-
Global information
- Generated on Tue Jun 17 09:00:30 2025
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2025-06-17_100000.log, ..., /home/postgres/pg_data/data/pg_log/postgresql-2025-06-17_104637.log
- Parsed 2,999,566 log entries in 1m29s
- Log start from 2025-06-17 10:00:00 to 2025-06-17 11:00:00
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Overview
Global Stats
- 266 Number of unique normalized queries
- 184,053 Number of queries
- 2h35m42s Total query duration
- 2025-06-17 10:00:00 First query
- 2025-06-17 11:00:00 Last query
- 3,372 queries/s at 2025-06-17 10:15:04 Query peak
- 2h35m42s Total query duration
- 9s19ms Prepare/parse total duration
- 1m26s Bind total duration
- 2h34m6s Execute total duration
- 1 Number of events
- 1 Number of unique normalized events
- 1 Max number of times the same event was reported
- 0 Number of cancellation
- 36 Total number of automatic vacuums
- 58 Total number of automatic analyzes
- 472 Number temporary file
- 175.70 MiB Max size of temporary file
- 7.63 MiB Average size of temporary file
- 3,858 Total number of sessions
- 11 sessions at 2025-06-17 10:45:07 Session peak
- 2d11h51m55s Total duration of sessions
- 55s861ms Average duration of sessions
- 47 Average queries per session
- 2s421ms Average queries duration per session
- 53s440ms Average idle time per session
- 3,861 Total number of connections
- 28 connections/s at 2025-06-17 10:00:55 Connection peak
- 2 Total number of databases
SQL Traffic
Key values
- 3,372 queries/s Query Peak
- 2025-06-17 10:15:04 Date
SELECT Traffic
Key values
- 3,301 queries/s Query Peak
- 2025-06-17 10:15:04 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 193 queries/s Query Peak
- 2025-06-17 10:45:49 Date
Queries duration
Key values
- 2h35m42s 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) Jun 17 10 184,052 0ms 42s521ms 50ms 4m25s 4m46s 5m26s 11 1 0ms 0ms 0ms 0ms 0ms 0ms Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jun 17 10 137,759 26 2ms 4s984ms 17s226ms 34s793ms 11 1 0 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jun 17 10 34,260 2,650 16 96 1ms 799ms 1s458ms 3s813ms 11 0 0 0 0 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Jun 17 10 23,981 155,320 6.48 13.26% 11 0 1 1.00 0.00% Day Hour Count Average / Second Jun 17 10 3,861 1.07/s 11 0 0.00/s Day Hour Count Average Duration Average idle time Jun 17 10 3,858 55s861ms 53s465ms 11 0 0ms 0ms -
Connections
Established Connections
Key values
- 28 connections Connection Peak
- 2025-06-17 10:00:55 Date
Connections per database
Key values
- acaweb_fx Main Database
- 3,861 connections Total
Connections per user
Key values
- postgres Main User
- 3,861 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 1384 connections
- 3,861 Total connections
Host Count 127.0.0.1 130 192.168.0.114 3 192.168.0.216 102 192.168.0.74 179 192.168.1.127 26 192.168.1.145 248 192.168.1.15 488 192.168.1.20 282 192.168.1.231 20 192.168.1.239 10 192.168.1.90 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 63 192.168.4.133 6 192.168.4.142 1,384 192.168.4.150 10 192.168.4.215 1 192.168.4.233 4 192.168.4.238 14 192.168.4.33 90 192.168.4.98 330 [local] 275 -
Sessions
Simultaneous sessions
Key values
- 11 sessions Session Peak
- 2025-06-17 10:45:07 Date
Histogram of session times
Key values
- 2,887 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 3,858 sessions Total
Sessions per user
Key values
- postgres Main User
- 3,858 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 3,858 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 128 1h22m22s 38s614ms 192.168.0.114 3 15m6s 5m2s 192.168.0.216 102 1m53s 1s116ms 192.168.0.74 179 4h26m43s 1m29s 192.168.1.127 26 7s773ms 298ms 192.168.1.145 248 4h9m48s 1m 192.168.1.15 487 3h57m 29s199ms 192.168.1.20 282 15h6m18s 3m12s 192.168.1.231 20 9h52m44s 29m38s 192.168.1.239 10 112ms 11ms 192.168.1.90 56 42s67ms 751ms 192.168.2.126 68 6s538ms 96ms 192.168.2.182 12 1s583ms 131ms 192.168.2.205 12 570ms 47ms 192.168.2.82 48 1m11s 1s494ms 192.168.3.199 63 37s692ms 598ms 192.168.4.133 6 70ms 11ms 192.168.4.142 1,384 20m53s 905ms 192.168.4.150 10 20h12m39s 2h1m15s 192.168.4.215 1 161ms 161ms 192.168.4.233 4 33ms 8ms 192.168.4.238 14 19s105ms 1s364ms 192.168.4.33 90 38s986ms 433ms 192.168.4.98 330 13s521ms 40ms [local] 275 2m24s 523ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 16,106 buffers Checkpoint Peak
- 2025-06-17 10:07:33 Date
- 209.843 seconds Highest write time
- 0.009 seconds Sync time
Checkpoints Wal files
Key values
- 9 files Wal files usage Peak
- 2025-06-17 10:07:33 Date
Checkpoints distance
Key values
- 270.42 Mo Distance Peak
- 2025-06-17 10:07:33 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Jun 17 10 57,416 1,838.196s 0.037s 1,838.585s 11 0 0s 0s 0s Day Hour Added Removed Recycled Synced files Longest sync Average sync Jun 17 10 0 0 31 1,986 0.007s 0s 11 0 0 0 0 0s 0s Day Hour Count Avg time (sec) Jun 17 10 0 0s 11 0 0s Day Hour Mean distance Mean estimate Jun 17 10 42,922.33 kB 98,393.50 kB 11 0.00 kB 0.00 kB -
Temporary Files
Size of temporary files
Key values
- 160.27 MiB Temp Files size Peak
- 2025-06-17 10:40:08 Date
Number of temporary files
Key values
- 30 per second Temp Files Peak
- 2025-06-17 10:47:12 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Jun 17 10 472 3.52 GiB 7.63 MiB 11 0 0 0 Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 133 599.55 MiB 3.02 MiB 7.68 MiB 4.51 MiB with rar_max as ( ;-
WITH rar_max as ( ;
Date: 2025-06-17 10:46:53 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver
2 42 1.61 GiB 2.59 MiB 175.70 MiB 39.33 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 = ? ), 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: 2025-06-17 10:00:11 Duration: 8s612ms 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: 2025-06-17 10:30:10 Duration: 7s216ms 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: 2025-06-17 10:10:09 Duration: 6s443ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
3 16 371.23 MiB 23.20 MiB 23.20 MiB 23.20 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: 2025-06-17 10:03:13 Duration: 1s633ms 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: 2025-06-17 10:18:13 Duration: 1s500ms 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: 2025-06-17 10:26:13 Duration: 1s391ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
4 16 754.35 MiB 47.14 MiB 47.15 MiB 47.15 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: 2025-06-17 10:31:16 Duration: 3s579ms 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: 2025-06-17 10:03:17 Duration: 3s90ms 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: 2025-06-17 10:18:17 Duration: 3s82ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
5 4 216.79 MiB 54.13 MiB 54.27 MiB 54.20 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2025-06-17 10:17:16 Duration: 13s572ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-06-17 10:47:14 Duration: 11s861ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-06-17 10:02:11 Duration: 8s715ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
6 2 8.55 MiB 4.26 MiB 4.29 MiB 4.28 MiB select resultuid from relevance_fibonacci_results order by resultuid desc limit ?), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp)))), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;-
SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4, $5, $6, $7, $8, $9, $10)) AND ($11 = 0 OR s.exchange in ($12)) AND ($13 = 0 OR coalesce(bim.code, s.symbol) in ($14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226, $227, $228, $229, $230, $231, $232, $233, $234, $235, $236, $237, $238, $239, $240, $241, $242, $243, $244, $245, $246, $247, $248, $249, $250, $251, $252, $253, $254, $255, $256, $257, $258, $259, $260, $261, $262, $263, $264, $265, $266, $267, $268, $269, $270, $271, $272, $273, $274, $275, $276, $277, $278, $279, $280, $281, $282, $283, $284, $285, $286, $287, $288, $289, $290, $291, $292, $293, $294, $295, $296, $297, $298, $299, $300, $301, $302, $303, $304, $305, $306, $307, $308, $309, $310, $311, $312, $313, $314, $315, $316, $317, $318, $319, $320, $321, $322, $323)) AND ($324 = 0 OR fr.pattern in ($325)) AND ($326 = 0 OR fr.patternlengthbars <= $327) AND ($328 = 0 OR ($329 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($330 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $331 OR relevant = 1) AND ($332 = 0 OR age <= $333) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 10:49:35 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver
Queries generating the largest temporary files
Rank Size Query 1 175.70 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: 2025-06-17 10:50:03 ]
2 142.57 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 10:10:06 ]
3 132.31 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 10:00:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
4 124.77 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: 2025-06-17 10:20:05 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
5 111.34 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 10:40:04 ]
6 98.16 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 10:30:05 ]
7 84.12 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: 2025-06-17 10:40:05 ]
8 69.98 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: 2025-06-17 10:30:07 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
9 59.96 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: 2025-06-17 10:20:04 ]
10 55.37 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: 2025-06-17 10:10:04 ]
11 54.27 MiB select updateageforrelevantresults ();[ Date: 2025-06-17 10:02:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
12 54.22 MiB select updateageforrelevantresults ();[ Date: 2025-06-17 10:32:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
13 54.17 MiB select updateageforrelevantresults ();[ Date: 2025-06-17 10:47:06 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
14 54.13 MiB select updateageforrelevantresults ();[ Date: 2025-06-17 10:17:07 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
15 49.31 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 10:00:07 ]
16 48.33 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: 2025-06-17 10:10:05 ]
17 48.17 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: 2025-06-17 10:00:07 ]
18 47.90 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: 2025-06-17 10:20:04 ]
19 47.15 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: 2025-06-17 10:11:15 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
20 47.15 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: 2025-06-17 10:16:15 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
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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 socialmedia.public.processes 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 Total 58 Vacuums per table
Key values
- public.solr_relevance_old (16) Main table vacuumed on database acaweb_fx
- 36 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 15,804 0 68 0 0 11,655 1,411 6,238,500 acaweb_fx.public.datafeeds_latestrun 4 0 455 0 34 0 0 71 33 72,776 acaweb_fx.pg_toast.pg_toast_2619 2 2 318 0 56 0 0 218 56 221,163 acaweb_fx.public.relevance_keylevels_results 2 2 8,432 0 474 2 98 2,591 674 2,323,479 acaweb_fx.public.relevance_autochartist_results 2 2 7,301 0 275 2 414 1,862 261 758,641 acaweb_fx.public.relevance_fibonacci_results 2 2 2,759 0 105 2 74 558 73 218,406 socialmedia.public.executionlogs 1 1 27,385 0 19,758 0 0 23,009 2,765 12,729,451 acaweb_fx.pg_catalog.pg_type 1 1 140 0 21 0 0 54 15 95,821 acaweb_fx.public.autochartist_symbolupdates 1 1 22,956 0 6,267 5 37,985 7,546 6,201 2,374,506 acaweb_fx.pg_catalog.pg_statistic 1 1 872 0 218 0 668 425 188 746,140 acaweb_fx.pg_catalog.pg_attribute 1 1 790 0 185 0 67 361 151 885,465 acaweb_fx.public.solr_imports 1 1 49 0 2 0 0 6 1 5,955 acaweb_fx.public.latest_t15_candle_view 1 1 92 0 1 0 0 6 1 9,043 acaweb_fx.pg_catalog.pg_class 1 1 371 0 45 0 40 125 40 192,474 Total 36 32 87,724 100,708 27,509 11 39,346 48,487 11,870 26,871,820 Tuples removed per table
Key values
- public.solr_relevance_old (83595) Main table with removed tuples on database acaweb_fx
- 95720 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 16 16 83,595 110,342 0 0 4,003 acaweb_fx.public.autochartist_symbolupdates 1 1 5,464 45,983 0 0 40,691 acaweb_fx.public.relevance_keylevels_results 2 2 2,046 25,522 0 0 558 acaweb_fx.public.relevance_autochartist_results 2 2 1,599 19,130 0 0 760 acaweb_fx.pg_catalog.pg_attribute 1 1 1,113 9,510 137 0 250 acaweb_fx.pg_catalog.pg_statistic 1 1 655 4,289 0 0 1,194 acaweb_fx.public.relevance_fibonacci_results 2 2 411 3,331 0 0 204 acaweb_fx.public.datafeeds_latestrun 4 0 263 65 5 0 64 acaweb_fx.pg_catalog.pg_type 1 1 159 1,341 3 0 38 acaweb_fx.pg_toast.pg_toast_2619 2 2 155 353 10 0 105 acaweb_fx.pg_catalog.pg_class 1 1 150 1,952 5 0 150 acaweb_fx.public.latest_t15_candle_view 1 1 61 14 0 0 1 acaweb_fx.public.solr_imports 1 1 49 3 2 0 2 socialmedia.public.executionlogs 1 1 0 5,275,551 0 0 82,702 Total 36 32 95,720 5,497,386 162 0 130,722 Pages removed per table
