249553904300-1|45791.4167|45792.5625|45791.6042|45792.6458|1152.9|1187.802|1130|1173.175', 515840249553904300, 2.000000000000000000000000000000, 'Rising Wedge', 4, '2025-05-16 08:27:11'::timestamp without time zone, 1, 0.222682291747050592500000000000, - 1.000000000000000000000000000000, 0.492930510396844212600000000000, 0.791238818622722828200000000000, 0.937538207091598629900000000000, 1188.184946746157493000000000000000, 1195.499872190777978000000000000000, '2025-05-16 04:00:00'::timestamp without time zone, '2025-05-17 01:00:00'::timestamp without time zone, '2025-05-14 09:30:00'::timestamp without time zone, '2025-05-16 04:00:00'::timestamp without time zone, 1128.400000000000091000000000000000, 1182.960000000000036000000000000000, '2025-05-14 10:00:00'::timestamp without time zone, '2025-05-15 13:30:00'::timestamp without time zone, '2025-05-14 14:30:00'::timestamp without time zone, '2025-05-15 15:30:00'::timestamp without time zone, 1152.900000000000091000000000000000, 1187.801999999999907000000000000000, 1130.000000000000000000000000000000, 1173.174999999999954000000000000000, 1.199305555555554292000000000000, 0.758739130434778585800000000000, 1.839341694455744802000000000000, 0.456327226738642122200000000000, 'Continuation', 0.000000000000000000000000000000, '2025-05-16 04:00:00'::timestamp without time zone, 1182.960000000000036000000000000000, 56, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-05-16 10:31:22 Duration: 13ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('515840249509938300-1|45783.6667|45786.6667|45785.6667|45792.6667|38.6798|38.7803|37.3853|38.5793', 515840249509938300, 2.000000000000000000000000000000, 'Rising Wedge', 4, '2025-05-16 07:57:07'::timestamp without time zone, 1, 0.026996330205657351200000000000, - 1.000000000000000000000000000000, 0.808434546571298318100000000000, 1.000000000000000000000000000000, 0.509253369415535339600000000000, 38.945244085194268280000000000000, 39.107215804466257220000000000000, '2025-05-16 00:00:00'::timestamp without time zone, '2025-05-20 16:00:00'::timestamp without time zone, '2025-05-01 00:00:00'::timestamp without time zone, '2025-05-16 00:00:00'::timestamp without time zone, 38.403249999999999890000000000000, 38.861539999999997980000000000000, '2025-05-06 16:00:00'::timestamp without time zone, '2025-05-09 16:00:00'::timestamp without time zone, '2025-05-08 16:00:00'::timestamp without time zone, '2025-05-15 16:00:00'::timestamp without time zone, 38.679800000000000180000000000000, 38.780299999999996880000000000000, 37.385320000000000110000000000000, 38.579320000000002720000000000000, 0.038516129032258150660000000000, 0.005583333333333150364000000000, 1.217655863720744414000000000000, 0.178749899873730910800000000000, 'Continuation', 0.000000000000000000000000000000, '2025-05-16 00:00:00'::timestamp without time zone, 38.829549999999997570000000000000, 45, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-05-16 10:01:17 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
5 5,975 8s235ms 0ms 34ms 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 #5
Day Hour Count Duration Avg duration May 16 10 5,975 8s235ms 1ms [ User: postgres - Total duration: 8s235ms - Times executed: 5975 ]
[ Application: [unknown] - Total duration: 8s235ms - Times executed: 5975 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-05-16 11:15:00', '958.03', '958.43', '956.35', '957.6', '139', '515840217484740300', '0', '2025-05-16 10:30:05.477', '2025-05-16 10:30:05.329') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '958.03', high = '958.43', low = '956.35', close = '957.6', volume = '139', bsf = '0', sastdatetimewritten = '2025-05-16 10:30:05.477', sastdatetimereceived = '2025-05-16 10:30:05.329';
Date: 2025-05-16 10:30:05 Duration: 34ms 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 ('2025-05-16 10:45:00', '22.22045', '22.2273', '22.21405', '22.2231', '1076', '605679104092484300', '0', '2025-05-16 10:00:07.201', '2025-05-16 10:00:06.985') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '22.22045', high = '22.2273', low = '22.21405', close = '22.2231', volume = '1076', bsf = '0', sastdatetimewritten = '2025-05-16 10:00:07.201', sastdatetimereceived = '2025-05-16 10:00:06.985';
Date: 2025-05-16 10:00:07 Duration: 26ms 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 ('2025-05-16 10:45:00', '3215.05', '3215.05', '3207.06', '3207.67', '3044', '515840243163260300', '0', '2025-05-16 10:00:05.908', '2025-05-16 10:00:05.809') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '3215.05', high = '3215.05', low = '3207.06', close = '3207.67', volume = '3044', bsf = '0', sastdatetimewritten = '2025-05-16 10:00:05.908', sastdatetimereceived = '2025-05-16 10:00:05.809';
Date: 2025-05-16 10:00:05 Duration: 24ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
6 3,390 4s896ms 0ms 12ms 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 #6
Day Hour Count Duration Avg duration May 16 10 3,390 4s896ms 1ms [ User: postgres - Total duration: 4s896ms - Times executed: 3390 ]
[ Application: [unknown] - Total duration: 4s896ms - Times executed: 3390 ]
-
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 (10.000000000000000000000000000000, - 1, 1, '2025-05-16 08:11:39'::timestamp without time zone, '2025-05-16 11:00:00', 0.000907499999999998151900000000, 5, 280, 0.935719999999999996200000000000, '2025-05-16 09:00:00', '2025-05-16 00:45:00', '2025-05-15 20:45:00', '2025-05-13 13:45:00', '2025-05-13 13:00:00', '', '', '', '', '', 816, 0.936154750000000035500000000000, '2025-05-16 11:00:00'::timestamp without time zone, '2025-05-16 11:00:00', 0.935374999999999956500000000000, 0.000447749999999996978600000000, 1, 515840230469314300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840230469314300|0.93572|1|2025-05-16 11:00:00|2025-05-16 11:00:00|1|-1', 0.934467649999999983000000000000, 0.001252350000000013175000000000, 2, '2025-05-13 13:00:00', 0.933570000000000010900000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-05-16 10:15:50 Duration: 12ms 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 (3.000000000000000000000000000000, - 1, 1, '2025-05-16 08:11:42'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 105, 149.754400000000004000000000000000, '2025-05-15 17:45:00', '2025-05-15 15:45:00', '2025-05-13 14:00:00', '', '', '', '', '', '', '', 210, 149.936120000000016700000000000000, '2025-05-15 18:00:00'::timestamp without time zone, '2025-05-15 18:00:00', 0.000000000000000000000000000000, 0.181719999999999992600000000000, - 1, 515840249516467300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249516467300|149.7544|1|2025-05-15 18:00:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-05-13 14:00:00', 149.754400000000004000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-05-16 10:15:53 Duration: 12ms 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, '2025-05-16 08:11:40'::timestamp without time zone, '', 0.500000000000000000000000000000, 4, 35, 1.111595000000000111000000000000, '2025-05-16 11:00:00', '2025-05-16 09:45:00', '2025-05-16 07:45:00', '2025-05-16 02:15:00', '', '', '', '', '', '', 87, 1.111723500000000087000000000000, '2025-05-16 11:00:00'::timestamp without time zone, '2025-05-16 11:00:00', 0.000000000000000000000000000000, 0.000172250000000007141300000000, - 1, 605679104889708300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|605679104889708300|1.111595|1|2025-05-16 11:00:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-05-16 02:15:00', 1.111595000000000111000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-05-16 10:15:51 Duration: 11ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
7 3,388 2s142ms 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 #7
Day Hour Count Duration Avg duration May 16 10 3,388 2s142ms 0ms [ User: postgres - Total duration: 2s142ms - Times executed: 3388 ]
[ Application: [unknown] - Total duration: 2s142ms - Times executed: 3388 ]
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-05-16 11:00:00', '3.78583', '3.78743', '3.78224', '3.78313', '1801', '515840247873808300', '0', '2025-05-16 10:31:00.285', '2025-05-16 10:31:00.223') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '3.78583', high = '3.78743', low = '3.78224', close = '3.78313', volume = '1801', bsf = '0', sastdatetimewritten = '2025-05-16 10:31:00.285', sastdatetimereceived = '2025-05-16 10:31:00.223';
Date: 2025-05-16 10:31:00 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 ('2025-05-16 11:00:00', '35.28', '35.5', '35.17', '35.42', '155', '515840247893477300', '0', '2025-05-16 10:31:02.444', '2025-05-16 10:31:02.309') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '35.28', high = '35.5', low = '35.17', close = '35.42', volume = '155', bsf = '0', sastdatetimewritten = '2025-05-16 10:31:02.444', sastdatetimereceived = '2025-05-16 10:31:02.309';
Date: 2025-05-16 10:31:02 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 ('2025-05-16 10:30:00', '0.53584', '0.53584', '0.53531', '0.53552', '2314', '515840247868761300', '0', '2025-05-16 10:00:41.561', '2025-05-16 10:00:41.52') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.53584', high = '0.53584', low = '0.53531', close = '0.53552', volume = '2314', bsf = '0', sastdatetimewritten = '2025-05-16 10:00:41.561', sastdatetimereceived = '2025-05-16 10:00:41.52';
Date: 2025-05-16 10:00:41 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
8 2,675 2s80ms 0ms 5ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration May 16 10 2,675 2s80ms 0ms [ User: postgres - Total duration: 2s80ms - Times executed: 2675 ]
[ Application: [unknown] - Total duration: 2s80ms - Times executed: 2675 ]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-05-15 16:00:00', reason = 'Approaching pattern wick broke through price level.' WHERE uniqueIndex = '|515840249530451300|58.95|1|2025-05-15 15:45:00|-1|-1' and relevant = 1;
Date: 2025-05-16 10:15:53 Duration: 5ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-05-15 19:30:00', reason = 'Emerging pattern broke out in the wrong direction.' WHERE uniqueIndex = '515840249538233300-1|45792.5208|45792.7708|45792.3333|45792.5625|208.4|206.28|205.9|205.42' and relevant = 1;
Date: 2025-05-16 10:16:00 Duration: 4ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-05-16 11:15:00', reason = 'Emerging pattern broke out in the wrong direction.' WHERE uniqueIndex = '500991628210504200-1|45793.2083|45793.4271|45792.9896|45793.3229|1.9088|1.8975|1.9019|1.8956' and relevant = 1;
Date: 2025-05-16 10:31:07 Duration: 4ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
9 2,195 1s158ms 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 #9
Day Hour Count Duration Avg duration May 16 10 2,195 1s158ms 0ms [ User: postgres - Total duration: 1s158ms - Times executed: 2195 ]
[ Application: [unknown] - Total duration: 1s158ms - Times executed: 2195 ]
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-05-16 10:00:00', '1.33235', '1.33281', '1.33117', '1.33137', '4551', '515840247885064300', '0', '2025-05-16 10:00:52.421', '2025-05-16 10:00:52.26') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '1.33235', high = '1.33281', low = '1.33117', close = '1.33137', volume = '4551', bsf = '0', sastdatetimewritten = '2025-05-16 10:00:52.421', sastdatetimereceived = '2025-05-16 10:00:52.26';