Key values
- unknown (0) Main table with removed pages on database unknown
- 0 pages Total removed
Pages removed per tables
NO DATASET
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_toast.pg_toast_2619 2 2 155 0 socialmedia.public.executionlogs 1 1 0 0 acaweb_fx.pg_catalog.pg_type 1 1 159 0 acaweb_fx.public.autochartist_symbolupdates 1 1 5464 0 acaweb_fx.public.datafeeds_latestrun 4 0 263 0 acaweb_fx.pg_catalog.pg_statistic 1 1 655 0 acaweb_fx.pg_catalog.pg_attribute 1 1 1113 0 acaweb_fx.public.solr_imports 1 1 49 0 acaweb_fx.public.latest_t15_candle_view 1 1 61 0 acaweb_fx.public.relevance_keylevels_results 2 2 2046 0 acaweb_fx.pg_catalog.pg_class 1 1 150 0 acaweb_fx.public.solr_relevance_old 16 16 83595 0 acaweb_fx.public.relevance_autochartist_results 2 2 1599 0 acaweb_fx.public.relevance_fibonacci_results 2 2 411 0 Total 36 32 95,720 0 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Jun 17 10 36 58 11 0 0 - 0 sec Highest CPU-cost vacuum
-
Locks
Locks by types
Key values
- unknown Main Lock Type
- 0 locks Total
Most frequent waiting queries (N)
Rank Count Total time Min time Max time Avg duration Query NO DATASET
Queries that waited the most
Rank Wait time Query NO DATASET
-
Queries
Queries by type
Key values
- 137,760 Total read queries
- 43,144 Total write queries
Queries by database
Key values
- acaweb_fx Main database
- 175,327 Requests
- 2h33m53s (acaweb_fx)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 175,327 2h33m53s copy from 96 6s479ms copy to 26 4s836ms cte 5,396 2h27m37s ddl 16 515ms delete 16 25ms insert 27,210 30s951ms others 3,097 8s859ms select 136,198 5m2s tcl 684 200ms update 2,588 20s864ms socialmedia Total 8,726 13s536ms insert 7,050 7s989ms others 52 2ms select 1,562 5s441ms update 62 102ms Queries by user
Key values
- postgres Main user
- 184,053 Requests
User Request type Count Duration postgres Total 184,053 2h34m6s copy from 96 6s479ms copy to 26 4s836ms cte 5,396 2h27m37s ddl 16 515ms delete 16 25ms insert 34,260 38s940ms others 3,149 8s862ms select 137,760 5m8s tcl 684 200ms update 2,650 20s967ms Duration by user
Key values
- 2h34m6s (postgres) Main time consuming user
User Request type Count Duration postgres Total 184,053 2h34m6s copy from 96 6s479ms copy to 26 4s836ms cte 5,396 2h27m37s ddl 16 515ms delete 16 25ms insert 34,260 38s940ms others 3,149 8s862ms select 137,760 5m8s tcl 684 200ms update 2,650 20s967ms Queries by host
Key values
- 192.168.1.145 Main host
- 53,936 Requests
- 41m45s (192.168.1.15)
- Main time consuming host
Host Request type Count Duration 127.0.0.1 Total 16,889 44s811ms copy to 26 4s836ms cte 24 379ms insert 14,014 18s997ms others 58 1ms select 719 18s321ms update 2,048 2s274ms 182.165.1.42 Total 220 7m14s cte 60 7m14s select 160 257ms 182.165.1.54 Total 641 121ms select 641 121ms 192.168.0.114 Total 44 91ms others 4 0ms select 14 83ms tcl 20 7ms update 6 1ms 192.168.0.216 Total 408 382ms others 204 21ms select 196 241ms update 8 119ms 192.168.0.236 Total 24 6ms cte 4 2ms select 20 4ms 192.168.0.239 Total 841 1s154ms select 841 1s154ms 192.168.0.42 Total 2,029 1s297ms insert 599 48ms select 1,430 1s248ms 192.168.0.74 Total 4,999 35m53s cte 1,014 35m50s others 358 4ms select 3,627 2s667ms 192.168.1.127 Total 1,257 5s203ms others 52 2ms select 1,203 5s196ms update 2 4ms 192.168.1.135 Total 250 667ms cte 8 164ms select 242 502ms 192.168.1.145 Total 53,936 31m2s cte 965 29m39s others 496 5ms select 52,475 1m22s 192.168.1.15 Total 23,852 41m45s cte 2,188 41m24s others 976 18ms select 20,688 20s997ms 192.168.1.20 Total 49,730 33m15s cte 1,013 31m53s others 564 6ms select 48,153 1m22s 192.168.1.201 Total 2,124 2s430ms select 2,124 2s430ms 192.168.1.210 Total 16 0ms select 16 0ms 192.168.1.23 Total 2,714 2s985ms select 2,714 2s985ms 192.168.1.231 Total 42 1ms others 40 0ms select 2 0ms 192.168.1.239 Total 40 24ms others 20 1ms select 20 22ms 192.168.1.90 Total 64 39s904ms cte 6 39s401ms others 8 0ms select 50 503ms 192.168.1.97 Total 34 13ms cte 5 2ms select 29 11ms 192.168.2.126 Total 90 428ms others 18 0ms select 68 428ms tcl 4 0ms 192.168.2.182 Total 48 344ms others 24 2ms select 12 12ms update 12 329ms 192.168.2.205 Total 138 119ms insert 90 7ms others 24 2ms select 20 21ms update 4 88ms 192.168.2.82 Total 1,036 2s145ms insert 664 1s312ms others 96 10ms select 166 103ms update 110 718ms 192.168.3.199 Total 252 316ms others 126 13ms select 114 138ms update 12 164ms 192.168.4.133 Total 20 1ms others 12 0ms select 4 1ms update 4 0ms 192.168.4.142 Total 13,430 11s940ms insert 11,839 10s578ms select 1,591 1s362ms 192.168.4.150 Total 22 1s817ms others 21 0ms select 1 1s817ms 192.168.4.215 Total 3 37ms cte 1 37ms others 2 0ms 192.168.4.233 Total 12 0ms others 8 0ms select 4 0ms 192.168.4.238 Total 44 18s210ms cte 12 18s204ms insert 4 5ms others 28 0ms 192.168.4.33 Total 7,469 8s333ms insert 7,050 7s989ms select 359 245ms update 60 98ms 192.168.4.98 Total 996 9s349ms others 6 8s447ms select 6 27ms tcl 660 193ms update 324 681ms [local] Total 339 2m23s copy from 96 6s479ms cte 96 37s199ms ddl 16 515ms delete 16 25ms others 4 320ms select 51 1m22s update 60 16s487ms Queries by application
Key values
- PostgreSQL JDBC Driver Main application
- 140,095 Requests
- 2h22m25s (PostgreSQL JDBC Driver)
- Main time consuming application
Application Request type Count Duration PostgreSQL JDBC Driver Total 140,095 2h22m25s cte 5,201 2h19m6s insert 603 54ms others 1,271 16ms select 133,016 3m18s update 4 0ms [unknown] Total 43,506 9m12s cte 75 7m53s insert 33,657 38s885ms others 1,874 8s524ms select 4,641 26s736ms tcl 684 200ms update 2,575 4s453ms psql Total 452 2m28s copy from 96 6s479ms copy to 26 4s836ms cte 120 37s578ms ddl 16 515ms delete 16 25ms others 4 320ms select 103 1m22s update 71 16s512ms Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2025-06-17 10:35:19 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 100,233 0-1ms duration
Slowest individual queries
Rank Duration Query 1 42s521ms 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: 2025-06-17 10:26:43 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
2 34s267ms 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: 2025-06-17 10:52:25 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
3 33s507ms 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: 2025-06-17 10:47:53 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
4 31s333ms 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: 2025-06-17 10:04:20 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
5 31s83ms 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: 2025-06-17 10:14:15 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
6 31s35ms 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: 2025-06-17 10:13:29 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
7 30s540ms 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: 2025-06-17 10:48:18 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
8 30s397ms 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: 2025-06-17 10:40:51 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
9 30s222ms 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: 2025-06-17 10:18:28 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
10 29s993ms 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: 2025-06-17 10:44:05 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
11 29s975ms 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: 2025-06-17 10:04:04 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
12 29s769ms 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: 2025-06-17 10:53:06 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
13 29s484ms 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: 2025-06-17 10:35:19 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
14 29s447ms 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: 2025-06-17 10:35:20 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
15 29s394ms 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: 2025-06-17 10:08:51 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
16 29s361ms 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: 2025-06-17 10:08:57 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
17 29s333ms 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: 2025-06-17 10:19:18 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
18 29s75ms 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: 2025-06-17 10:23:52 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
19 28s844ms 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: 2025-06-17 10:28:51 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
20 25s508ms 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: 2025-06-17 10:31:37 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
Time consuming queries
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 1h3m46s 426 371ms 25s508ms 8s982ms 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 Jun 17 10 426 1h3m46s 8s982ms [ User: postgres - Total duration: 1h3m46s - Times executed: 426 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h26s - Times executed: 414 ]
[ Application: [unknown] - Total duration: 3m20s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 10:31:37 Duration: 25s508ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 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: 2025-06-17 10:35:53 Duration: 23s475ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('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: 2025-06-17 10:52:05 Duration: 22s786ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
2 58m48s 424 145ms 42s521ms 8s323ms 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 Jun 17 10 424 58m48s 8s323ms [ User: postgres - Total duration: 58m48s - Times executed: 424 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 56m17s - Times executed: 412 ]
[ Application: [unknown] - Total duration: 2m31s - 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: 2025-06-17 10:26:43 Duration: 42s521ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 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: 2025-06-17 10:52:25 Duration: 34s267ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 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: 2025-06-17 10:47:53 Duration: 33s507ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
3 19m58s 403 552ms 9s112ms 2s974ms 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 Jun 17 10 403 19m58s 2s974ms [ User: postgres - Total duration: 19m58s - Times executed: 403 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 18m52s - Times executed: 391 ]
[ 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: 2025-06-17 10:25:58 Duration: 9s112ms 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: 2025-06-17 10:22:29 Duration: 8s966ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 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: 2025-06-17 10:31:05 Duration: 8s736ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
4 2m33s 272 85ms 1s723ms 565ms 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 Jun 17 10 272 2m33s 565ms [ User: postgres - Total duration: 2m33s - Times executed: 272 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m17s - Times executed: 260 ]
[ Application: [unknown] - Total duration: 16s323ms - 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: 2025-06-17 10:31:22 Duration: 1s723ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver 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: 2025-06-17 10:51:06 Duration: 1s672ms 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: 2025-06-17 10:36:03 Duration: 1s657ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
5 1m59s 33,124 1ms 34ms 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 Jun 17 10 33,124 1m59s 3ms [ User: postgres - Total duration: 1m59s - Times executed: 33124 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m59s - Times executed: 33124 ]
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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 = 'CADCHF' OR dss.downloadersymbol = 'CADCHF') AND dss.enabled = 1;
Date: 2025-06-17 10:00:05 Duration: 34ms 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 = 'NKE.US' OR dss.downloadersymbol = 'NKE.US') AND dss.enabled = 1;
Date: 2025-06-17 10:30:05 Duration: 34ms 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 = 'SEKJPY' OR dss.downloadersymbol = 'SEKJPY') AND dss.enabled = 1;
Date: 2025-06-17 10:00:05 Duration: 33ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
6 1m 39,514 0ms 30ms 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 Jun 17 10 39,514 1m 1ms [ User: postgres - Total duration: 1m - Times executed: 39514 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m - Times executed: 39514 ]