Date: 2025-05-16 10:00:52 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-05-16 10:00:00', '0.53567', '0.53596', '0.53531', '0.53552', '4184', '515840247868983300', '0', '2025-05-16 10:00:41.961', '2025-05-16 10:00:41.823') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.53567', high = '0.53596', low = '0.53531', close = '0.53552', volume = '4184', bsf = '0', sastdatetimewritten = '2025-05-16 10:00:41.961', sastdatetimereceived = '2025-05-16 10:00:41.823';
Date: 2025-05-16 10:00:41 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 ('2025-05-16 10:00:00', '42314.45', '42397.95', '42307.05', '42396.45', '2468', '515840248000890300', '0', '2025-05-16 10:10:58.303', '2025-05-16 10:10:58.268') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '42314.45', high = '42397.95', low = '42307.05', close = '42396.45', volume = '2468', bsf = '0', sastdatetimewritten = '2025-05-16 10:10:58.303', sastdatetimereceived = '2025-05-16 10:10:58.268';
Date: 2025-05-16 10:10:58 Duration: 6ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
10 2,038 1s33ms 0ms 8ms 0ms insert into fibonacci_results (bandwidth, pattern, gmttimefound, direction, patternstarttime, patternendtime, patternstartprice, patternendprice, qtytp, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, patternlengthbars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) values (?.?, ?, ?::timestamp without time zone, ?, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?, ?, ?, ?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration May 16 10 2,038 1s33ms 0ms [ User: postgres - Total duration: 1s33ms - Times executed: 2038 ]
[ Application: [unknown] - Total duration: 1s33ms - Times executed: 2038 ]
-
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, '3 Drive', '2025-05-16 08:27:19'::timestamp without time zone, 1, '2024-12-23 00:00:00'::timestamp without time zone, '2025-05-15 00:00:00'::timestamp without time zone, 88.909999999999996590000000000000, - 1.000000000000000000000000000000, 5, 88.909999999999996590000000000000, '2024-12-23 00:00:00'::timestamp without time zone, 105.799999999999997200000000000000, '2025-02-14 00:00:00'::timestamp without time zone, 77.560000000000002280000000000000, '2025-04-07 00:00:00'::timestamp without time zone, 100.420000000000001710000000000000, '2025-05-15 00:00:00'::timestamp without time zone, 63.431743018318002220000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.779264599977719241200000000000, - 1.000000000000000000000000000000, 15.204815993140318400000000000000, 124, 100.420000000000001710000000000000, 86.291743015767551130000000000000, 123.279999997449550600000000000000, 92.510112206887768590000000000000, 110.481532699773069300000000000000, 81.925871509159009060000000000000, 77.560000002550452790000000000000, 515840249520555300, 0.441470800044561573200000000000, 'AB=1.618*XA (1.672) BC=0.786*AB (0.809) ', 0, '3 Drive|1|2024-12-23 00:00:00|88.91|-1|5|124|AB=1.618*XA (1.672)","BC=0.786*AB (0.809)|0|515840249520555300|2024-12-23 00:00:00|2025-02-14 00:00:00|2025-04-07 00:00:00|2025-05-15 00:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-05-16 10:31:29 Duration: 8ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (3.000000000000000000000000000000, 'ABCD', '2025-05-16 07:57:03'::timestamp without time zone, 1, '2025-05-07 10:00:00'::timestamp without time zone, '2025-05-16 10:00:00'::timestamp without time zone, 15.490000000000000210000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 15.710000000000000850000000000000, '2025-05-07 18:00:00'::timestamp without time zone, 14.490000000000000210000000000000, '2025-05-14 10:00:00'::timestamp without time zone, 15.250000000000000000000000000000, '2025-05-15 16:00:00'::timestamp without time zone, 14.029999999999999360000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.889917303979803842000000000000, - 1.000000000000000000000000000000, 159.454678766748259000000000000000, 89, 15.250000000000000000000000000000, 14.784001466214000690000000000000, 16.004001466213999550000000000000, 14.989104680916000230000000000000, 15.581863972389999870000000000000, 14.640000000000000570000000000000, 14.495998533786000450000000000000, 515840246011905300, 0.220165392040392315900000000000, 'BC=0.618*AB (0.623) ', 0, 'ABCD|1|2025-05-07 10:00:00|15.49|-1|4|89|BC=0.618*AB (0.623)|0|515840246011905300|1899-12-29 00:00:00|2025-05-07 18:00:00|2025-05-14 10:00:00|2025-05-15 16:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-05-16 10:01:13 Duration: 7ms 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 (2.000000000000000000000000000000, 'ABCD', '2025-05-16 07:57:01'::timestamp without time zone, 1, '2025-05-15 11:30:00'::timestamp without time zone, '2025-05-16 10:45:00'::timestamp without time zone, 77.689999999999997720000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 78.430000000000006820000000000000, '2025-05-15 12:15:00'::timestamp without time zone, 77.030000000000001140000000000000, '2025-05-15 16:30:00'::timestamp without time zone, 78.090000000000003410000000000000, '2025-05-16 10:15:00'::timestamp without time zone, 76.689999999999997720000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.786334538236154623200000000000, - 1.000000000000000000000000000000, 28.130473222249595010000000000000, 43, 78.090000000000003410000000000000, 77.555247584179994640000000000000, 78.955247584180000330000000000000, 77.790611928920000650000000000000, 78.470827509300008280000000000000, 77.390000000000000570000000000000, 77.224752415820006490000000000000, 515840246004393300, 0.427330923527690864600000000000, 'BC=0.786*AB (0.757) ', 0, 'ABCD|1|2025-05-15 11:30:00|77.69|-1|4|43|BC=0.786*AB (0.757)|0|515840246004393300|1899-12-29 00:00:00|2025-05-15 12:15:00|2025-05-15 16:30:00|2025-05-16 10:15:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-05-16 10:01:11 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
11 1,436 735ms 0ms 6ms 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 #11
Day Hour Count Duration Avg duration May 16 10 1,436 735ms 0ms [ User: postgres - Total duration: 735ms - Times executed: 1436 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 728ms - Times executed: 1430 ]
[ Application: [unknown] - Total duration: 6ms - Times executed: 6 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '606125363483575303' 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 = '606125363483575303' OR a.resultuid = '606125363483575303') AND dtt.dayofweek = 3;
Date: 2025-05-16 10:52:10 Duration: 6ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '606125247646021303' 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 = '606125247646021303' OR a.resultuid = '606125247646021303') AND dtt.dayofweek = 3;
Date: 2025-05-16 10:20:46 Duration: 4ms 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 = '606124541823008303' 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 = '606124541823008303' OR a.resultuid = '606124541823008303') AND dtt.dayofweek = 3;
Date: 2025-05-16 10:43:08 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
12 1,281 1s228ms 0ms 10ms 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 #12
Day Hour Count Duration Avg duration May 16 10 1,281 1s228ms 0ms [ User: postgres - Total duration: 1s228ms - Times executed: 1281 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s196ms - Times executed: 1267 ]
[ Application: [unknown] - Total duration: 31ms - Times executed: 14 ]
-
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 = '606125247828310301' 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 = '606125247828310301' OR a.resultuid = '606125247828310301') AND dtt.dayofweek = 3;
Date: 2025-05-16 10:39:03 Duration: 10ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_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 = '606124777260033301' 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 = '606124777260033301' OR a.resultuid = '606124777260033301') AND dtt.dayofweek = 3;
Date: 2025-05-16 10:41:08 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ) SELECT a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, CASE WHEN a.old_resultuid = '606125185374497301' 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 = '606125185374497301' OR a.resultuid = '606125185374497301') AND dtt.dayofweek = 3;
Date: 2025-05-16 10:14:04 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
13 991 9ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration May 16 10 991 9ms 0ms [ User: postgres - Total duration: 9ms - Times executed: 991 ]
[ Application: [unknown] - Total duration: 9ms - Times executed: 991 ]
-
SET extra_float_digits = 3;
Date: 2025-05-16 10:40:29 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2025-05-16 10:50:02 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.2.126 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2025-05-16 10:55:40 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: [unknown] Bind query: yes
14 957 12ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration May 16 10 957 12ms 0ms [ User: postgres - Total duration: 12ms - Times executed: 957 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12ms - Times executed: 957 ]
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-05-16 10:30:06 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-05-16 10:30:07 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-05-16 10:30:04 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
15 874 1s426ms 0ms 5ms 1ms select s.symbolid, dss.downloadfrequency, dss.downloadersymbol from downloadersymbolsettings dss inner join symbols s on dss.symbolid = s.symbolid where dss.classname = ? and s.deleted = ? and dss.enabled = ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration May 16 10 874 1s426ms 1ms [ User: postgres - Total duration: 1s426ms - Times executed: 874 ]
[ Application: [unknown] - Total duration: 1s426ms - Times executed: 874 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'ICMARKETS-AU-MT5' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-05-16 10:15:50 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'PEPPERSTONE' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-05-16 10:45:06 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'PEPPERSTONE' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-05-16 10:15:05 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
16 874 167ms 0ms 0ms 0ms select downloadersymbol, spike_threshold from price_datafeed_spike_threshold where classname = ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration May 16 10 874 167ms 0ms [ User: postgres - Total duration: 167ms - Times executed: 874 ]
[ Application: [unknown] - Total duration: 167ms - Times executed: 874 ]
-
SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'PEPPERSTONE';
Date: 2025-05-16 10:15:42 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'ATFX';
Date: 2025-05-16 10:45:35 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'BDSWISS';
Date: 2025-05-16 10:00:30 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
17 620 21ms 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 #17
Day Hour Count Duration Avg duration May 16 10 620 21ms 0ms [ User: postgres - Total duration: 21ms - Times executed: 620 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 21ms - Times executed: 620 ]
-
SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '515840243185493300' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-05-16 10:04:55 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '515840243886409300' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-05-16 10:18:16 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '515840243273975300' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-05-16 10:07:50 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
18 611 1s898ms 0ms 29ms 3ms select * from powerstatslatestprfprice (?, ?);Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration May 16 10 611 1s898ms 3ms [ User: postgres - Total duration: 1s898ms - Times executed: 611 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s834ms - Times executed: 602 ]
[ Application: [unknown] - Total duration: 63ms - Times executed: 9 ]
-
select * from PowerStatsLatestPRFPrice ('515840245847959300', '15');
Date: 2025-05-16 10:15:48 Duration: 29ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
-
select * from PowerStatsLatestPRFPrice ('515840243247146300', '15');
Date: 2025-05-16 10:30:33 Duration: 28ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
-
select * from PowerStatsLatestPRFPrice ('515840243153880300', '15');
Date: 2025-05-16 10:46:00 Duration: 26ms Database: acaweb_fx User: postgres Remote: 192.168.1.135 Application: PostgreSQL JDBC Driver Bind query: yes
19 555 47ms 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 #19
Day Hour Count Duration Avg duration May 16 10 555 47ms 0ms [ User: postgres - Total duration: 47ms - Times executed: 555 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 47ms - Times executed: 555 ]
-
/*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 = '606124996561430301';
Date: 2025-05-16 10:41:49 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
-
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = '606125011771406301';
Date: 2025-05-16 10:44:24 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
-
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = '606124833683693301';
Date: 2025-05-16 10:20:31 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
20 554 1s247ms 0ms 21ms 2ms 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 May 16 10 554 1s247ms 2ms [ User: postgres - Total duration: 1s247ms - Times executed: 554 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s238ms - Times executed: 550 ]
[ Application: [unknown] - Total duration: 9ms - Times executed: 4 ]
-
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 = '515840243189073300' 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: 2025-05-16 10:15:07 Duration: 21ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
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 = '515840243162686300' 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: 2025-05-16 10:00:04 Duration: 18ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
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 = '515840243162686300' 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: 2025-05-16 10:54:41 Duration: 15ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 8s513ms 9s356ms 8s788ms 4 35s155ms select updateageforrelevantresults ();Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration May 16 10 4 35s155ms 8s788ms [ User: postgres - Total duration: 35s155ms - Times executed: 4 ]
[ Application: psql - Total duration: 35s155ms - Times executed: 4 ]
-
select updateageforrelevantresults ();
Date: 2025-05-16 10:32:11 Duration: 9s356ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-05-16 10:17:10 Duration: 8s692ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-05-16 10:47:11 Duration: 8s593ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
2 362ms 23s831ms 8s633ms 320 46m2s with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ), ar as ( select a.*, rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end ), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on sg.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration May 16 10 320 46m2s 8s633ms [ User: postgres - Total duration: 46m2s - Times executed: 320 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 42m55s - Times executed: 308 ]
[ Application: [unknown] - Total duration: 3m6s - Times executed: 12 ]
-
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: 2025-05-16 10:16:04 Duration: 23s831ms 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 = '529' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('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 ('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: 2025-05-16 10:41:28 Duration: 19s716ms 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 ), 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: 2025-05-16 10:15:48 Duration: 17s680ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
3 124ms 36s917ms 7s192ms 319 38m14s with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration May 16 10 319 38m14s 7s192ms [ User: postgres - Total duration: 38m14s - Times executed: 319 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 36m - Times executed: 307 ]
[ Application: [unknown] - Total duration: 2m13s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-05-16 10:21:06 Duration: 36s917ms 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 ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-05-16 10:17:37 Duration: 31s454ms 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 ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-05-16 10:06:00 Duration: 30s456ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
4 4s429ms 8s615ms 5s969ms 6 35s814ms 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 May 16 10 6 35s814ms 5s969ms [ User: postgres - Total duration: 35s814ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 35s814ms - 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: 2025-05-16 10:00:11 Duration: 8s615ms 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: 2025-05-16 10:30:10 Duration: 7s907ms 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: 2025-05-16 10:20:08 Duration: 5s503ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
5 634ms 8s359ms 2s761ms 299 13m45s 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 May 16 10 299 13m45s 2s761ms [ User: postgres - Total duration: 13m45s - Times executed: 299 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12m40s - Times executed: 287 ]
[ 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: 2025-05-16 10:15:10 Duration: 8s359ms 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_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: 2025-05-16 10:15:56 Duration: 7s752ms 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: 2025-05-16 10:25:53 Duration: 7s592ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
6 1s758ms 2s980ms 2s72ms 16 33s165ms 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 May 16 10 16 33s165ms 2s72ms [ User: postgres - Total duration: 33s165ms - Times executed: 16 ]
[ Application: psql - Total duration: 33s165ms - 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: 2025-05-16 10:41:16 Duration: 2s980ms 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: 2025-05-16 10:16:16 Duration: 2s977ms 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: 2025-05-16 10:46:16 Duration: 2s953ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
7 1s283ms 2s170ms 1s480ms 20 29s614ms 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 = ? limit ? ) 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 May 16 10 20 29s614ms 1s480ms [ User: postgres - Total duration: 29s614ms - Times executed: 20 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 29s614ms - Times executed: 20 ]
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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' limit 1) 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: 2025-05-16 10:17:39 Duration: 2s170ms 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' limit 1) 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: 2025-05-16 10:37:11 Duration: 1s883ms 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' limit 1) 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: 2025-05-16 10:17:33 Duration: 1s818ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
8 1s46ms 1s767ms 1s342ms 6 8s52ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration May 16 10 6 8s52ms 1s342ms [ User: postgres - Total duration: 8s52ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 8s52ms - Times executed: 6 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-05-16 10:16:16 Duration: 1s767ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-05-16 10:46:18 Duration: 1s746ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-05-16 10:31:17 Duration: 1s345ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
9 665ms 1s605ms 876ms 16 14s23ms 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 #9
Day Hour Count Duration Avg duration May 16 10 16 14s23ms 876ms [ User: postgres - Total duration: 14s23ms - Times executed: 16 ]
[ Application: psql - Total duration: 14s23ms - 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: 2025-05-16 10:41:13 Duration: 1s605ms 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: 2025-05-16 10:26:12 Duration: 1s191ms 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: 2025-05-16 10:16:13 Duration: 1s143ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
10 12ms 10s574ms 846ms 34 28s764ms select fixcandlegaps (?, false);Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration May 16 10 34 28s764ms 846ms [ User: postgres - Total duration: 28s764ms - Times executed: 34 ]
[ Application: psql - Total duration: 28s764ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-05-16 10:06:30 Duration: 10s574ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-05-16 10:06:08 Duration: 3s609ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('AXIORY', false);
Date: 2025-05-16 10:06:11 Duration: 2s710ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 161ms 2s85ms 663ms 186 2m3s 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 May 16 10 186 2m3s 663ms [ User: postgres - Total duration: 2m3s - Times executed: 186 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m46s - Times executed: 174 ]
[ Application: [unknown] - Total duration: 16s575ms - 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: 2025-05-16 10:46:07 Duration: 2s85ms 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: 2025-05-16 10:16:12 Duration: 2s73ms 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: 2025-05-16 10:41:06 Duration: 2s68ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
12 94ms 893ms 350ms 131 45s926ms 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 #12
Day Hour Count Duration Avg duration May 16 10 131 45s926ms 350ms [ User: postgres - Total duration: 45s926ms - Times executed: 131 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 45s926ms - Times executed: 131 ]
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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: 2025-05-16 10:16:18 Duration: 893ms 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: 2025-05-16 10:52:14 Duration: 886ms 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: 2025-05-16 10:52:14 Duration: 884ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
13 9ms 294ms 89ms 186 16s590ms 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 #13
Day Hour Count Duration Avg duration May 16 10 186 16s590ms 89ms [ User: postgres - Total duration: 16s590ms - Times executed: 186 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14s121ms - Times executed: 174 ]