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243203999300';
Date: 2025-06-17 10:30:05 Duration: 30ms 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 = '515840217506064300';
Date: 2025-06-17 10:00:05 Duration: 29ms 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 = '515840216985953300';
Date: 2025-06-17 10:00:06 Duration: 27ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
7 48s329ms 120 92ms 908ms 402ms 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 Jun 17 10 120 48s329ms 402ms [ User: postgres - Total duration: 48s329ms - Times executed: 120 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 48s329ms - Times executed: 120 ]
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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: 2025-06-17 10:04:00 Duration: 908ms 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: 2025-06-17 10:52:00 Duration: 904ms 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: 2025-06-17 10:04:00 Duration: 897ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
8 42s610ms 4 8s460ms 13s572ms 10s652ms select updateageforrelevantresults ();Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Jun 17 10 4 42s610ms 10s652ms [ User: postgres - Total duration: 42s610ms - Times executed: 4 ]
[ Application: psql - Total duration: 42s610ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-06-17 10:17:16 Duration: 13s572ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-06-17 10:47:14 Duration: 11s861ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-06-17 10:02:11 Duration: 8s715ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
9 39s401ms 6 5s168ms 8s612ms 6s566ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jun 17 10 6 39s401ms 6s566ms [ User: postgres - Total duration: 39s401ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 39s401ms - 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: 2025-06-17 10:00:11 Duration: 8s612ms 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: 2025-06-17 10:30:10 Duration: 7s216ms 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: 2025-06-17 10:10:09 Duration: 6s443ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
10 34s577ms 16 1s814ms 3s579ms 2s161ms 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 Jun 17 10 16 34s577ms 2s161ms [ User: postgres - Total duration: 34s577ms - Times executed: 16 ]
[ Application: psql - Total duration: 34s577ms - 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: 2025-06-17 10:31:16 Duration: 3s579ms 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: 2025-06-17 10:03:17 Duration: 3s90ms 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: 2025-06-17 10:18:17 Duration: 3s82ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 22s900ms 34 12ms 9s531ms 673ms select fixcandlegaps (?, false);Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jun 17 10 34 22s900ms 673ms [ User: postgres - Total duration: 22s900ms - Times executed: 34 ]
[ Application: psql - Total duration: 22s900ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-06-17 10:06:25 Duration: 9s531ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-06-17 10:06:08 Duration: 3s93ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('AXIORY', false);
Date: 2025-06-17 10:06:10 Duration: 2s88ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
12 18s204ms 12 1s284ms 1s828ms 1s517ms 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 #12
Day Hour Count Duration Avg duration Jun 17 10 12 18s204ms 1s517ms [ User: postgres - Total duration: 18s204ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 18s204ms - Times executed: 12 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '620' 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 = '620')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '620' 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 = '620' 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: 2025-06-17 10:51:44 Duration: 1s828ms 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: 2025-06-17 10:36:53 Duration: 1s741ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '617' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '617' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '617' 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: 2025-06-17 10:36:46 Duration: 1s710ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
13 15s941ms 16 671ms 1s633ms 996ms 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 #13
Day Hour Count Duration Avg duration Jun 17 10 16 15s941ms 996ms [ User: postgres - Total duration: 15s941ms - Times executed: 16 ]
[ Application: psql - Total duration: 15s941ms - 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: 2025-06-17 10:03:13 Duration: 1s633ms 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: 2025-06-17 10:18:13 Duration: 1s500ms 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: 2025-06-17 10:26:13 Duration: 1s391ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
14 13s103ms 8 1s230ms 2s555ms 1s637ms select updateresultsmaterializedview ();Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Jun 17 10 8 13s103ms 1s637ms [ User: postgres - Total duration: 13s103ms - Times executed: 8 ]
[ Application: psql - Total duration: 13s103ms - Times executed: 8 ]
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select updateresultsmaterializedview ();
Date: 2025-06-17 10:17:19 Duration: 2s555ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-06-17 10:35:35 Duration: 2s263ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-06-17 10:32:12 Duration: 1s601ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
15 11s831ms 164 18ms 367ms 72ms select distinct a.symbolid, p.resultuid, case when a.breakout >= ? then ? else ? end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient from relevance_autochartist_results p inner join autochartist_results a on p.resultuid = a.resultuid inner join autochartist_stocklist asl on a.symbolid = asl.symbolid where asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Jun 17 10 164 11s831ms 72ms [ User: postgres - Total duration: 11s831ms - Times executed: 164 ]
[ Application: [unknown] - Total duration: 11s831ms - Times executed: 164 ]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2025-06-17 10:45:06 Duration: 367ms 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: 2025-06-17 10:31:18 Duration: 316ms 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 'ATFX - 1';
Date: 2025-06-17 10:31:30 Duration: 259ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
16 11s301ms 8,174 0ms 84ms 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 Jun 17 10 8,174 11s301ms 1ms [ User: postgres - Total duration: 11s301ms - Times executed: 8174 ]
[ Application: [unknown] - Total duration: 11s301ms - Times executed: 8174 ]
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INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('5158402486269643000.2321|45824.9896|45825.4167|45825.125|45825.4375|2680.16|2585.88|2523.32|2569.24', 515840248626964300, 3.000000000000000000000000000000, 'Triangle', 4, '2025-06-17 07:57:36'::timestamp without time zone, 1, 0.190123375801421384800000000000, 0.232103854297226158700000000000, 0.417080731845113073000000000000, 1.000000000000000000000000000000, 0.654310280454370230000000000000, 2602.395517894392014000000000000000, 2631.943242946540522000000000000000, '2025-06-17 10:45:00'::timestamp without time zone, '2025-06-17 16:15:00'::timestamp without time zone, '2025-06-16 18:45:00'::timestamp without time zone, '2025-06-17 10:45:00'::timestamp without time zone, 2627.190000000000054000000000000000, 2578.981463414634163000000000000000, '2025-06-16 23:45:00'::timestamp without time zone, '2025-06-17 10:00:00'::timestamp without time zone, '2025-06-17 03:00:00'::timestamp without time zone, '2025-06-17 10:30:00'::timestamp without time zone, 2680.159999999999854000000000000000, 2585.880000000000109000000000000000, 2523.320000000000164000000000000000, 2569.239999999999782000000000000000, 1.530666666666653963000000000000, - 2.299512195121944824000000000000, 1.368240575837407436000000000000, 0.269134377638254429500000000000, 'Continuation', 2.308536585365800420000000000000, '2025-06-17 10:45:00'::timestamp without time zone, 2581.289999999999964000000000000000, 44, 0, 39.339999999999996300000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 10:02:01 Duration: 84ms 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 ('5158402461216783001|45820.6667|45824.7083|45821.7083|45824.6667|471.84|468.91|458.04|463.01', 515840246121678300, 2.000000000000000000000000000000, 'Triangle', 5, '2025-06-17 07:57:34'::timestamp without time zone, - 1, 0.126194370737100602900000000000, 1.000000000000000000000000000000, 0.354993539590814311000000000000, 0.410047842317565525200000000000, 0.211514719477086388100000000000, 453.909482433707978600000000000000, 458.564784347378349600000000000000, '2025-06-17 10:00:00'::timestamp without time zone, '2025-06-19 19:00:00'::timestamp without time zone, '2025-06-12 12:00:00'::timestamp without time zone, '2025-06-17 10:00:00'::timestamp without time zone, 466.060000000000002200000000000000, 464.873749999999972700000000000000, '2025-06-12 16:00:00'::timestamp without time zone, '2025-06-16 17:00:00'::timestamp without time zone, '2025-06-13 17:00:00'::timestamp without time zone, '2025-06-16 16:00:00'::timestamp without time zone, 471.839999999999975000000000000000, 468.910000000000025000000000000000, 458.040000000000020500000000000000, 463.009999999999990900000000000000, 0.621249999999996305200000000000, - 0.154210526315786827800000000000, 1.930186363566327001000000000000, 0.481915311974155380400000000000, 'Reversal', - 2.983749999999986358000000000000, '2025-06-17 10:00:00'::timestamp without time zone, 461.889999999999986400000000000000, 21, 0, 4.603749999999990905000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 10:01:59 Duration: 66ms 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 ('515840246121678300-1|45819.4583|45824.7083|45818.4167|45821.4167|482.26|468.91|466.81|456.84', 515840246121678300, 3.000000000000000000000000000000, 'Channel Down', 4, '2025-06-17 07:57:34'::timestamp without time zone, - 1, 0.177368834412502285300000000000, - 1.000000000000000000000000000000, 0.467191615759681766400000000000, 0.511624655141465711800000000000, 0.500606103379527711600000000000, 454.681955253219484800000000000000, 458.886648022174767900000000000000, '2025-06-17 10:00:00'::timestamp without time zone, '2025-06-20 22:00:00'::timestamp without time zone, '2025-06-09 11:00:00'::timestamp without time zone, '2025-06-17 10:00:00'::timestamp without time zone, 476.959999999999979600000000000000, 460.360000000000013600000000000000, '2025-06-11 11:00:00'::timestamp without time zone, '2025-06-16 17:00:00'::timestamp without time zone, '2025-06-10 10:00:00'::timestamp without time zone, '2025-06-13 10:00:00'::timestamp without time zone, 482.259999999999990900000000000000, 468.910000000000025000000000000000, 466.810000000000002200000000000000, 456.839999999999975000000000000000, - 0.369259259259260286200000000000, - 0.404545454545453486700000000000, 1.636081292743599036000000000000, 0.388783427550188076500000000000, 'Continuation', 0.000000000000000000000000000000, '2025-06-17 10:00:00'::timestamp without time zone, 461.889999999999986400000000000000, 45, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 10:01:59 Duration: 62ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
17 8s447ms 6 1s95ms 2s51ms 1s407ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Jun 17 10 6 8s447ms 1s407ms [ User: postgres - Total duration: 8s447ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 8s447ms - Times executed: 6 ]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-17 10:31:18 Duration: 2s51ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-17 10:01:18 Duration: 1s756ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-17 10:46:17 Duration: 1s314ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
18 7s615ms 6,780 0ms 4ms 1ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Jun 17 10 6,780 7s615ms 1ms [ User: postgres - Total duration: 7s615ms - Times executed: 6780 ]
[ Application: [unknown] - Total duration: 7s615ms - Times executed: 6780 ]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 52, schedule: 0 14 * * 1 Africa/Johannesburg', NULL, NULL);
Date: 2025-06-17 10:26:49 Duration: 4ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 87, schedule: 0 6 * * 1 Africa/Johannesburg', NULL, NULL);
Date: 2025-06-17 10:12:49 Duration: 3ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 87, schedule: 0 6 * * 1 Africa/Johannesburg', NULL, NULL);
Date: 2025-06-17 10:40:49 Duration: 3ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
19 7s218ms 6,078 0ms 24ms 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 #19
Day Hour Count Duration Avg duration Jun 17 10 6,078 7s218ms 1ms [ User: postgres - Total duration: 7s218ms - Times executed: 6078 ]
[ Application: [unknown] - Total duration: 7s218ms - Times executed: 6078 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 11:15:00', '87.8305', '87.9085', '87.81', '87.9015', '1431', '515840230538789300', '0', '2025-06-17 10:30:07.558', '2025-06-17 10:30:07.306') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '87.8305', high = '87.9085', low = '87.81', close = '87.9015', volume = '1431', bsf = '0', sastdatetimewritten = '2025-06-17 10:30:07.558', sastdatetimereceived = '2025-06-17 10:30:07.306';
Date: 2025-06-17 10:30:07 Duration: 24ms 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 ('2025-06-17 11:15:00', '27.05', '27.14', '26.94', '27.13', '103', '515840246003549300', '0', '2025-06-17 10:30:05.858', '2025-06-17 10:30:05.767') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '27.05', high = '27.14', low = '26.94', close = '27.13', volume = '103', bsf = '0', sastdatetimewritten = '2025-06-17 10:30:05.858', sastdatetimereceived = '2025-06-17 10:30:05.767';
Date: 2025-06-17 10:30:05 Duration: 19ms 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 ('2025-06-17 11:00:00', '4.27387', '4.27447', '4.27195', '4.27215', '807', '515840243918956300', '0', '2025-06-17 10:15:05.747', '2025-06-17 10:15:05.622') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '4.27387', high = '4.27447', low = '4.27195', close = '4.27215', volume = '807', bsf = '0', sastdatetimewritten = '2025-06-17 10:15:05.747', sastdatetimereceived = '2025-06-17 10:15:05.622';
Date: 2025-06-17 10:15:05 Duration: 16ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
20 6s201ms 164 17ms 145ms 37ms 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 #20
Day Hour Count Duration Avg duration Jun 17 10 164 6s201ms 37ms [ User: postgres - Total duration: 6s201ms - Times executed: 164 ]
[ Application: [unknown] - Total duration: 6s201ms - Times executed: 164 ]
-
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: 2025-06-17 10:31:20 Duration: 145ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
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 'Alpari - 1';
Date: 2025-06-17 10:30:40 Duration: 126ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
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 'Alpari - 1';
Date: 2025-06-17 10:16:58 Duration: 124ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 52,799 290ms 0ms 15ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jun 17 10 52,798 290ms 0ms 11 1 0ms 0ms [ User: postgres - Total duration: 290ms - Times executed: 52799 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 275ms - Times executed: 52503 ]
[ Application: [unknown] - Total duration: 14ms - Times executed: 296 ]
-
select 1;
Date: 2025-06-17 10:30:05 Duration: 15ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-06-17 10:15:05 Duration: 15ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-06-17 10:00:07 Duration: 13ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
2 39,514 1m 0ms 30ms 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 Jun 17 10 39,514 1m 1ms [ User: postgres - Total duration: 1m - Times executed: 39514 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m - Times executed: 39514 ]
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243203999300';
Date: 2025-06-17 10:30:05 Duration: 30ms 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 = '515840217506064300';
Date: 2025-06-17 10:00:05 Duration: 29ms 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 = '515840216985953300';
Date: 2025-06-17 10:00:06 Duration: 27ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
3 33,124 1m59s 1ms 34ms 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 Jun 17 10 33,124 1m59s 3ms [ User: postgres - Total duration: 1m59s - Times executed: 33124 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m59s - Times executed: 33124 ]
-
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 = 'CADCHF' OR dss.downloadersymbol = 'CADCHF') AND dss.enabled = 1;
Date: 2025-06-17 10:00:05 Duration: 34ms 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 = 'NKE.US' OR dss.downloadersymbol = 'NKE.US') AND dss.enabled = 1;
Date: 2025-06-17 10:30:05 Duration: 34ms 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 = 'SEKJPY' OR dss.downloadersymbol = 'SEKJPY') AND dss.enabled = 1;
Date: 2025-06-17 10:00:05 Duration: 33ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
4 8,174 11s301ms 0ms 84ms 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 Jun 17 10 8,174 11s301ms 1ms [ User: postgres - Total duration: 11s301ms - Times executed: 8174 ]
[ Application: [unknown] - Total duration: 11s301ms - Times executed: 8174 ]
-
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 ('5158402486269643000.2321|45824.9896|45825.4167|45825.125|45825.4375|2680.16|2585.88|2523.32|2569.24', 515840248626964300, 3.000000000000000000000000000000, 'Triangle', 4, '2025-06-17 07:57:36'::timestamp without time zone, 1, 0.190123375801421384800000000000, 0.232103854297226158700000000000, 0.417080731845113073000000000000, 1.000000000000000000000000000000, 0.654310280454370230000000000000, 2602.395517894392014000000000000000, 2631.943242946540522000000000000000, '2025-06-17 10:45:00'::timestamp without time zone, '2025-06-17 16:15:00'::timestamp without time zone, '2025-06-16 18:45:00'::timestamp without time zone, '2025-06-17 10:45:00'::timestamp without time zone, 2627.190000000000054000000000000000, 2578.981463414634163000000000000000, '2025-06-16 23:45:00'::timestamp without time zone, '2025-06-17 10:00:00'::timestamp without time zone, '2025-06-17 03:00:00'::timestamp without time zone, '2025-06-17 10:30:00'::timestamp without time zone, 2680.159999999999854000000000000000, 2585.880000000000109000000000000000, 2523.320000000000164000000000000000, 2569.239999999999782000000000000000, 1.530666666666653963000000000000, - 2.299512195121944824000000000000, 1.368240575837407436000000000000, 0.269134377638254429500000000000, 'Continuation', 2.308536585365800420000000000000, '2025-06-17 10:45:00'::timestamp without time zone, 2581.289999999999964000000000000000, 44, 0, 39.339999999999996300000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 10:02:01 Duration: 84ms 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 ('5158402461216783001|45820.6667|45824.7083|45821.7083|45824.6667|471.84|468.91|458.04|463.01', 515840246121678300, 2.000000000000000000000000000000, 'Triangle', 5, '2025-06-17 07:57:34'::timestamp without time zone, - 1, 0.126194370737100602900000000000, 1.000000000000000000000000000000, 0.354993539590814311000000000000, 0.410047842317565525200000000000, 0.211514719477086388100000000000, 453.909482433707978600000000000000, 458.564784347378349600000000000000, '2025-06-17 10:00:00'::timestamp without time zone, '2025-06-19 19:00:00'::timestamp without time zone, '2025-06-12 12:00:00'::timestamp without time zone, '2025-06-17 10:00:00'::timestamp without time zone, 466.060000000000002200000000000000, 464.873749999999972700000000000000, '2025-06-12 16:00:00'::timestamp without time zone, '2025-06-16 17:00:00'::timestamp without time zone, '2025-06-13 17:00:00'::timestamp without time zone, '2025-06-16 16:00:00'::timestamp without time zone, 471.839999999999975000000000000000, 468.910000000000025000000000000000, 458.040000000000020500000000000000, 463.009999999999990900000000000000, 0.621249999999996305200000000000, - 0.154210526315786827800000000000, 1.930186363566327001000000000000, 0.481915311974155380400000000000, 'Reversal', - 2.983749999999986358000000000000, '2025-06-17 10:00:00'::timestamp without time zone, 461.889999999999986400000000000000, 21, 0, 4.603749999999990905000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 10:01:59 Duration: 66ms 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 ('515840246121678300-1|45819.4583|45824.7083|45818.4167|45821.4167|482.26|468.91|466.81|456.84', 515840246121678300, 3.000000000000000000000000000000, 'Channel Down', 4, '2025-06-17 07:57:34'::timestamp without time zone, - 1, 0.177368834412502285300000000000, - 1.000000000000000000000000000000, 0.467191615759681766400000000000, 0.511624655141465711800000000000, 0.500606103379527711600000000000, 454.681955253219484800000000000000, 458.886648022174767900000000000000, '2025-06-17 10:00:00'::timestamp without time zone, '2025-06-20 22:00:00'::timestamp without time zone, '2025-06-09 11:00:00'::timestamp without time zone, '2025-06-17 10:00:00'::timestamp without time zone, 476.959999999999979600000000000000, 460.360000000000013600000000000000, '2025-06-11 11:00:00'::timestamp without time zone, '2025-06-16 17:00:00'::timestamp without time zone, '2025-06-10 10:00:00'::timestamp without time zone, '2025-06-13 10:00:00'::timestamp without time zone, 482.259999999999990900000000000000, 468.910000000000025000000000000000, 466.810000000000002200000000000000, 456.839999999999975000000000000000, - 0.369259259259260286200000000000, - 0.404545454545453486700000000000, 1.636081292743599036000000000000, 0.388783427550188076500000000000, 'Continuation', 0.000000000000000000000000000000, '2025-06-17 10:00:00'::timestamp without time zone, 461.889999999999986400000000000000, 45, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 10:01:59 Duration: 62ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
5 6,780 7s615ms 0ms 4ms 1ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Jun 17 10 6,780 7s615ms 1ms [ User: postgres - Total duration: 7s615ms - Times executed: 6780 ]
[ Application: [unknown] - Total duration: 7s615ms - Times executed: 6780 ]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 52, schedule: 0 14 * * 1 Africa/Johannesburg', NULL, NULL);
Date: 2025-06-17 10:26:49 Duration: 4ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 87, schedule: 0 6 * * 1 Africa/Johannesburg', NULL, NULL);
Date: 2025-06-17 10:12:49 Duration: 3ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 87, schedule: 0 6 * * 1 Africa/Johannesburg', NULL, NULL);
Date: 2025-06-17 10:40:49 Duration: 3ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
6 6,078 7s218ms 0ms 24ms 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 #6
Day Hour Count Duration Avg duration Jun 17 10 6,078 7s218ms 1ms [ User: postgres - Total duration: 7s218ms - Times executed: 6078 ]
[ Application: [unknown] - Total duration: 7s218ms - Times executed: 6078 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 11:15:00', '87.8305', '87.9085', '87.81', '87.9015', '1431', '515840230538789300', '0', '2025-06-17 10:30:07.558', '2025-06-17 10:30:07.306') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '87.8305', high = '87.9085', low = '87.81', close = '87.9015', volume = '1431', bsf = '0', sastdatetimewritten = '2025-06-17 10:30:07.558', sastdatetimereceived = '2025-06-17 10:30:07.306';
Date: 2025-06-17 10:30:07 Duration: 24ms 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 ('2025-06-17 11:15:00', '27.05', '27.14', '26.94', '27.13', '103', '515840246003549300', '0', '2025-06-17 10:30:05.858', '2025-06-17 10:30:05.767') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '27.05', high = '27.14', low = '26.94', close = '27.13', volume = '103', bsf = '0', sastdatetimewritten = '2025-06-17 10:30:05.858', sastdatetimereceived = '2025-06-17 10:30:05.767';
Date: 2025-06-17 10:30:05 Duration: 19ms 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 ('2025-06-17 11:00:00', '4.27387', '4.27447', '4.27195', '4.27215', '807', '515840243918956300', '0', '2025-06-17 10:15:05.747', '2025-06-17 10:15:05.622') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '4.27387', high = '4.27447', low = '4.27195', close = '4.27215', volume = '807', bsf = '0', sastdatetimewritten = '2025-06-17 10:15:05.747', sastdatetimereceived = '2025-06-17 10:15:05.622';
Date: 2025-06-17 10:15:05 Duration: 16ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
7 3,471 2s173ms 0ms 8ms 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 Jun 17 10 3,471 2s173ms 0ms [ User: postgres - Total duration: 2s173ms - Times executed: 3471 ]
[ Application: [unknown] - Total duration: 2s173ms - Times executed: 3471 ]
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 11:00:00', '106.508', '106.751', '106.459', '106.716', '4011', '515840247880157300', '0', '2025-06-17 10:30:47.381', '2025-06-17 10:30:46.412') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '106.508', high = '106.751', low = '106.459', close = '106.716', volume = '4011', bsf = '0', sastdatetimewritten = '2025-06-17 10:30:47.381', sastdatetimereceived = '2025-06-17 10:30:46.412';
Date: 2025-06-17 10:30:47 Duration: 8ms 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 ('2025-06-17 10:30:00', '1.35593', '1.35728', '1.35529', '1.35639', '2489', '515840247884826300', '0', '2025-06-17 10:00:55.186', '2025-06-17 10:00:55.05') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '1.35593', high = '1.35728', low = '1.35529', close = '1.35639', volume = '2489', bsf = '0', sastdatetimewritten = '2025-06-17 10:00:55.186', sastdatetimereceived = '2025-06-17 10:00:55.05';