[ Application: [unknown] - Total duration: 2s468ms - 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: 2025-05-16 10:16:12 Duration: 294ms 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: 2025-05-16 10:46:07 Duration: 294ms 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: 2025-05-16 10:26:13 Duration: 294ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
14 0ms 479ms 85ms 80 6s860ms copy solr_relevance_old (uuid, relevant, age, result_uid) from stdin with ( format csv, header);Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration May 16 10 80 6s860ms 85ms [ User: postgres - Total duration: 6s860ms - Times executed: 80 ]
[ Application: psql - Total duration: 6s860ms - Times executed: 80 ]
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COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2025-05-16 10:18:12 Duration: 479ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2025-05-16 10:11:15 Duration: 464ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2025-05-16 10:56:13 Duration: 379ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
15 15ms 281ms 74ms 211 15s723ms 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 May 16 10 211 15s723ms 74ms [ User: postgres - Total duration: 15s723ms - Times executed: 211 ]
[ Application: [unknown] - Total duration: 15s723ms - Times executed: 211 ]
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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 'ICMARKETS-AU-MT5 - 4';
Date: 2025-05-16 10:15:49 Duration: 281ms 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 'GLOBALGTMT5 - 1';
Date: 2025-05-16 10:45:12 Duration: 254ms 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 'ICMARKETS - 1';
Date: 2025-05-16 10:46:00 Duration: 249ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
16 16ms 236ms 42ms 211 8s882ms 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 #16
Day Hour Count Duration Avg duration May 16 10 211 8s882ms 42ms [ User: postgres - Total duration: 8s882ms - Times executed: 211 ]
[ Application: [unknown] - Total duration: 8s882ms - Times executed: 211 ]
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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 'GLOBALGTMT5 - 1';
Date: 2025-05-16 10:30:05 Duration: 236ms 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 'ICMARKETS - 1';
Date: 2025-05-16 10:46:00 Duration: 183ms 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 'ICMARKETS - 1';
Date: 2025-05-16 10:15:41 Duration: 173ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
17 0ms 42ms 3ms 30,048 1m57s 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 #17
Day Hour Count Duration Avg duration May 16 10 30,048 1m57s 3ms [ User: postgres - Total duration: 1m57s - Times executed: 30048 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m57s - Times executed: 30048 ]
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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 = 'GBPSEK' OR dss.downloadersymbol = 'GBPSEK') AND dss.enabled = 1;
Date: 2025-05-16 10:30:05 Duration: 42ms 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 = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'BIDU.US' OR dss.downloadersymbol = 'BIDU.US') AND dss.enabled = 1;
Date: 2025-05-16 10:30:05 Duration: 40ms 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 = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'AUS200' OR dss.downloadersymbol = 'AUS200') AND dss.enabled = 1;
Date: 2025-05-16 10:00:07 Duration: 38ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
18 0ms 29ms 3ms 611 1s898ms select * from powerstatslatestprfprice (?, ?);Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration May 16 10 611 1s898ms 3ms [ User: postgres - Total duration: 1s898ms - Times executed: 611 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s834ms - Times executed: 602 ]
[ Application: [unknown] - Total duration: 63ms - Times executed: 9 ]
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select * from PowerStatsLatestPRFPrice ('515840245847959300', '15');
Date: 2025-05-16 10:15:48 Duration: 29ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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select * from PowerStatsLatestPRFPrice ('515840243247146300', '15');
Date: 2025-05-16 10:30:33 Duration: 28ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
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select * from PowerStatsLatestPRFPrice ('515840243153880300', '15');
Date: 2025-05-16 10:46:00 Duration: 26ms Database: acaweb_fx User: postgres Remote: 192.168.1.135 Application: PostgreSQL JDBC Driver Bind query: yes
19 0ms 21ms 2ms 554 1s247ms 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 #19
Day Hour Count Duration Avg duration May 16 10 554 1s247ms 2ms [ User: postgres - Total duration: 1s247ms - Times executed: 554 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s238ms - Times executed: 550 ]
[ Application: [unknown] - Total duration: 9ms - Times executed: 4 ]
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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 = '515840243189073300' 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: 2025-05-16 10:15:07 Duration: 21ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 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 = '515840243162686300' 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: 2025-05-16 10:00:04 Duration: 18ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 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 = '515840243162686300' 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: 2025-05-16 10:54:41 Duration: 15ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
20 0ms 5ms 1ms 874 1s426ms select s.symbolid, dss.downloadfrequency, dss.downloadersymbol from downloadersymbolsettings dss inner join symbols s on dss.symbolid = s.symbolid where dss.classname = ? and s.deleted = ? and dss.enabled = ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration May 16 10 874 1s426ms 1ms [ User: postgres - Total duration: 1s426ms - Times executed: 874 ]
[ Application: [unknown] - Total duration: 1s426ms - Times executed: 874 ]
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'ICMARKETS-AU-MT5' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-05-16 10:15:50 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'PEPPERSTONE' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-05-16 10:45:06 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'PEPPERSTONE' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-05-16 10:15:05 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 2s402ms 2,508 0ms 13ms 0ms WITH rar_max as ( ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration May 16 10 2,508 2s402ms 0ms [ User: postgres - Total duration: 1h33m50s - Times executed: 2508 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h28m18s - Times executed: 2438 ]
[ Application: [unknown] - Total duration: 5m32s - Times executed: 70 ]
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WITH rar_max as ( ;
Date: 2025-05-16 10:52:10 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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WITH rar_max as ( ;
Date: 2025-05-16 10:52:10 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
WITH rar_max as ( ;
Date: 2025-05-16 10:26:56 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
2 1s787ms 4,482 0ms 15ms 0ms SELECT ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 10 4,482 1s787ms 0ms [ User: postgres - Total duration: 8s929ms - Times executed: 4482 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 8s681ms - Times executed: 3542 ]
[ Application: [unknown] - Total duration: 247ms - Times executed: 940 ]
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SELECT ;
Date: 2025-05-16 10:45:06 Duration: 15ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
SELECT ;
Date: 2025-05-16 10:15:05 Duration: 9ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
SELECT ;
Date: 2025-05-16 10:30:03 Duration: 8ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
3 1s173ms 874 0ms 3ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 10 874 1s173ms 1ms [ User: postgres - Total duration: 1s426ms - Times executed: 874 ]
[ Application: [unknown] - Total duration: 1s426ms - Times executed: 874 ]
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-05-16 10:15:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-05-16 10:15:03 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-05-16 10:15:04 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
4 752ms 2,657 0ms 7ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 10 2,657 752ms 0ms [ User: postgres - Total duration: 6s259ms - Times executed: 2657 ]
[ Application: [unknown] - Total duration: 6s259ms - Times executed: 2657 ]
-
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: 2025-05-16 10:45:06 Duration: 7ms 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: 2025-05-16 10:00:05 Duration: 6ms 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: 2025-05-16 10:00:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
5 343ms 3,262 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 10 3,262 343ms 0ms [ User: postgres - Total duration: 2s64ms - Times executed: 3262 ]
[ Application: [unknown] - Total duration: 2s64ms - Times executed: 3262 ]
-
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: 2025-05-16 10:41:57 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
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: 2025-05-16 10:41:53 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
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: 2025-05-16 10:41:55 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
6 243ms 2,066 0ms 1ms 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 10 2,066 243ms 0ms [ User: postgres - Total duration: 1s100ms - Times executed: 2066 ]
[ Application: [unknown] - Total duration: 1s100ms - Times executed: 2066 ]
-
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: 2025-05-16 10:10:42 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
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: 2025-05-16 10:10:40 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
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: 2025-05-16 10:10:34 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
7 164ms 991 0ms 22ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 10 991 164ms 0ms [ User: postgres - Total duration: 9ms - Times executed: 991 ]
[ Application: [unknown] - Total duration: 9ms - Times executed: 991 ]
-
SET extra_float_digits = 3;
Date: 2025-05-16 10:00:04 Duration: 22ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
SET extra_float_digits = 3;
Date: 2025-05-16 10:32:16 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
SET extra_float_digits = 3;
Date: 2025-05-16 10:30:07 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
8 125ms 2,089 0ms 10ms 0ms select 1;Times Reported Time consuming prepare #8
Day Hour Count Duration Avg duration 10 2,089 125ms 0ms [ User: postgres - Total duration: 8ms - Times executed: 2089 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 7ms - Times executed: 2057 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 32 ]
-
select 1;
Date: 2025-05-16 10:00:04 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