Date: 2025-06-17 10:00:55 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 11:00:00', '0.53121', '0.53153', '0.53098', '0.53145', '1800', '515840247868761300', '0', '2025-06-17 10:30:44.756', '2025-06-17 10:30:44.584') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.53121', high = '0.53153', low = '0.53098', close = '0.53145', volume = '1800', bsf = '0', sastdatetimewritten = '2025-06-17 10:30:44.756', sastdatetimereceived = '2025-06-17 10:30:44.584';
Date: 2025-06-17 10:30:44 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
8 3,064 5s301ms 0ms 36ms 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 #8
Day Hour Count Duration Avg duration Jun 17 10 3,064 5s301ms 1ms [ User: postgres - Total duration: 5s301ms - Times executed: 3064 ]
[ Application: [unknown] - Total duration: 5s301ms - Times executed: 3064 ]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, - 1, 2, '2025-06-17 07:57:34'::timestamp without time zone, '', 0.500000000000000000000000000000, 4, 54, 654.360000000000013600000000000000, '2025-06-17 10:15:00', '2025-06-17 08:15:00', '2025-06-17 07:15:00', '2025-06-16 20:45:00', '', '', '', '', '', '', 135, 653.777000000000043600000000000000, '2025-06-17 10:45:00'::timestamp without time zone, '2025-06-17 10:45:00', 0.000000000000000000000000000000, 0.582999999999998408400000000000, 1, 515840248623286300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840248623286300|654.36|2|2025-06-17 10:45:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-06-16 20:45:00', 646.419999999999959000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 10:02:00 Duration: 36ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (9.000000000000000000000000000000, - 1, 2, '2025-06-17 07:57:34'::timestamp without time zone, '2025-06-17 10:45:00', 0.047245000000000592080000000000, 4, 258, 24.117429999999998810000000000000, '2025-06-16 15:45:00', '2025-06-16 13:30:00', '2025-06-12 23:45:00', '2025-06-12 18:15:00', '', '', '', '', '', '', 455, 24.102025999999998620000000000000, '2025-06-17 10:45:00'::timestamp without time zone, '2025-06-17 10:45:00', 24.158069999999998600000000000000, 0.015403999999999999290000000000, - 1, 515840233889653300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840233889653300|24.11743|2|2025-06-17 10:45:00|2025-06-17 10:45:00|-1|-1', 24.182628099999998740000000000000, 0.065198099999999925560000000000, 2, '2025-06-12 18:15:00', 24.206389999999998960000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 10:01:59 Duration: 24ms 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 (8.000000000000000000000000000000, - 1, 2, '2025-06-17 07:57:36'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 39, 1.356735000000000024000000000000, '2025-06-17 07:45:00', '2025-06-16 23:15:00', '2025-06-16 22:00:00', '', '', '', '', '', '', '', 78, 1.356661000000000117000000000000, '2025-06-17 07:45:00'::timestamp without time zone, '2025-06-17 07:45:00', 0.000000000000000000000000000000, 0.000078000000000000296740000000, 1, 515840249730262300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249730262300|1.356735|2|2025-06-17 07:45:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-06-16 22:00:00', 1.356735000000000024000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 10:02:01 Duration: 22ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
9 2,718 2s140ms 0ms 37ms 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 #9
Day Hour Count Duration Avg duration Jun 17 10 2,718 2s140ms 0ms [ User: postgres - Total duration: 2s140ms - Times executed: 2718 ]
[ Application: [unknown] - Total duration: 2s140ms - Times executed: 2718 ]
-
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', '2025-06-17 07:57:38'::timestamp without time zone, 1, '2025-06-16 00:00:00'::timestamp without time zone, '2025-06-17 10:00:00'::timestamp without time zone, 1.565020000000000078000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 1.573280000000000012000000000000, '2025-06-16 17:00:00'::timestamp without time zone, 1.567180000000000018000000000000, '2025-06-17 00:00:00'::timestamp without time zone, 1.570889999999999898000000000000, '2025-06-17 09:00:00'::timestamp without time zone, 1.564789999999999903000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.829707744405192126900000000000, - 1.000000000000000000000000000000, 3.898322838187041839000000000000, 23, 1.570889999999999898000000000000, 1.568560007331069928000000000000, 1.574660007331069922000000000000, 1.569585523404579908000000000000, 1.572549319861949790000000000000, 1.567839999999999900000000000000, 1.567119992668929873000000000000, 515840216984700300, 0.340584511189615801700000000000, 'BC=0.618*AB (0.608) ', 0, 'ABCD|1|2025-06-16 00:00:00|1.56502|-1|4|23|BC=0.618*AB (0.608)|0|515840216984700300|1899-12-29 00:00:00|2025-06-16 17:00:00|2025-06-17 00:00:00|2025-06-17 09:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 10:02:03 Duration: 37ms 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', '2025-06-17 07:57:36'::timestamp without time zone, - 1, '2025-06-17 04:00:00'::timestamp without time zone, '2025-06-17 10:45:00'::timestamp without time zone, 2591.119999999999891000000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 2556.880000000000109000000000000000, '2025-06-17 05:30:00'::timestamp without time zone, 2618.010000000000218000000000000000, '2025-06-17 06:00:00'::timestamp without time zone, 2569.239999999999782000000000000000, '2025-06-17 10:30:00'::timestamp without time zone, 2630.369999999999891000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.876205946387257572600000000000, - 1.000000000000000000000000000000, 25.419720309920784020000000000000, 22, 2569.239999999999782000000000000000, 2592.589582270768915000000000000000, 2531.459582270768806000000000000000, 2582.312566275085828000000000000000, 2552.611438826064841000000000000000, 2599.804999999999836000000000000000, 2607.020417729230758000000000000000, 515840248626964300, 0.247588107225484854700000000000, 'BC=0.786*AB (0.798) ', 0, 'ABCD|-1|2025-06-17 04:00:00|2591.12|-1|4|22|BC=0.786*AB (0.798)|0|515840248626964300|1899-12-29 00:00:00|2025-06-17 05:30:00|2025-06-17 06:00:00|2025-06-17 10:30:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 10:02:01 Duration: 25ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (3.000000000000000000000000000000, 'Gartley', '2025-06-17 07:57:37'::timestamp without time zone, - 1, '2025-06-16 01:00:00'::timestamp without time zone, '2025-06-17 10:30:00'::timestamp without time zone, 76.650000000000005680000000000000, - 1.000000000000000000000000000000, 5, 76.650000000000005680000000000000, '2025-06-16 01:00:00'::timestamp without time zone, 69.400000000000005680000000000000, '2025-06-16 17:30:00'::timestamp without time zone, 73.689999999999997720000000000000, '2025-06-17 02:30:00'::timestamp without time zone, 71.150000000000005680000000000000, '2025-06-17 09:30:00'::timestamp without time zone, 75.099597489050012200000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.702921441870672070200000000000, - 1.000000000000000000000000000000, 0.851404655731247128600000000000, 85, 71.150000000000005680000000000000, 72.658611999132929780000000000000, 68.709014510082923260000000000000, 71.994615981277931380000000000000, 70.075631875362546450000000000000, 73.124798744525008940000000000000, 73.590985489917088100000000000000, 515840233910510300, 0.445561771989902932800000000000, 'BC=0.618*AB (0.592) ', 0, 'Gartley|-1|2025-06-16 01:00:00|76.65|-1|5|85|BC=0.618*AB (0.592)|0|515840233910510300|2025-06-16 01:00:00|2025-06-16 17:30:00|2025-06-17 02:30:00|2025-06-17 09:30:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 10:02:03 Duration: 23ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
10 2,252 1s108ms 0ms 8ms 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 #10
Day Hour Count Duration Avg duration Jun 17 10 2,252 1s108ms 0ms [ User: postgres - Total duration: 1s108ms - Times executed: 2252 ]
[ Application: [unknown] - Total duration: 1s108ms - Times executed: 2252 ]
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 10:00:00', '0.53112', '0.53182', '0.53076', '0.53122', '4699', '515840247868983300', '0', '2025-06-17 10:00:42.734', '2025-06-17 10:00:42.684') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.53112', high = '0.53182', low = '0.53076', close = '0.53122', volume = '4699', bsf = '0', sastdatetimewritten = '2025-06-17 10:00:42.734', sastdatetimereceived = '2025-06-17 10:00:42.684';
Date: 2025-06-17 10:00:42 Duration: 8ms 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 ('2025-06-17 10:00:00', '4.53', '4.56', '4.52', '4.54', '102', '515840247949018300', '0', '2025-06-17 10:02:56.108', '2025-06-17 10:02:56.041') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '4.53', high = '4.56', low = '4.52', close = '4.54', volume = '102', bsf = '0', sastdatetimewritten = '2025-06-17 10:02:56.108', sastdatetimereceived = '2025-06-17 10:02:56.041';
Date: 2025-06-17 10:02:56 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 ('2025-06-17 10:00:00', '1.35615', '1.35728', '1.35529', '1.35639', '5356', '515840247885064300', '0', '2025-06-17 10:00:55.037', '2025-06-17 10:00:54.953') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '1.35615', high = '1.35728', low = '1.35529', close = '1.35639', volume = '5356', bsf = '0', sastdatetimewritten = '2025-06-17 10:00:55.037', sastdatetimereceived = '2025-06-17 10:00:54.953';
Date: 2025-06-17 10:00:55 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
11 2,037 2s248ms 0ms 31ms 1ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jun 17 10 2,037 2s248ms 1ms [ User: postgres - Total duration: 2s248ms - Times executed: 2037 ]
[ Application: [unknown] - Total duration: 2s248ms - Times executed: 2037 ]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-06-17 10:00:00', reason = 'Emerging pattern broke out in the wrong direction.' WHERE uniqueIndex = '515840233364883300-1|45810.4167|45820.4167|45817.6667|45824.4167|16.206|16.308|15.888|16.096' and relevant = 1;
Date: 2025-06-17 10:02:00 Duration: 31ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-06-17 10:45:00', reason = 'Price has moved too far in the wrong direction' WHERE uniqueIndex = '5158402338896533001|45825.3021|45825.3542|45825.3333|45825.3646|24.2025|24.1941|24.1467|24.1438' and relevant = 1;
Date: 2025-06-17 10:01:59 Duration: 19ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-06-17 10:00:00', reason = 'Emerging pattern broke out in the wrong direction.' WHERE uniqueIndex = '500991628274271200-1|45821.5833|45824.75|45824.0417|45825.125|38119.7|38630.7|37794.7|38322.7' and relevant = 1;
Date: 2025-06-17 10:02:00 Duration: 15ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
12 1,998 2s606ms 0ms 23ms 1ms 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 Jun 17 10 1,998 2s606ms 1ms [ User: postgres - Total duration: 2s606ms - Times executed: 1998 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s603ms - Times executed: 1993 ]
[ Application: [unknown] - Total duration: 2ms - Times executed: 5 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ) SELECT a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, CASE WHEN a.old_resultuid = '606306203563335301' 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 = '606306203563335301' OR a.resultuid = '606306203563335301') AND dtt.dayofweek = 3;
Date: 2025-06-17 10:01:05 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ) SELECT a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, CASE WHEN a.old_resultuid = '606306437710473301' 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 = '606306437710473301' OR a.resultuid = '606306437710473301') AND dtt.dayofweek = 3;
Date: 2025-06-17 10:17:06 Duration: 19ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ) SELECT a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, CASE WHEN a.old_resultuid = '606306206066119301' 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 = '606306206066119301' OR a.resultuid = '606306206066119301') AND dtt.dayofweek = 3;
Date: 2025-06-17 10:31:04 Duration: 18ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
13 1,296 20ms 0ms 7ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jun 17 10 1,296 20ms 0ms [ User: postgres - Total duration: 20ms - Times executed: 1296 ]
[ Application: [unknown] - Total duration: 20ms - Times executed: 1296 ]
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SET extra_float_digits = 3;
Date: 2025-06-17 10:31:04 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: [unknown] Bind query: yes
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SET extra_float_digits = 3;
Date: 2025-06-17 10:54:05 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: [unknown] Bind query: yes