select 1;
Date: 2025-05-16 10:30:04 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
select 1;
Date: 2025-05-16 10:48:28 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
9 110ms 20 4ms 7ms 5ms with sym_info as ( ;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 10 20 110ms 5ms [ User: postgres - Total duration: 29s614ms - Times executed: 20 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 29s614ms - Times executed: 20 ]
-
with sym_info as ( ;
Date: 2025-05-16 10:07:31 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
-
with sym_info as ( ;
Date: 2025-05-16 10:07:19 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
-
with sym_info as ( ;
Date: 2025-05-16 10:21:06 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
10 54ms 54 0ms 3ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 10 54 54ms 1ms [ User: postgres - Total duration: 22s890ms - Times executed: 54 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 22s890ms - Times executed: 54 ]
-
WITH last_candle AS ( ;
Date: 2025-05-16 10:48:15 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
WITH last_candle AS ( ;
Date: 2025-05-16 10:20:33 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
WITH last_candle AS ( ;
Date: 2025-05-16 10:16:00 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
11 47ms 18 1ms 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 #11
Day Hour Count Duration Avg duration 10 18 47ms 2ms [ User: postgres - Total duration: 31ms - Times executed: 18 ]
[ Application: [unknown] - Total duration: 31ms - 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: 2025-05-16 10:11:00 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: 2025-05-16 10:41:08 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-05-16 10:21:01 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
12 37ms 25 0ms 2ms 1ms with wh_patitioned as ( ;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 10 25 37ms 1ms [ User: postgres - Total duration: 1s18ms - Times executed: 25 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s18ms - Times executed: 25 ]
-
with wh_patitioned as ( ;
Date: 2025-05-16 10:12:12 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
with wh_patitioned as ( ;
Date: 2025-05-16 10:16:57 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
with wh_patitioned as ( ;
Date: 2025-05-16 10:22:28 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
13 23ms 24 0ms 7ms 0ms select count(*) from datafeed_restarter_events where is_current_entry = 1;Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 10 24 23ms 0ms [ User: postgres - Total duration: 63ms - Times executed: 24 ]
[ Application: [unknown] - Total duration: 63ms - Times executed: 24 ]
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select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-05-16 10:00:04 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
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select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-05-16 10:00:02 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-05-16 10:25:07 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
14 18ms 6 2ms 3ms 3ms select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 10 6 18ms 3ms [ User: postgres - Total duration: 12ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 12ms - Times executed: 6 ]
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select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2025-05-16 10:20:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
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select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2025-05-16 10:10:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
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select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2025-05-16 10:30:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
15 16ms 6 2ms 3ms 2ms 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;Times Reported Time consuming prepare #15
Day Hour Count Duration Avg duration 10 6 16ms 2ms [ User: postgres - Total duration: 35s814ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 35s814ms - 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: 2025-05-16 10:20:02 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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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: 2025-05-16 10:10:02 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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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: 2025-05-16 10:40:02 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
16 13ms 27 0ms 1ms 0ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 10 27 13ms 0ms [ User: postgres - Total duration: 0ms - Times executed: 27 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 0ms - Times executed: 27 ]
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-05-16 10:39:35 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-05-16 10:06:00 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-05-16 10:28:38 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
17 11ms 957 0ms 0ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 10 957 11ms 0ms [ User: postgres - Total duration: 12ms - Times executed: 957 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12ms - Times executed: 957 ]
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-05-16 10:29:26 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-05-16 10:00:03 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-05-16 10:05:41 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
18 8ms 90 0ms 0ms 0ms INSERT INTO mt4datafeederrors (datafeedname, eventtimestamp, errordescription, status, serveraddress, username) values ($1, current_timestamp, $2, $3, $4, $5);Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 10 90 8ms 0ms [ User: postgres - Total duration: 8ms - Times executed: 90 ]
[ Application: [unknown] - Total duration: 8ms - Times executed: 90 ]
-
INSERT INTO mt4datafeederrors (datafeedname, eventtimestamp, errordescription, status, serveraddress, username) values ($1, current_timestamp, $2, $3, $4, $5);
Date: 2025-05-16 10:20:53 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.205
-
INSERT INTO mt4datafeederrors (datafeedname, eventtimestamp, errordescription, status, serveraddress, username) values ($1, current_timestamp, $2, $3, $4, $5);
Date: 2025-05-16 10:47:37 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.205
-
INSERT INTO mt4datafeederrors (datafeedname, eventtimestamp, errordescription, status, serveraddress, username) values ($1, current_timestamp, $2, $3, $4, $5);
Date: 2025-05-16 10:32:15 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.205
19 4ms 4 1ms 1ms 1ms select distinct replace(recognitionengine, ' ', '_') || '%' || replace(datetimeupdate::text, ' ', '_') as t from latest_candle_datetime_per_receng order by t;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 10 4 4ms 1ms [ User: postgres - Total duration: 0ms - Times executed: 4 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 4 ]
-
select distinct replace(recognitionengine, ' ', '_') || '%' || replace(datetimeupdate::text, ' ', '_') as t from latest_candle_datetime_per_receng order by t;
Date: 2025-05-16 10:10:23 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select distinct replace(recognitionengine, ' ', '_') || '%' || replace(datetimeupdate::text, ' ', '_') as t from latest_candle_datetime_per_receng order by t;
Date: 2025-05-16 10:40:23 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
-
select distinct replace(recognitionengine, ' ', '_') || '%' || replace(datetimeupdate::text, ' ', '_') as t from latest_candle_datetime_per_receng order by t;
Date: 2025-05-16 10:10:22 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
20 4ms 4 0ms 1ms 1ms select *, ;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 10 4 4ms 1ms [ User: postgres - Total duration: 1ms - Times executed: 4 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1ms - Times executed: 4 ]
-
select *, ;
Date: 2025-05-16 10:43:01 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.161
-
select *, ;
Date: 2025-05-16 10:43:01 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.161
-
select *, ;
Date: 2025-05-16 10:43:02 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.161
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 36s468ms 68,929 0ms 26ms 0ms SELECT ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration May 16 10 68,929 36s468ms 0ms [ User: postgres - Total duration: 2m58s - Times executed: 68929 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m57s - Times executed: 67988 ]
[ Application: [unknown] - Total duration: 248ms - Times executed: 941 ]
-
SELECT ;
Date: 2025-05-16 10:15:06 Duration: 26ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '515840243148834300'
-
SELECT ;
Date: 2025-05-16 10:45:06 Duration: 25ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '515840216964965300'
-
SELECT ;
Date: 2025-05-16 10:15:04 Duration: 24ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '0', $3 = '0', $4 = 'MCD.US', $5 = 'MCD.US'
2 27s37ms 4,154 0ms 35ms 6ms WITH rar_max as ( ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 10 4,154 27s37ms 6ms [ User: postgres - Total duration: 1h40m24s - Times executed: 4154 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h33m39s - Times executed: 4074 ]
[ Application: [unknown] - Total duration: 6m44s - Times executed: 80 ]
-
WITH rar_max as ( ;
Date: 2025-05-16 10:34:46 Duration: 35ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = 't', $2 = '958', $3 = '3', $4 = '60', $5 = '240', $6 = '1440', $7 = '0', $8 = '', $9 = '50', $10 = 'AUDCAD', $11 = 'AUDJPY', $12 = 'AUDUSD', $13 = 'EURAUD', $14 = 'EURCHF', $15 = 'EURGBP', $16 = 'EURJPY', $17 = 'EURMXN', $18 = 'EURUSD', $19 = 'GBPJPY', $20 = 'GBPUSD', $21 = 'NZDUSD', $22 = 'USDCAD', $23 = 'USDCHF', $24 = 'USDJPY', $25 = 'USDMXN', $26 = 'BTCUSD', $27 = 'ETHUSD', $28 = 'LTCUSD', $29 = 'AAPL.US', $30 = 'AMD.US', $31 = 'AMZN.US', $32 = 'BABA.US', $33 = 'BRK.B.US', $34 = 'GOOG.US', $35 = 'INTC.US', $36 = 'META.US', $37 = 'MSFT.US', $38 = 'NFLX.US', $39 = 'NKE.US', $40 = 'NVDA.US', $41 = 'PYPL.US', $42 = 'TSLA.US', $43 = 'V.US', $44 = 'Cocoa', $45 = 'Coffee', $46 = 'NatGas', $47 = 'SpotBrent', $48 = 'XAGUSD', $49 = 'XAUUSD', $50 = 'AUS200', $51 = 'EUSTX50', $52 = 'FRA40', $53 = 'GER40', $54 = 'HK50', $55 = 'JPN225', $56 = 'NAS100', $57 = 'UK100', $58 = 'US30', $59 = 'US500', $60 = '0', $61 = '', $62 = '0', $63 = '0', $64 = '0', $65 = '400', $66 = '400', $67 = 't', $68 = '10', $69 = '10'
-
WITH rar_max as ( ;