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SET extra_float_digits = 3;
Date: 2025-06-17 10:53:58 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: [unknown] Bind query: yes
14 1,270 16ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Jun 17 10 1,270 16ms 0ms [ User: postgres - Total duration: 16ms - Times executed: 1270 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 16ms - Times executed: 1270 ]
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-17 10:09:30 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-17 10:00:07 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-17 10:56:47 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
15 1,022 650ms 0ms 19ms 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 #15
Day Hour Count Duration Avg duration Jun 17 10 1,022 650ms 0ms [ User: postgres - Total duration: 650ms - Times executed: 1022 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 650ms - Times executed: 1022 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '606306442612296303' 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 = '606306442612296303' OR a.resultuid = '606306442612296303') AND dtt.dayofweek = 3;
Date: 2025-06-17 10:13:01 Duration: 19ms 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 = '606306442024422303' 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 = '606306442024422303' OR a.resultuid = '606306442024422303') AND dtt.dayofweek = 3;
Date: 2025-06-17 10:26:13 Duration: 17ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '606306321776954303' 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 = '606306321776954303' OR a.resultuid = '606306321776954303') AND dtt.dayofweek = 3;
Date: 2025-06-17 10:01:08 Duration: 8ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
16 999 360ms 0ms 4ms 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars as length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternstartprice, resy1, supporty1, dtt.timezone, cps.pip, newlevels.profit from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern left join currencypips cps on cps.symbol = s.symbol left join lateral calc_cp_signal (a.resultuid) newlevels on true where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Jun 17 10 999 360ms 0ms [ User: postgres - Total duration: 360ms - Times executed: 999 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 360ms - Times executed: 999 ]
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SELECT CASE WHEN a.old_resultuid = '606306558138921301' THEN a.old_resultuid ELSE a.resultuid END as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars AS length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternStartPrice, resy1, supporty1, dtt.timezone, cps.pip, newLevels.profit FROM autochartist_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid INNER JOIN patterns p ON p.patternname = a.pattern LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT JOIN LATERAL calc_cp_signal (a.resultuid) newLevels on true WHERE (a.old_resultuid = '606306558138921301' OR a.resultuid = '606306558138921301') AND dtt.dayofweek = 3;
Date: 2025-06-17 10:47:46 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '606306439267884301' THEN a.old_resultuid ELSE a.resultuid END as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars AS length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternStartPrice, resy1, supporty1, dtt.timezone, cps.pip, newLevels.profit FROM autochartist_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid INNER JOIN patterns p ON p.patternname = a.pattern LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT JOIN LATERAL calc_cp_signal (a.resultuid) newLevels on true WHERE (a.old_resultuid = '606306439267884301' OR a.resultuid = '606306439267884301') AND dtt.dayofweek = 3;
Date: 2025-06-17 10:30:01 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '606306616311275301' THEN a.old_resultuid ELSE a.resultuid END as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars AS length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternStartPrice, resy1, supporty1, dtt.timezone, cps.pip, newLevels.profit FROM autochartist_results a INNER JOIN downloadersymbolsettings dss ON a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN symbols s ON a.symbolid = s.symbolid INNER JOIN patterns p ON p.patternname = a.pattern LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT JOIN LATERAL calc_cp_signal (a.resultuid) newLevels on true WHERE (a.old_resultuid = '606306616311275301' OR a.resultuid = '606306616311275301') AND dtt.dayofweek = 3;
Date: 2025-06-17 10:57:32 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
17 966 4s969ms 3ms 13ms 5ms select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Jun 17 10 966 4s969ms 5ms [ User: postgres - Total duration: 4s969ms - Times executed: 966 ]
[ Application: [unknown] - Total duration: 4s969ms - Times executed: 966 ]
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select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;
Date: 2025-06-17 10:52:01 Duration: 13ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
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select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;
Date: 2025-06-17 10:45:18 Duration: 11ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
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select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;
Date: 2025-06-17 10:52:06 Duration: 10ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
18 883 2s49ms 0ms 23ms 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 #18
Day Hour Count Duration Avg duration Jun 17 10 883 2s49ms 2ms [ User: postgres - Total duration: 2s49ms - Times executed: 883 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s49ms - Times executed: 883 ]
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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 = '515840245858969300' 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: 2025-06-17 10:52:04 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 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 = '515840233921111300' 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: 2025-06-17 10:00:05 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 = '515840246009750300' 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: 2025-06-17 10:47:47 Duration: 18ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
19 777 1s211ms 0ms 7ms 1ms select s.symbolid, dss.downloadfrequency, dss.downloadersymbol from downloadersymbolsettings dss inner join symbols s on dss.symbolid = s.symbolid where dss.classname = ? and s.deleted = ? and dss.enabled = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Jun 17 10 777 1s211ms 1ms [ User: postgres - Total duration: 1s211ms - Times executed: 777 ]
[ Application: [unknown] - Total duration: 1s211ms - Times executed: 777 ]
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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: 2025-06-17 10:30:59 Duration: 7ms 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 = 'HOTFOREX' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-17 10:30:58 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 = 'ICMARKETS-AU-MT5' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-17 10:47:35 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
20 777 146ms 0ms 1ms 0ms select downloadersymbol, spike_threshold from price_datafeed_spike_threshold where classname = ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Jun 17 10 777 146ms 0ms [ User: postgres - Total duration: 146ms - Times executed: 777 ]
[ Application: [unknown] - Total duration: 146ms - Times executed: 777 ]
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SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'AXIORY';
Date: 2025-06-17 10:30:53 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'GLOBALGTMT5';
Date: 2025-06-17 10:30:46 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'ATFX';
Date: 2025-06-17 10:00:30 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 8s460ms 13s572ms 10s652ms 4 42s610ms select updateageforrelevantresults ();Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jun 17 10 4 42s610ms 10s652ms [ User: postgres - Total duration: 42s610ms - Times executed: 4 ]
[ Application: psql - Total duration: 42s610ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-06-17 10:17:16 Duration: 13s572ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-06-17 10:47:14 Duration: 11s861ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-06-17 10:02:11 Duration: 8s715ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
2 371ms 25s508ms 8s982ms 426 1h3m46s 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 Jun 17 10 426 1h3m46s 8s982ms [ User: postgres - Total duration: 1h3m46s - Times executed: 426 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h26s - Times executed: 414 ]
[ Application: [unknown] - Total duration: 3m20s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 10:31:37 Duration: 25s508ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 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: 2025-06-17 10:35:53 Duration: 23s475ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('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: 2025-06-17 10:52:05 Duration: 22s786ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
3 145ms 42s521ms 8s323ms 424 58m48s 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 Jun 17 10 424 58m48s 8s323ms [ User: postgres - Total duration: 58m48s - Times executed: 424 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 56m17s - Times executed: 412 ]
[ Application: [unknown] - Total duration: 2m31s - 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: 2025-06-17 10:26:43 Duration: 42s521ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 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: 2025-06-17 10:52:25 Duration: 34s267ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 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: 2025-06-17 10:47:53 Duration: 33s507ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
4 5s168ms 8s612ms 6s566ms 6 39s401ms 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 Jun 17 10 6 39s401ms 6s566ms [ User: postgres - Total duration: 39s401ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 39s401ms - 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: 2025-06-17 10:00:11 Duration: 8s612ms 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: 2025-06-17 10:30:10 Duration: 7s216ms 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: 2025-06-17 10:10:09 Duration: 6s443ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
5 552ms 9s112ms 2s974ms 403 19m58s 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 Jun 17 10 403 19m58s 2s974ms [ User: postgres - Total duration: 19m58s - Times executed: 403 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 18m52s - Times executed: 391 ]
[ 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: 2025-06-17 10:25:58 Duration: 9s112ms 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: 2025-06-17 10:22:29 Duration: 8s966ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 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: 2025-06-17 10:31:05 Duration: 8s736ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
6 1s814ms 3s579ms 2s161ms 16 34s577ms 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 Jun 17 10 16 34s577ms 2s161ms [ User: postgres - Total duration: 34s577ms - Times executed: 16 ]
[ Application: psql - Total duration: 34s577ms - 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: 2025-06-17 10:31:16 Duration: 3s579ms 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: 2025-06-17 10:03:17 Duration: 3s90ms 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: 2025-06-17 10:18:17 Duration: 3s82ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
7 1s230ms 2s555ms 1s637ms 8 13s103ms select updateresultsmaterializedview ();Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Jun 17 10 8 13s103ms 1s637ms [ User: postgres - Total duration: 13s103ms - Times executed: 8 ]
[ Application: psql - Total duration: 13s103ms - Times executed: 8 ]
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select updateresultsmaterializedview ();
Date: 2025-06-17 10:17:19 Duration: 2s555ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-06-17 10:35:35 Duration: 2s263ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-06-17 10:32:12 Duration: 1s601ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
8 1s284ms 1s828ms 1s517ms 12 18s204ms 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 #8
Day Hour Count Duration Avg duration Jun 17 10 12 18s204ms 1s517ms [ User: postgres - Total duration: 18s204ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 18s204ms - Times executed: 12 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '620' 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 = '620')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '620' 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 = '620' 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: 2025-06-17 10:51:44 Duration: 1s828ms 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: 2025-06-17 10:36:53 Duration: 1s741ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '617' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '617' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '617' 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: 2025-06-17 10:36:46 Duration: 1s710ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
9 1s95ms 2s51ms 1s407ms 6 8s447ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jun 17 10 6 8s447ms 1s407ms [ User: postgres - Total duration: 8s447ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 8s447ms - Times executed: 6 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-17 10:31:18 Duration: 2s51ms 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: 2025-06-17 10:01:18 Duration: 1s756ms 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: 2025-06-17 10:46:17 Duration: 1s314ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
10 671ms 1s633ms 996ms 16 15s941ms 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 #10
Day Hour Count Duration Avg duration Jun 17 10 16 15s941ms 996ms [ User: postgres - Total duration: 15s941ms - Times executed: 16 ]
[ Application: psql - Total duration: 15s941ms - 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: 2025-06-17 10:03:13 Duration: 1s633ms 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: 2025-06-17 10:18:13 Duration: 1s500ms 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: 2025-06-17 10:26:13 Duration: 1s391ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 12ms 9s531ms 673ms 34 22s900ms select fixcandlegaps (?, false);Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jun 17 10 34 22s900ms 673ms [ User: postgres - Total duration: 22s900ms - Times executed: 34 ]
[ Application: psql - Total duration: 22s900ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-06-17 10:06:25 Duration: 9s531ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-06-17 10:06:08 Duration: 3s93ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('AXIORY', false);
Date: 2025-06-17 10:06:10 Duration: 2s88ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
12 85ms 1s723ms 565ms 272 2m33s with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jun 17 10 272 2m33s 565ms [ User: postgres - Total duration: 2m33s - Times executed: 272 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m17s - Times executed: 260 ]
[ Application: [unknown] - Total duration: 16s323ms - 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: 2025-06-17 10:31:22 Duration: 1s723ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver 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: 2025-06-17 10:51:06 Duration: 1s672ms 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: 2025-06-17 10:36:03 Duration: 1s657ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
13 92ms 908ms 402ms 120 48s329ms with last_candle as ( select acs.symbolid as symbolid, acs.latestpricedatetime as latest_candle_time, bsl.brokerid as broker_id, coalesce(bim.code, s.symbol) as symbol, bim.code as symbol_mapping, s.exchange as exchange, s.timegranularity as timegranularity from autochartist_symbolupdates acs inner join brokersymbollist bsl on acs.symbolid = bsl.symbolid inner join symbols s on acs.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bsl.brokerid = ? and s.deleted = ? and s.nonliquid = ? and acs.latestpricedatetime is not null ) select * from ( select lc.broker_id as brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / ?) + ? as sast_hh, mod(cast(psp.fromtime as int), ?) as sast_mm, current_timestamp as datetime, (powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice as closingprice, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / ?.?) as low_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / ?.?) as high_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / ?.?) as low_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / ?.?) as high_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / ?.?) as low_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / ?.?) as high_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / ?.?) as low_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / ?.?) as high_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / ?.?) as low_1440, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / ?.?) as high_1440, dtt.absolutetimezoneoffset as datafeedtimezoneoffset, dtt.timezone as datafeedtimezonename, (round((cast(? as float) - rank) / ? * ?)) as rank_rounded, ((cast(? as float) - rank) / ? * ?) as rank from last_candle lc inner join downloadersymbolsettings dss on lc.symbolid = dss.symbolid inner join datafeedstimetable dtt on trim(dss.classname) = trim(dtt.classname) and dtt.dayofweek = ? -- assuming timezone is same for whole week. inner join powerstats_symboldata psd on psd.symbolid = lc.symbolid left outer join powerstats_trumpet psp on psd.trumpetsymbolid = psp.symbolid and psp.dayofweek = extract(dow from lc.latest_candle_time) and psp.fromtime = cast(extract(? from lc.latest_candle_time) as integer) * ? + extract(? from (cast(extract(? from lc.latest_candle_time) as integer) / ?) * ? * interval ?) inner join prfsymboltree prf on psd.symbolid = prf.symbolid and date_trunc(?, prf.enddate) = date_trunc(?, psp.enddate) left join lateral ( select ph.hour, (ave + stddev) as volatility, rank() over (order by (ave + stddev) desc) as rank from powerstats_hourly ph where ph.symbolid = psd.hourlysymbolid and date_trunc(?,ph.enddate) = date_trunc(?, prf.enddate) ) rank_query on true where prf.brokerid = ? and rank_query.hour = floor((psp.fromtime) / ?) and volatility > ? order by rank desc, rank_rounded desc, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jun 17 10 120 48s329ms 402ms [ User: postgres - Total duration: 48s329ms - Times executed: 120 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 48s329ms - Times executed: 120 ]
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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: 2025-06-17 10:04:00 Duration: 908ms 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: 2025-06-17 10:52:00 Duration: 904ms 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: 2025-06-17 10:04:00 Duration: 897ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
14 18ms 367ms 72ms 164 11s831ms select distinct a.symbolid, p.resultuid, case when a.breakout >= ? then ? else ? end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient from relevance_autochartist_results p inner join autochartist_results a on p.resultuid = a.resultuid inner join autochartist_stocklist asl on a.symbolid = asl.symbolid where asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Jun 17 10 164 11s831ms 72ms [ User: postgres - Total duration: 11s831ms - Times executed: 164 ]
[ Application: [unknown] - Total duration: 11s831ms - Times executed: 164 ]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2025-06-17 10:45:06 Duration: 367ms 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: 2025-06-17 10:31:18 Duration: 316ms 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 'ATFX - 1';
Date: 2025-06-17 10:31:30 Duration: 259ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
15 17ms 145ms 37ms 164 6s201ms 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 Jun 17 10 164 6s201ms 37ms [ User: postgres - Total duration: 6s201ms - Times executed: 164 ]
[ Application: [unknown] - Total duration: 6s201ms - Times executed: 164 ]
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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: 2025-06-17 10:31:20 Duration: 145ms 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 'Alpari - 1';
Date: 2025-06-17 10:30:40 Duration: 126ms 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 'Alpari - 1';
Date: 2025-06-17 10:16:58 Duration: 124ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
16 3ms 13ms 5ms 966 4s969ms select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Jun 17 10 966 4s969ms 5ms [ User: postgres - Total duration: 4s969ms - Times executed: 966 ]
[ Application: [unknown] - Total duration: 4s969ms - Times executed: 966 ]
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select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;
Date: 2025-06-17 10:52:01 Duration: 13ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
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select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;
Date: 2025-06-17 10:45:18 Duration: 11ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
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select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;
Date: 2025-06-17 10:52:06 Duration: 10ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
17 1ms 34ms 3ms 33,124 1m59s 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 Jun 17 10 33,124 1m59s 3ms [ User: postgres - Total duration: 1m59s - Times executed: 33124 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m59s - Times executed: 33124 ]
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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 = 'CADCHF' OR dss.downloadersymbol = 'CADCHF') AND dss.enabled = 1;
Date: 2025-06-17 10:00:05 Duration: 34ms 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 = 'NKE.US' OR dss.downloadersymbol = 'NKE.US') AND dss.enabled = 1;
Date: 2025-06-17 10:30:05 Duration: 34ms 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 = 'SEKJPY' OR dss.downloadersymbol = 'SEKJPY') AND dss.enabled = 1;
Date: 2025-06-17 10:00:05 Duration: 33ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
18 0ms 23ms 2ms 883 2s49ms 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 #18
Day Hour Count Duration Avg duration Jun 17 10 883 2s49ms 2ms [ User: postgres - Total duration: 2s49ms - Times executed: 883 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s49ms - Times executed: 883 ]
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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 = '515840245858969300' 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: 2025-06-17 10:52:04 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 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 = '515840233921111300' 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: 2025-06-17 10:00:05 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 = '515840246009750300' 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: 2025-06-17 10:47:47 Duration: 18ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
19 0ms 36ms 1ms 3,064 5s301ms 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 #19
Day Hour Count Duration Avg duration Jun 17 10 3,064 5s301ms 1ms [ User: postgres - Total duration: 5s301ms - Times executed: 3064 ]
[ Application: [unknown] - Total duration: 5s301ms - Times executed: 3064 ]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, - 1, 2, '2025-06-17 07:57:34'::timestamp without time zone, '', 0.500000000000000000000000000000, 4, 54, 654.360000000000013600000000000000, '2025-06-17 10:15:00', '2025-06-17 08:15:00', '2025-06-17 07:15:00', '2025-06-16 20:45:00', '', '', '', '', '', '', 135, 653.777000000000043600000000000000, '2025-06-17 10:45:00'::timestamp without time zone, '2025-06-17 10:45:00', 0.000000000000000000000000000000, 0.582999999999998408400000000000, 1, 515840248623286300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840248623286300|654.36|2|2025-06-17 10:45:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-06-16 20:45:00', 646.419999999999959000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 10:02:00 Duration: 36ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (9.000000000000000000000000000000, - 1, 2, '2025-06-17 07:57:34'::timestamp without time zone, '2025-06-17 10:45:00', 0.047245000000000592080000000000, 4, 258, 24.117429999999998810000000000000, '2025-06-16 15:45:00', '2025-06-16 13:30:00', '2025-06-12 23:45:00', '2025-06-12 18:15:00', '', '', '', '', '', '', 455, 24.102025999999998620000000000000, '2025-06-17 10:45:00'::timestamp without time zone, '2025-06-17 10:45:00', 24.158069999999998600000000000000, 0.015403999999999999290000000000, - 1, 515840233889653300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840233889653300|24.11743|2|2025-06-17 10:45:00|2025-06-17 10:45:00|-1|-1', 24.182628099999998740000000000000, 0.065198099999999925560000000000, 2, '2025-06-12 18:15:00', 24.206389999999998960000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 10:01:59 Duration: 24ms 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 (8.000000000000000000000000000000, - 1, 2, '2025-06-17 07:57:36'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 39, 1.356735000000000024000000000000, '2025-06-17 07:45:00', '2025-06-16 23:15:00', '2025-06-16 22:00:00', '', '', '', '', '', '', '', 78, 1.356661000000000117000000000000, '2025-06-17 07:45:00'::timestamp without time zone, '2025-06-17 07:45:00', 0.000000000000000000000000000000, 0.000078000000000000296740000000, 1, 515840249730262300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249730262300|1.356735|2|2025-06-17 07:45:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-06-16 22:00:00', 1.356735000000000024000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 10:02:01 Duration: 22ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