Date: 2025-05-16 10:26:56 Duration: 34ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '627', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '213', $13 = '#ADBE', $14 = '#ALVG', $15 = '#AMZN', $16 = '#APPL', $17 = '#BA', $18 = '#BABA', $19 = '#BAYGn', $20 = '#BMWG', $21 = '#BNPP', $22 = '#CAT', $23 = '#CBKG', $24 = '#DAIGn', $25 = '#DIS', $26 = '#EA', $27 = '#FB', $28 = '#FDX', $29 = '#GE', $30 = '#GM', $31 = '#GOOGL', $32 = '#GS', $33 = '#INTC', $34 = '#JPM', $35 = '#KO', $36 = '#META', $37 = '#MSFT', $38 = '#NFLX', $39 = '#TSLA', $40 = '#VOWG', $41 = '#WMT', $42 = '#XOM', $43 = 'AUDCAD', $44 = 'AUDCHF', $45 = 'AUDJPY', $46 = 'AUDNZD', $47 = 'AUDUSD', $48 = 'AUS_200', $49 = 'BTCEUR', $50 = 'BTCGBP', $51 = 'BTCUSD', $52 = 'CADCHF', $53 = 'CADJPY', $54 = 'CHFJPY', $55 = 'CL_BRENT', $56 = 'DASHUSD', $57 = 'EOSUSD', $58 = 'ESP_35', $59 = 'ETHEUR', $60 = 'ETHGBP', $61 = 'ETHUSD', $62 = 'EURAUD', $63 = 'EURCAD', $64 = 'EURCHF', $65 = 'EURGBP', $66 = 'EURJPY', $67 = 'EURMXN', $68 = 'EURNOK', $69 = 'EURNZD', $70 = 'EURPLN', $71 = 'EURSEK', $72 = 'EURTRY', $73 = 'EURUSD', $74 = 'EUR_50', $75 = 'FRA_40', $76 = 'GBPAUD', $77 = 'GBPCAD', $78 = 'GBPCHF', $79 = 'GBPJPY', $80 = 'GBPNZD', $81 = 'GBPUSD', $82 = 'GBPZAR', $83 = 'GBR_100', $84 = 'HKDJPY', $85 = 'HKG_50', $86 = 'IOTAUSD', $87 = 'LTCEUR', $88 = 'LTCUSD', $89 = 'NAS100', $90 = 'NEOUSD', $91 = 'NOKJPY', $92 = 'NZDCAD', $93 = 'NZDCHF', $94 = 'NZDJPY', $95 = 'NZDUSD', $96 = 'OMGUSD', $97 = 'SPX500', $98 = 'TRXUSD', $99 = 'US30', $100 = 'USDCAD', $101 = 'USDCHF', $102 = 'USDCNH', $103 = 'USDDKK', $104 = 'USDJPY', $105 = 'USDMXN', $106 = 'USDNOK', $107 = 'USDPLN', $108 = 'USDSEK', $109 = 'USDSGD', $110 = 'USDZAR', $111 = 'USOIL', $112 = 'XAGUSD', $113 = 'XAUEUR', $114 = 'XAUUSD', $115 = 'XMRUSD', $116 = 'XPTUSD', $117 = 'XRPUSD', $118 = 'ZARJPY', $119 = 'ZECUSD', $120 = 'AUDCAD', $121 = 'AUDCHF', $122 = 'AUDJPY', $123 = 'AUDNZD', $124 = 'AUDUSD', $125 = 'CADCHF', $126 = 'CADJPY', $127 = 'CHFJPY', $128 = 'EURAUD', $129 = 'EURCAD', $130 = 'EURCHF', $131 = 'EURGBP', $132 = 'EURJPY', $133 = 'EURMXN', $134 = 'EURNOK', $135 = 'EURNZD', $136 = 'EURPLN', $137 = 'EURSEK', $138 = 'EURTRY', $139 = 'EURUSD', $140 = 'GBPAUD', $141 = 'GBPCAD', $142 = 'GBPCHF', $143 = 'GBPJPY', $144 = 'GBPNZD', $145 = 'GBPUSD', $146 = 'GBPZAR', $147 = 'HKDJPY', $148 = 'NOKJPY', $149 = 'NZDCAD', $150 = 'NZDCHF', $151 = 'NZDJPY', $152 = 'NZDUSD', $153 = 'USDCAD', $154 = 'USDCHF', $155 = 'USDCNH', $156 = 'USDDKK', $157 = 'USDJPY', $158 = 'USDMXN', $159 = 'USDNOK', $160 = 'USDPLN', $161 = 'USDSEK', $162 = 'USDSGD', $163 = 'USDZAR', $164 = 'ZARJPY', $165 = 'BTCEUR', $166 = 'BTCGBP', $167 = 'BTCUSD', $168 = 'DASHUSD', $169 = 'EOSUSD', $170 = 'ETHEUR', $171 = 'ETHGBP', $172 = 'ETHUSD', $173 = 'IOTAUSD', $174 = 'LTCEUR', $175 = 'LTCUSD', $176 = 'NEOUSD', $177 = 'OMGUSD', $178 = 'TRXUSD', $179 = 'XMRUSD', $180 = 'XRPUSD', $181 = 'ZECUSD', $182 = 'XAGUSD', $183 = 'XAUEUR', $184 = 'XAUUSD', $185 = 'XPTUSD', $186 = 'CL_BRENT', $187 = 'USOIL', $188 = '#ALVG', $189 = '#BAYGn', $190 = '#BMWG', $191 = '#BNPP', $192 = '#CBKG', $193 = '#DAIGn', $194 = '#VOWG', $195 = 'AUS_200', $196 = 'ESP_35', $197 = 'EUR_50', $198 = 'FRA_40', $199 = 'GBR_100', $200 = 'HKG_50', $201 = 'NAS100', $202 = 'SPX500', $203 = 'US30', $204 = '#ADBE', $205 = '#AMZN', $206 = '#APPL', $207 = '#BA', $208 = '#BABA', $209 = '#CAT', $210 = '#DIS', $211 = '#EA', $212 = '#FB', $213 = '#FDX', $214 = '#GE', $215 = '#GM', $216 = '#GOOGL', $217 = '#GS', $218 = '#INTC', $219 = '#JPM', $220 = '#KO', $221 = '#MSFT', $222 = '#NFLX', $223 = '#TSLA', $224 = '#WMT', $225 = '#XOM', $226 = '400', $227 = '400', $228 = 't', $229 = '10', $230 = '10'
-
WITH rar_max as ( ;
Date: 2025-05-16 10:26:12 Duration: 32ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.42 parameters: $1 = '689', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '310', $13 = '#AAPL', $14 = '#ADS', $15 = '#AIG', $16 = '#ALV', $17 = '#AMZN', $18 = '#AXP', $19 = '#BA', $20 = '#BABA', $21 = '#BAC', $22 = '#BAS', $23 = '#BAYN', $24 = '#BEI', $25 = '#BIDU', $26 = '#BMW', $27 = '#C', $28 = '#CAT', $29 = '#CBK', $30 = '#CL', $31 = '#CSCO', $32 = '#CVX', $33 = '#DAI', $34 = '#DB1', $35 = '#DBK', $36 = '#DIS', $37 = '#DPW', $38 = '#DTE', $39 = '#EBAY', $40 = '#EON', $41 = '#F', $42 = '#FB', $43 = '#FDX', $44 = '#FME', $45 = '#GE', $46 = '#GM', $47 = '#GOOG', $48 = '#GS', $49 = '#HPQ', $50 = '#IBM', $51 = '#IFX', $52 = '#INTC', $53 = '#JD', $54 = '#JNJ', $55 = '#JPM', $56 = '#KO', $57 = '#LHA', $58 = '#LMT', $59 = '#MA', $60 = '#MCD', $61 = '#META', $62 = '#MMM', $63 = '#MSFT', $64 = '#MUV2', $65 = '#NFLX', $66 = '#NKE', $67 = '#NTES', $68 = '#ORCL', $69 = '#PFE', $70 = '#PG', $71 = '#QCOM', $72 = '#RACE', $73 = '#RWE', $74 = '#SAP', $75 = '#SIE', $76 = '#T', $77 = '#UBER', $78 = '#V', $79 = '#VOW', $80 = '#WB', $81 = '#XOM', $82 = 'AUDCAD', $83 = 'AUDCHF', $84 = 'AUDJPY', $85 = 'AUDNZD', $86 = 'AUDUSD', $87 = 'AUS200', $88 = 'BRENT', $89 = 'BTCUSD', $90 = 'CADCHF', $91 = 'CADJPY', $92 = 'CHFJPY', $93 = 'CHI50', $94 = 'ESP35', $95 = 'ETHUSD', $96 = 'EU50', $97 = 'EURAUD', $98 = 'EURCAD', $99 = 'EURCHF', $100 = 'EURGBP', $101 = 'EURHUF', $102 = 'EURJPY', $103 = 'EURNZD', $104 = 'EURPLN', $105 = 'EURUSD', $106 = 'FRA40', $107 = 'GBPAUD', $108 = 'GBPCAD', $109 = 'GBPCHF', $110 = 'GBPJPY', $111 = 'GBPNZD', $112 = 'GBPUSD', $113 = 'GER30', $114 = 'HK50', $115 = 'HKCH50', $116 = 'IT40', $117 = 'JP225', $118 = 'LTCUSD', $119 = 'NAS100', $120 = 'NZDCAD', $121 = 'NZDCHF', $122 = 'NZDJPY', $123 = 'NZDUSD', $124 = 'SPX500', $125 = 'UK100', $126 = 'US30', $127 = 'USDCAD', $128 = 'USDCHF', $129 = 'USDCNH', $130 = 'USDCZK', $131 = 'USDDKK', $132 = 'USDHKD', $133 = 'USDHUF', $134 = 'USDJPY', $135 = 'USDMXN', $136 = 'USDNOK', $137 = 'USDPLN', $138 = 'USDSEK', $139 = 'USDSGD', $140 = 'USDTRY', $141 = 'USDX', $142 = 'USDZAR', $143 = 'WTI', $144 = 'XAGUSD', $145 = 'XAUUSD', $146 = '#ADS', $147 = '#ALV', $148 = '#BAS', $149 = '#BAYN', $150 = '#BEI', $151 = '#BMW', $152 = '#CBK', $153 = '#DAI', $154 = '#DB1', $155 = '#DBK', $156 = '#DPW', $157 = '#DTE', $158 = '#EON', $159 = '#FME', $160 = '#IFX', $161 = '#LHA', $162 = '#MUV2', $163 = '#RWE', $164 = '#SAP', $165 = '#SIE', $166 = '#VOW', $167 = 'AUDCAD', $168 = 'AUDCHF', $169 = 'AUDJPY', $170 = 'AUDNZD', $171 = 'AUDUSD', $172 = 'CADCHF', $173 = 'CADJPY', $174 = 'CHFJPY', $175 = 'EURAUD', $176 = 'EURCAD', $177 = 'EURCHF', $178 = 'EURGBP', $179 = 'EURHUF', $180 = 'EURJPY', $181 = 'EURNZD', $182 = 'EURPLN', $183 = 'EURUSD', $184 = 'GBPAUD', $185 = 'GBPCAD', $186 = 'GBPCHF', $187 = 'GBPJPY', $188 = 'GBPNZD', $189 = 'GBPUSD', $190 = 'NZDCAD', $191 = 'NZDCHF', $192 = 'NZDJPY', $193 = 'NZDUSD', $194 = 'USDCAD', $195 = 'USDCHF', $196 = 'USDCNH', $197 = 'USDCZK', $198 = 'USDDKK', $199 = 'USDHKD', $200 = 'USDHUF', $201 = 'USDJPY', $202 = 'USDMXN', $203 = 'USDNOK', $204 = 'USDPLN', $205 = 'USDSEK', $206 = 'USDSGD', $207 = 'USDTRY', $208 = 'USDX', $209 = 'USDZAR', $210 = 'XAGUSD', $211 = 'XAUUSD', $212 = 'BTCUSD', $213 = 'ETHUSD', $214 = 'LTCUSD', $215 = 'AUDCAD', $216 = 'AUDCHF', $217 = 'AUDJPY', $218 = 'AUDNZD', $219 = 'CADCHF', $220 = 'CADJPY', $221 = 'CHFJPY', $222 = 'EURAUD', $223 = 'EURCAD', $224 = 'EURCHF', $225 = 'EURGBP', $226 = 'EURHUF', $227 = 'EURJPY', $228 = 'EURNZD', $229 = 'EURPLN', $230 = 'GBPAUD', $231 = 'GBPCAD', $232 = 'GBPCHF', $233 = 'GBPJPY', $234 = 'GBPNZD', $235 = 'NZDCAD', $236 = 'NZDCHF', $237 = 'NZDJPY', $238 = 'USDCNH', $239 = 'USDCZK', $240 = 'USDDKK', $241 = 'USDHKD', $242 = 'USDHUF', $243 = 'USDMXN', $244 = 'USDNOK', $245 = 'USDPLN', $246 = 'USDSEK', $247 = 'USDSGD', $248 = 'USDTRY', $249 = 'USDX', $250 = 'USDZAR', $251 = 'XAGUSD', $252 = 'XAUUSD', $253 = 'BRENT', $254 = 'WTI', $255 = 'AUS200', $256 = 'CHI50', $257 = 'ESP35', $258 = 'EU50', $259 = 'FRA40', $260 = 'GER30', $261 = 'HK50', $262 = 'HKCH50', $263 = 'IT40', $264 = 'JP225', $265 = 'NAS100', $266 = 'SPX500', $267 = 'UK100', $268 = 'US30', $269 = 'AUDUSD', $270 = 'EURUSD', $271 = 'GBPUSD', $272 = 'NZDUSD', $273 = 'USDCAD', $274 = 'USDCHF', $275 = 'USDJPY', $276 = '#AAPL', $277 = '#AIG', $278 = '#AMZN', $279 = '#AXP', $280 = '#BA', $281 = '#BABA', $282 = '#BAC', $283 = '#BIDU', $284 = '#C', $285 = '#CAT', $286 = '#CL', $287 = '#CSCO', $288 = '#CVX', $289 = '#DIS', $290 = '#EBAY', $291 = '#F', $292 = '#FB', $293 = '#FDX', $294 = '#GE', $295 = '#GM', $296 = '#GOOG', $297 = '#GS', $298 = '#HPQ', $299 = '#IBM', $300 = '#INTC', $301 = '#JD', $302 = '#JNJ', $303 = '#JPM', $304 = '#KO', $305 = '#LMT', $306 = '#MA', $307 = '#MCD', $308 = '#MMM', $309 = '#MSFT', $310 = '#NFLX', $311 = '#NKE', $312 = '#NTES', $313 = '#ORCL', $314 = '#PFE', $315 = '#PG', $316 = '#QCOM', $317 = '#RACE', $318 = '#T', $319 = '#UBER', $320 = '#V', $321 = '#WB', $322 = '#XOM', $323 = '400', $324 = '400', $325 = 't', $326 = '10', $327 = '10'
3 1s669ms 874 1ms 13ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 10 874 1s669ms 1ms [ User: postgres - Total duration: 1s426ms - Times executed: 874 ]
[ Application: [unknown] - Total duration: 1s426ms - Times executed: 874 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-05-16 10:15:03 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'GLOBALGTMT5'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-05-16 10:15:59 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'PEPPERSTONE'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-05-16 10:30:06 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'ATFX'
4 1s406ms 47 0ms 46ms 29ms with wh_patitioned as ( ;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 10 47 1s406ms 29ms [ User: postgres - Total duration: 1s905ms - Times executed: 47 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s905ms - Times executed: 47 ]
-
with wh_patitioned as ( ;
Date: 2025-05-16 10:35:51 Duration: 46ms 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: 2025-05-16 10:22:28 Duration: 44ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '627', $2 = '627', $3 = '627', $4 = '627', $5 = '627', $6 = '627', $7 = '627', $8 = '627', $9 = '627'
-
with wh_patitioned as ( ;
Date: 2025-05-16 10:46:01 Duration: 44ms 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'
5 899ms 45,684 0ms 21ms 0ms select 1;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 10 45,684 899ms 0ms [ User: postgres - Total duration: 222ms - Times executed: 45684 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 221ms - Times executed: 45542 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 142 ]
-
select 1;
Date: 2025-05-16 10:00:04 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
select 1;
Date: 2025-05-16 10:15:06 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
select 1;
Date: 2025-05-16 10:30:04 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
6 863ms 131 4ms 17ms 6ms WITH last_candle AS ( ;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 10 131 863ms 6ms [ User: postgres - Total duration: 45s926ms - Times executed: 131 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 45s926ms - Times executed: 131 ]
-
WITH last_candle AS ( ;
Date: 2025-05-16 10:40:14 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529'
-
WITH last_candle AS ( ;
Date: 2025-05-16 10:20:33 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2025-05-16 10:48:16 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558'
7 628ms 5,975 0ms 7ms 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 10 5,975 628ms 0ms [ User: postgres - Total duration: 8s235ms - Times executed: 5975 ]
[ Application: [unknown] - Total duration: 8s235ms - Times executed: 5975 ]
-
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: 2025-05-16 10:15:06 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-05-16 11:00:00', $2 = '8468.1', $3 = '8468.1', $4 = '8442.1', $5 = '8443.6', $6 = '529', $7 = '515840245908539300', $8 = '0', $9 = '2025-05-16 10:15:06.956', $10 = '2025-05-16 10:15:06.846', $11 = '8468.1', $12 = '8468.1', $13 = '8442.1', $14 = '8443.6', $15 = '529', $16 = '0', $17 = '2025-05-16 10:15:06.956', $18 = '2025-05-16 10:15:06.846'
-
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: 2025-05-16 10:15:33 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-05-16 10:45:00', $2 = '402.5495', $3 = '402.7215', $4 = '402.508', $5 = '402.7215', $6 = '495', $7 = '515840249384641300', $8 = '0', $9 = '2025-05-16 10:15:33.461', $10 = '2025-05-16 10:15:32.752', $11 = '402.5495', $12 = '402.7215', $13 = '402.508', $14 = '402.7215', $15 = '495', $16 = '0', $17 = '2025-05-16 10:15:33.461', $18 = '2025-05-16 10:15:32.752'
-
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: 2025-05-16 10:00:05 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-05-16 10:30:00', $2 = '42446', $3 = '42453', $4 = '42437', $5 = '42439', $6 = '411', $7 = '515840230455699300', $8 = '0', $9 = '2025-05-16 10:00:05.632', $10 = '2025-05-16 10:00:05.415', $11 = '42446', $12 = '42453', $13 = '42437', $14 = '42439', $15 = '411', $16 = '0', $17 = '2025-05-16 10:00:05.632', $18 = '2025-05-16 10:00:05.415'
8 618ms 20 28ms 44ms 30ms with sym_info as ( ;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 10 20 618ms 30ms [ User: postgres - Total duration: 29s614ms - Times executed: 20 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 29s614ms - Times executed: 20 ]
-
with sym_info as ( ;
Date: 2025-05-16 10:07:36 Duration: 44ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'
-
with sym_info as ( ;
Date: 2025-05-16 10:21:27 Duration: 37ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '627', $2 = 'Forex', $3 = 'Forex', $4 = '627', $5 = 'Forex', $6 = '627', $7 = '627', $8 = 'Forex', $9 = '627'
-
with sym_info as ( ;
Date: 2025-05-16 10:07:19 Duration: 37ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
9 317ms 27 9ms 17ms 11ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 10 27 317ms 11ms [ User: postgres - Total duration: 0ms - Times executed: 27 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 0ms - Times executed: 27 ]
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-05-16 10:46:13 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '489', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-05-16 10:22:55 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '489', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-05-16 10:19:05 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '489', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
10 307ms 3,388 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 10 3,388 307ms 0ms [ User: postgres - Total duration: 2s142ms - Times executed: 3388 ]
[ Application: [unknown] - Total duration: 2s142ms - Times executed: 3388 ]
-
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: 2025-05-16 10:41:55 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-05-16 11:00:00', $2 = '21367.3', $3 = '21389.8', $4 = '21365', $5 = '21383.8', $6 = '3803', $7 = '515840248039147300', $8 = '0', $9 = '2025-05-16 10:41:55.637', $10 = '2025-05-16 10:41:55.57', $11 = '21367.3', $12 = '21389.8', $13 = '21365', $14 = '21383.8', $15 = '3803', $16 = '0', $17 = '2025-05-16 10:41:55.637', $18 = '2025-05-16 10:41:55.57'
-
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: 2025-05-16 10:41:53 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-05-16 10:00:00', $2 = '23356.85', $3 = '23384.35', $4 = '23337.25', $5 = '23368.35', $6 = '1856', $7 = '515840247933633300', $8 = '0', $9 = '2025-05-16 10:41:53.618', $10 = '2025-05-16 10:41:53.538', $11 = '23356.85', $12 = '23384.35', $13 = '23337.25', $14 = '23368.35', $15 = '1856', $16 = '0', $17 = '2025-05-16 10:41:53.618', $18 = '2025-05-16 10:41:53.538'
-
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: 2025-05-16 10:41:57 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-05-16 11:00:00', $2 = '42397.45', $3 = '42432.05', $4 = '42388.55', $5 = '42417.05', $6 = '1155', $7 = '515840248000726300', $8 = '0', $9 = '2025-05-16 10:41:57.595', $10 = '2025-05-16 10:41:57.558', $11 = '42397.45', $12 = '42432.05', $13 = '42388.55', $14 = '42417.05', $15 = '1155', $16 = '0', $17 = '2025-05-16 10:41:57.595', $18 = '2025-05-16 10:41:57.558'
11 214ms 2,195 0ms 1ms 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 bind #11
Day Hour Count Duration Avg duration 10 2,195 214ms 0ms [ User: postgres - Total duration: 1s158ms - Times executed: 2195 ]
[ Application: [unknown] - Total duration: 1s158ms - Times executed: 2195 ]
-
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: 2025-05-16 10:15:49 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-05-16 10:00:00', $2 = '193.282', $3 = '193.4805', $4 = '193.1455', $5 = '193.394', $6 = '8286', $7 = '515840230497281300', $8 = '0', $9 = '2025-05-16 10:15:49.916', $10 = '2025-05-16 10:15:49.915', $11 = '193.282', $12 = '193.4805', $13 = '193.1455', $14 = '193.394', $15 = '8286', $16 = '0', $17 = '2025-05-16 10:15:49.916', $18 = '2025-05-16 10:15:49.915'
-
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: 2025-05-16 10:00:53 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-05-16 10:00:00', $2 = '2.1155', $3 = '2.1241', $4 = '2.1155', $5 = '2.1223', $6 = '1321', $7 = '515840249415747300', $8 = '0', $9 = '2025-05-16 10:00:53.018', $10 = '2025-05-16 10:00:53.017', $11 = '2.1155', $12 = '2.1241', $13 = '2.1155', $14 = '2.1223', $15 = '1321', $16 = '0', $17 = '2025-05-16 10:00:53.018', $18 = '2025-05-16 10:00:53.017'
-
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: 2025-05-16 10:10:42 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-05-15 21:00:00', $2 = '107.94', $3 = '108.45', $4 = '107.92', $5 = '108.37', $6 = '3379', $7 = '515840247963296300', $8 = '0', $9 = '2025-05-16 10:10:42.164', $10 = '2025-05-16 10:10:42.124', $11 = '107.94', $12 = '108.45', $13 = '107.92', $14 = '108.37', $15 = '3379', $16 = '0', $17 = '2025-05-16 10:10:42.164', $18 = '2025-05-16 10:10:42.124'
12 172ms 199 0ms 1ms 0ms SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 10 199 172ms 0ms [ User: postgres - Total duration: 1s120ms - Times executed: 199 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s83ms - Times executed: 195 ]
[ Application: [unknown] - Total duration: 37ms - Times executed: 4 ]
-
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2025-05-16 10:20:33 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '529', $2 = 'NZDUSD.r', $3 = '529'
-
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2025-05-16 10:46:49 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.42 parameters: $1 = '689', $2 = 'XAUUSD', $3 = '689'
-
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2025-05-16 10:30:50 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.42 parameters: $1 = '689', $2 = 'XAUUSD', $3 = '689'
13 52ms 13 3ms 6ms 4ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 10 13 52ms 4ms [ User: postgres - Total duration: 731ms - Times executed: 13 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 707ms - Times executed: 12 ]
[ Application: [unknown] - Total duration: 23ms - Times executed: 1 ]
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-05-16 10:34:10 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.42 parameters: $1 = '689', $2 = '689'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-05-16 10:56:00 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '627', $2 = '627'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-05-16 10:30:51 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '538', $2 = '538'
14 42ms 555 0ms 0ms 0ms /*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 = $1;Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 10 555 42ms 0ms [ User: postgres - Total duration: 47ms - Times executed: 555 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 47ms - Times executed: 555 ]
-
/*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 = $1;
Date: 2025-05-16 10:20:14 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '606122420050209301'
-
/*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 = $1;
Date: 2025-05-16 10:40:55 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '606125366570489301'
-
/*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 = $1;
Date: 2025-05-16 10:28:39 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '606124986260547301'
15 31ms 309 0ms 0ms 0ms select category, ;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 10 309 31ms 0ms [ User: postgres - Total duration: 29ms - Times executed: 309 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 29ms - Times executed: 309 ]
-
select category, ;
Date: 2025-05-16 10:00:32 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.54 parameters: $1 = '601729875362372307', $2 = 'symbol', $3 = 'UK100', $4 = 'JPN225', $5 = 'AUS200', $6 = 'USA100', $7 = 'USDIndex', $8 = 'USA30', $9 = 'FRA40', $10 = 'SUI20', $11 = 'UK100', $12 = 'NETH25', $13 = 'USDIndex', $14 = 'USA30', $15 = 'JPN225', $16 = 'USA100', $17 = 'SPA35', $18 = 'AUS200', $19 = 'NETH25', $20 = 'SUI20', $21 = 'FRA40', $22 = 'SPA35', $23 = '601729875362372307', $24 = 'symbol', $25 = 'UK100', $26 = 'JPN225', $27 = 'AUS200', $28 = 'USA100', $29 = 'USDIndex', $30 = 'USA30', $31 = 'FRA40', $32 = 'SUI20', $33 = 'UK100', $34 = 'NETH25', $35 = 'USDIndex', $36 = 'USA30', $37 = 'JPN225', $38 = 'USA100', $39 = 'SPA35', $40 = 'AUS200', $41 = 'NETH25', $42 = 'SUI20', $43 = 'FRA40', $44 = 'SPA35'
-
select category, ;
Date: 2025-05-16 10:02:20 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.54 parameters: $1 = '500996399109302207', $2 = 'symbol', $3 = 'UK100', $4 = 'EURO50', $5 = 'XTIUSD', $6 = 'WTI', $7 = 'XAUAUD', $8 = 'FRA40', $9 = 'US100', $10 = 'XBRUSD', $11 = 'JP225', $12 = 'US500', $13 = 'XAUUSD', $14 = 'AUS200', $15 = 'BTCUSD', $16 = 'XAGUSD', $17 = 'SING30', $18 = 'CHINA50', $19 = 'XAGAUD', $20 = 'HK50', $21 = 'XPTUSD', $22 = 'US30', $23 = 'XPDUSD', $24 = 'CHINA50', $25 = 'WTI', $26 = 'EURO50', $27 = 'XTIUSD', $28 = 'UK100', $29 = 'XAGAUD', $30 = 'XAGUSD', $31 = 'US500', $32 = 'XAUAUD', $33 = 'AUS200', $34 = 'FRA40', $35 = 'XBRUSD', $36 = 'US30', $37 = 'US100', $38 = 'JP225', $39 = 'XAUUSD', $40 = 'HK50', $41 = 'BTCUSD', $42 = 'XPDUSD', $43 = 'SING30', $44 = 'SPA35', $45 = 'XPTUSD', $46 = 'ITA40', $47 = 'SPA35', $48 = 'ITA40', $49 = '500996399109302207', $50 = 'symbol', $51 = 'UK100', $52 = 'EURO50', $53 = 'XTIUSD', $54 = 'WTI', $55 = 'XAUAUD', $56 = 'FRA40', $57 = 'US100', $58 = 'XBRUSD', $59 = 'JP225', $60 = 'US500', $61 = 'XAUUSD', $62 = 'AUS200', $63 = 'BTCUSD', $64 = 'XAGUSD', $65 = 'SING30', $66 = 'CHINA50', $67 = 'XAGAUD', $68 = 'HK50', $69 = 'XPTUSD', $70 = 'US30', $71 = 'XPDUSD', $72 = 'CHINA50', $73 = 'WTI', $74 = 'EURO50', $75 = 'XTIUSD', $76 = 'UK100', $77 = 'XAGAUD', $78 = 'XAGUSD', $79 = 'US500', $80 = 'XAUAUD', $81 = 'AUS200', $82 = 'FRA40', $83 = 'XBRUSD', $84 = 'US30', $85 = 'US100', $86 = 'JP225', $87 = 'XAUUSD', $88 = 'HK50', $89 = 'BTCUSD', $90 = 'XPDUSD', $91 = 'SING30', $92 = 'SPA35', $93 = 'XPTUSD', $94 = 'ITA40', $95 = 'SPA35', $96 = 'ITA40'
-
select category, ;
Date: 2025-05-16 10:04:35 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.54 parameters: $1 = '515852059309933307', $2 = 'symbol', $3 = 'EURJPY', $4 = 'CADJPY', $5 = 'GBPJPY', $6 = 'NZDJPY', $7 = 'USDJPY', $8 = 'CHFJPY', $9 = 'XAGUSD', $10 = 'XAUUSD', $11 = 'GBPNZD', $12 = 'EURNZD', $13 = 'EURCAD', $14 = 'CADCHF', $15 = 'GBPCAD', $16 = 'GBPCAD', $17 = 'EURCAD', $18 = 'AUDUSD', $19 = 'NZDUSD', $20 = 'EURCHF', $21 = 'EURUSD', $22 = 'USDCAD', $23 = 'XAGUSD', $24 = 'GBPUSD', $25 = 'CADJPY', $26 = 'USDCAD', $27 = 'GBPJPY', $28 = 'GBPCHF', $29 = 'GBPCHF', $30 = 'EURNZD', $31 = 'EURJPY', $32 = 'GBPUSD', $33 = 'USDJPY', $34 = 'XAUUSD', $35 = 'USDCHF', $36 = 'CHFJPY', $37 = 'NZDJPY', $38 = 'GBPNZD', $39 = 'EURUSD', $40 = 'AUDUSD', $41 = 'EURCHF', $42 = 'USDCHF', $43 = 'NZDUSD', $44 = 'CADCHF', $45 = '515852059309933307', $46 = 'symbol', $47 = 'EURJPY', $48 = 'CADJPY', $49 = 'GBPJPY', $50 = 'NZDJPY', $51 = 'USDJPY', $52 = 'CHFJPY', $53 = 'XAGUSD', $54 = 'XAUUSD', $55 = 'GBPNZD', $56 = 'EURNZD', $57 = 'EURCAD', $58 = 'CADCHF', $59 = 'GBPCAD', $60 = 'GBPCAD', $61 = 'EURCAD', $62 = 'AUDUSD', $63 = 'NZDUSD', $64 = 'EURCHF', $65 = 'EURUSD', $66 = 'USDCAD', $67 = 'XAGUSD', $68 = 'GBPUSD', $69 = 'CADJPY', $70 = 'USDCAD', $71 = 'GBPJPY', $72 = 'GBPCHF', $73 = 'GBPCHF', $74 = 'EURNZD', $75 = 'EURJPY', $76 = 'GBPUSD', $77 = 'USDJPY', $78 = 'XAUUSD', $79 = 'USDCHF', $80 = 'CHFJPY', $81 = 'NZDJPY', $82 = 'GBPNZD', $83 = 'EURUSD', $84 = 'AUDUSD', $85 = 'EURCHF', $86 = 'USDCHF', $87 = 'NZDUSD', $88 = 'CADCHF'
16 31ms 1 31ms 31ms 31ms with maxwhid as ( ;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 10 1 31ms 31ms [ User: postgres - Total duration: 35ms - Times executed: 1 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 35ms - Times executed: 1 ]
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with maxwhid as ( ;
Date: 2025-05-16 10:11:10 Duration: 31ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.131 parameters: $1 = '335', $2 = '621', $3 = '637', $4 = '642', $5 = '660', $6 = '666', $7 = '643', $8 = '630', $9 = '680', $10 = '641', $11 = '431', $12 = '622', $13 = '489', $14 = '529', $15 = '576', $16 = '665', $17 = '667', $18 = '558', $19 = '620', $20 = '125', $21 = '488', $22 = '567', $23 = '689', $24 = '700', $25 = '758', $26 = '763', $27 = '765', $28 = '817', $29 = '914', $30 = '972'
17 24ms 6 3ms 5ms 4ms 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;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 10 6 24ms 4ms [ User: postgres - Total duration: 35s814ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 35s814ms - 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: 2025-05-16 10:20:02 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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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: 2025-05-16 10:40:02 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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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: 2025-05-16 10:50:02 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
18 23ms 620 0ms 0ms 0ms SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 10 620 23ms 0ms [ User: postgres - Total duration: 21ms - Times executed: 620 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 21ms - Times executed: 620 ]
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-05-16 10:47:36 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.239 parameters: $1 = '500991628266833200'
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-05-16 10:17:56 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '515840233919005300'
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-05-16 10:37:16 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '515840233392162300'
19 21ms 260 0ms 0ms 0ms /*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, 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 '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb 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 where resultuid = $1 and dtt.dayofweek = 3;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 10 260 21ms 0ms [ User: postgres - Total duration: 16ms - Times executed: 260 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 16ms - Times executed: 260 ]
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/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, 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 '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb 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 where resultuid = $1 and dtt.dayofweek = 3;
Date: 2025-05-16 10:34:19 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '606125185767513303'
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/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, 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 '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb 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 where resultuid = $1 and dtt.dayofweek = 3;
Date: 2025-05-16 10:53:01 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '606125068033878303'
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/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, 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 '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb 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 where resultuid = $1 and dtt.dayofweek = 3;
Date: 2025-05-16 10:45:31 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.239 parameters: $1 = '606124891392645303'
20 17ms 199 0ms 0ms 0ms SELECT DISTINCT COALESCE(stddev_15 / 2, 0) AS low_15_stddev, COALESCE(ave_15 / 2, 0) AS low_15_ave, COALESCE(stddev_15 / 2, 0) AS high_15_stddev, COALESCE(ave_15 / 2, 0) AS high_15_ave, COALESCE(stddev_30 / 2, 0) AS low_30_stddev, COALESCE(ave_30 / 2, 0) AS low_30_ave, COALESCE(stddev_30 / 2, 0) AS high_30_stddev, COALESCE(ave_30 / 2, 0) AS high_30_ave, COALESCE(stddev_60 / 2, 0) AS low_60_stddev, COALESCE(ave_60 / 2, 0) AS low_60_ave, COALESCE(stddev_60 / 2, 0) AS high_60_stddev, COALESCE(ave_60 / 2, 0) AS high_60_ave, COALESCE(stddev_240 / 2, 0) AS low_240_stddev, COALESCE(ave_240 / 2, 0) AS low_240_ave, COALESCE(stddev_240 / 2, 0) AS high_240_stddev, COALESCE(ave_240 / 2, 0) AS high_240_ave, COALESCE(stddev_1440 / 2, 0) AS low_1440_stddev, COALESCE(ave_1440 / 2, 0) AS low_1440_ave, COALESCE(stddev_1440 / 2, 0) AS high_1440_stddev, COALESCE(ave_1440 / 2, 0) AS high_1440_ave, s.exchange AS exchange, s.symbol AS symbol, s.longname, ps.enddate AS executiondate, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, dss.downloadersymbol FROM powerstats_trumpet ps INNER JOIN downloadersymbolsettings dss ON dss.symbolid = ps.symbolid INNER JOIN datafeedstimetable dtt ON dtt.classname = dss.classname INNER JOIN symbols s ON ps.symbolid = s.symbolid WHERE ps.dayofweek = $1 AND ps.fromtime = $2 AND ps.symbolid = $3 ORDER BY ps.enddate DESC LIMIT 1;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 10 199 17ms 0ms [ User: postgres - Total duration: 579ms - Times executed: 199 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 562ms - Times executed: 195 ]
[ Application: [unknown] - Total duration: 17ms - Times executed: 4 ]
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SELECT DISTINCT COALESCE(stddev_15 / 2, 0) AS low_15_stddev, COALESCE(ave_15 / 2, 0) AS low_15_ave, COALESCE(stddev_15 / 2, 0) AS high_15_stddev, COALESCE(ave_15 / 2, 0) AS high_15_ave, COALESCE(stddev_30 / 2, 0) AS low_30_stddev, COALESCE(ave_30 / 2, 0) AS low_30_ave, COALESCE(stddev_30 / 2, 0) AS high_30_stddev, COALESCE(ave_30 / 2, 0) AS high_30_ave, COALESCE(stddev_60 / 2, 0) AS low_60_stddev, COALESCE(ave_60 / 2, 0) AS low_60_ave, COALESCE(stddev_60 / 2, 0) AS high_60_stddev, COALESCE(ave_60 / 2, 0) AS high_60_ave, COALESCE(stddev_240 / 2, 0) AS low_240_stddev, COALESCE(ave_240 / 2, 0) AS low_240_ave, COALESCE(stddev_240 / 2, 0) AS high_240_stddev, COALESCE(ave_240 / 2, 0) AS high_240_ave, COALESCE(stddev_1440 / 2, 0) AS low_1440_stddev, COALESCE(ave_1440 / 2, 0) AS low_1440_ave, COALESCE(stddev_1440 / 2, 0) AS high_1440_stddev, COALESCE(ave_1440 / 2, 0) AS high_1440_ave, s.exchange AS exchange, s.symbol AS symbol, s.longname, ps.enddate AS executiondate, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, dss.downloadersymbol FROM powerstats_trumpet ps INNER JOIN downloadersymbolsettings dss ON dss.symbolid = ps.symbolid INNER JOIN datafeedstimetable dtt ON dtt.classname = dss.classname INNER JOIN symbols s ON ps.symbolid = s.symbolid WHERE ps.dayofweek = $1 AND ps.fromtime = $2 AND ps.symbolid = $3 ORDER BY ps.enddate DESC LIMIT 1;
Date: 2025-05-16 10:01:10 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '5', $2 = '645', $3 = '515840243130983300'
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SELECT DISTINCT COALESCE(stddev_15 / 2, 0) AS low_15_stddev, COALESCE(ave_15 / 2, 0) AS low_15_ave, COALESCE(stddev_15 / 2, 0) AS high_15_stddev, COALESCE(ave_15 / 2, 0) AS high_15_ave, COALESCE(stddev_30 / 2, 0) AS low_30_stddev, COALESCE(ave_30 / 2, 0) AS low_30_ave, COALESCE(stddev_30 / 2, 0) AS high_30_stddev, COALESCE(ave_30 / 2, 0) AS high_30_ave, COALESCE(stddev_60 / 2, 0) AS low_60_stddev, COALESCE(ave_60 / 2, 0) AS low_60_ave, COALESCE(stddev_60 / 2, 0) AS high_60_stddev, COALESCE(ave_60 / 2, 0) AS high_60_ave, COALESCE(stddev_240 / 2, 0) AS low_240_stddev, COALESCE(ave_240 / 2, 0) AS low_240_ave, COALESCE(stddev_240 / 2, 0) AS high_240_stddev, COALESCE(ave_240 / 2, 0) AS high_240_ave, COALESCE(stddev_1440 / 2, 0) AS low_1440_stddev, COALESCE(ave_1440 / 2, 0) AS low_1440_ave, COALESCE(stddev_1440 / 2, 0) AS high_1440_stddev, COALESCE(ave_1440 / 2, 0) AS high_1440_ave, s.exchange AS exchange, s.symbol AS symbol, s.longname, ps.enddate AS executiondate, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, dss.downloadersymbol FROM powerstats_trumpet ps INNER JOIN downloadersymbolsettings dss ON dss.symbolid = ps.symbolid INNER JOIN datafeedstimetable dtt ON dtt.classname = dss.classname INNER JOIN symbols s ON ps.symbolid = s.symbolid WHERE ps.dayofweek = $1 AND ps.fromtime = $2 AND ps.symbolid = $3 ORDER BY ps.enddate DESC LIMIT 1;
Date: 2025-05-16 10:15:49 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.42 parameters: $1 = '5', $2 = '660', $3 = '515840245847959300'
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SELECT DISTINCT COALESCE(stddev_15 / 2, 0) AS low_15_stddev, COALESCE(ave_15 / 2, 0) AS low_15_ave, COALESCE(stddev_15 / 2, 0) AS high_15_stddev, COALESCE(ave_15 / 2, 0) AS high_15_ave, COALESCE(stddev_30 / 2, 0) AS low_30_stddev, COALESCE(ave_30 / 2, 0) AS low_30_ave, COALESCE(stddev_30 / 2, 0) AS high_30_stddev, COALESCE(ave_30 / 2, 0) AS high_30_ave, COALESCE(stddev_60 / 2, 0) AS low_60_stddev, COALESCE(ave_60 / 2, 0) AS low_60_ave, COALESCE(stddev_60 / 2, 0) AS high_60_stddev, COALESCE(ave_60 / 2, 0) AS high_60_ave, COALESCE(stddev_240 / 2, 0) AS low_240_stddev, COALESCE(ave_240 / 2, 0) AS low_240_ave, COALESCE(stddev_240 / 2, 0) AS high_240_stddev, COALESCE(ave_240 / 2, 0) AS high_240_ave, COALESCE(stddev_1440 / 2, 0) AS low_1440_stddev, COALESCE(ave_1440 / 2, 0) AS low_1440_ave, COALESCE(stddev_1440 / 2, 0) AS high_1440_stddev, COALESCE(ave_1440 / 2, 0) AS high_1440_ave, s.exchange AS exchange, s.symbol AS symbol, s.longname, ps.enddate AS executiondate, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, dss.downloadersymbol FROM powerstats_trumpet ps INNER JOIN downloadersymbolsettings dss ON dss.symbolid = ps.symbolid INNER JOIN datafeedstimetable dtt ON dtt.classname = dss.classname INNER JOIN symbols s ON ps.symbolid = s.symbolid WHERE ps.dayofweek = $1 AND ps.fromtime = $2 AND ps.symbolid = $3 ORDER BY ps.enddate DESC LIMIT 1;
Date: 2025-05-16 10:30:49 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.42 parameters: $1 = '5', $2 = '675', $3 = '515840245847959300'
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Events
Log levels
Key values
- 506,728 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