20 0ms 7ms 1ms 777 1s211ms 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 Jun 17 10 777 1s211ms 1ms [ User: postgres - Total duration: 1s211ms - Times executed: 777 ]
[ Application: [unknown] - Total duration: 1s211ms - Times executed: 777 ]
-
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: 2025-06-17 10:30:59 Duration: 7ms 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 = 'HOTFOREX' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-17 10:30:58 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 = 'ICMARKETS-AU-MT5' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-17 10:47:35 Duration: 4ms 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 3s452ms 3,229 0ms 18ms 1ms WITH rar_max as ( ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Jun 17 10 3,229 3s452ms 1ms [ User: postgres - Total duration: 2h4m56s - Times executed: 3229 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2h4m56s - Times executed: 3222 ]
[ Application: [unknown] - Total duration: 4ms - Times executed: 7 ]
-
WITH rar_max as ( ;
Date: 2025-06-17 10:53:58 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
WITH rar_max as ( ;
Date: 2025-06-17 10:52:01 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
WITH rar_max as ( ;
Date: 2025-06-17 10:52:04 Duration: 14ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
2 2s385ms 5,971 0ms 11ms 0ms SELECT ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 10 5,971 2s385ms 0ms [ User: postgres - Total duration: 12s552ms - Times executed: 5971 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12s391ms - Times executed: 5144 ]
[ Application: [unknown] - Total duration: 161ms - Times executed: 827 ]
-
SELECT ;
Date: 2025-06-17 10:15:04 Duration: 11ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
SELECT ;
Date: 2025-06-17 10:15:04 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
SELECT ;
Date: 2025-06-17 10:15:05 Duration: 9ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
3 1s32ms 777 0ms 2ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 10 777 1s32ms 1ms [ User: postgres - Total duration: 1s211ms - Times executed: 777 ]
[ Application: [unknown] - Total duration: 1s211ms - Times executed: 777 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-17 10:15:06 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-17 10:45:49 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-17 10:00:38 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
4 630ms 2,331 0ms 1ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 10 2,331 630ms 0ms [ User: postgres - Total duration: 5s158ms - Times executed: 2331 ]
[ Application: [unknown] - Total duration: 5s158ms - Times executed: 2331 ]
-
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: 2025-06-17 10:31:30 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 10:30:59 Duration: 0ms 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: 2025-06-17 10:46:17 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
5 361ms 3,354 0ms 5ms 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 3,354 361ms 0ms [ User: postgres - Total duration: 2s75ms - Times executed: 3354 ]
[ Application: [unknown] - Total duration: 2s75ms - Times executed: 3354 ]
-
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: 2025-06-17 10:31:04 Duration: 5ms 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: 2025-06-17 10:10:56 Duration: 1ms 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: 2025-06-17 10:00:55 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
6 260ms 2,138 0ms 3ms 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 2,138 260ms 0ms [ User: postgres - Total duration: 1s50ms - Times executed: 2138 ]
[ Application: [unknown] - Total duration: 1s50ms - Times executed: 2138 ]
-
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: 2025-06-17 10:00:42 Duration: 3ms 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: 2025-06-17 10:00:47 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: 2025-06-17 10:10:40 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
7 187ms 3,069 0ms 20ms 0ms select 1;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 10 3,069 187ms 0ms [ User: postgres - Total duration: 12ms - Times executed: 3069 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12ms - Times executed: 3069 ]
-
select 1;
Date: 2025-06-17 10:15:05 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
select 1;
Date: 2025-06-17 10:15:04 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
select 1;
Date: 2025-06-17 10:51:19 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
8 186ms 1,296 0ms 3ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #8
Day Hour Count Duration Avg duration 10 1,296 186ms 0ms [ User: postgres - Total duration: 20ms - Times executed: 1296 ]
[ Application: [unknown] - Total duration: 20ms - Times executed: 1296 ]
-
SET extra_float_digits = 3;
Date: 2025-06-17 10:30:43 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
SET extra_float_digits = 3;
Date: 2025-06-17 10:31:04 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
SET extra_float_digits = 3;
Date: 2025-06-17 10:56:47 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
9 79ms 12 4ms 7ms 6ms with sym_info as ( ;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 10 12 79ms 6ms [ User: postgres - Total duration: 18s204ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 18s204ms - Times executed: 12 ]
-
with sym_info as ( ;
Date: 2025-06-17 10:51:46 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
-
with sym_info as ( ;
Date: 2025-06-17 10:06:50 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
-
with sym_info as ( ;
Date: 2025-06-17 10:51:42 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
10 65ms 54 0ms 3ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 10 54 65ms 1ms [ User: postgres - Total duration: 27s585ms - Times executed: 54 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 27s585ms - Times executed: 54 ]
-
WITH last_candle AS ( ;
Date: 2025-06-17 10:16:00 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
WITH last_candle AS ( ;
Date: 2025-06-17 10:36:03 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
WITH last_candle AS ( ;
Date: 2025-06-17 10:16:00 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
11 54ms 18 2ms 6ms 3ms 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 54ms 3ms [ User: postgres - Total duration: 33ms - Times executed: 18 ]
[ Application: [unknown] - Total duration: 33ms - Times executed: 18 ]
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-06-17 10:11:01 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-06-17 10:31:02 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-06-17 10:51:21 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
12 48ms 30 0ms 2ms 1ms with wh_patitioned as ( ;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 10 30 48ms 1ms [ User: postgres - Total duration: 958ms - Times executed: 30 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 958ms - Times executed: 30 ]
-
with wh_patitioned as ( ;
Date: 2025-06-17 10:56:29 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
with wh_patitioned as ( ;
Date: 2025-06-17 10:12:47 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
with wh_patitioned as ( ;
Date: 2025-06-17 10:35:46 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
13 28ms 24 0ms 10ms 1ms 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 28ms 1ms [ User: postgres - Total duration: 64ms - Times executed: 24 ]
[ Application: [unknown] - Total duration: 64ms - Times executed: 24 ]
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-06-17 10:00:07 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-06-17 10:40:07 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-06-17 10:45:00 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
14 27ms 53 0ms 1ms 0ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 10 53 27ms 0ms [ User: postgres - Total duration: 1ms - Times executed: 53 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1ms - Times executed: 53 ]
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-17 10:44:05 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-17 10:26:43 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
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WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-17 10:52:25 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
15 19ms 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 #15
Day Hour Count Duration Avg duration 10 6 19ms 3ms [ User: postgres - Total duration: 13ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 13ms - 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: 2025-06-17 10:30:04 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: 2025-06-17 10:40:04 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: 2025-06-17 10:50:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
16 19ms 18 0ms 1ms 1ms select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 10 18 19ms 1ms [ User: postgres - Total duration: 58ms - Times executed: 18 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 58ms - Times executed: 18 ]
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select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2025-06-17 10:52:00 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 127.0.0.1
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select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2025-06-17 10:50:50 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 127.0.0.1
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select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2025-06-17 10:26:57 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 127.0.0.1
17 17ms 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 #17
Day Hour Count Duration Avg duration 10 6 17ms 2ms [ User: postgres - Total duration: 39s401ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 39s401ms - 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: 2025-06-17 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: 2025-06-17 10:10:02 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: 2025-06-17 10:50:02 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
18 15ms 1,270 0ms 0ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 10 1,270 15ms 0ms [ User: postgres - Total duration: 16ms - Times executed: 1270 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 16ms - Times executed: 1270 ]
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-17 10:52:01 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-17 10:38:04 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-17 10:12:41 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
19 13ms 18 0ms 1ms 0ms select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 10 18 13ms 0ms [ User: postgres - Total duration: 23ms - Times executed: 18 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 23ms - Times executed: 18 ]
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select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2025-06-17 10:26:57 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 127.0.0.1
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select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2025-06-17 10:52:00 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 127.0.0.1
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select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2025-06-17 10:16:56 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 127.0.0.1
20 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 #20
Day Hour Count Duration Avg duration 10 90 8ms 0ms [ User: postgres - Total duration: 7ms - Times executed: 90 ]
[ Application: [unknown] - Total duration: 7ms - Times executed: 90 ]
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INSERT INTO mt4datafeederrors (datafeedname, eventtimestamp, errordescription, status, serveraddress, username) values ($1, current_timestamp, $2, $3, $4, $5);
Date: 2025-06-17 10:02:24 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.205
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INSERT INTO mt4datafeederrors (datafeedname, eventtimestamp, errordescription, status, serveraddress, username) values ($1, current_timestamp, $2, $3, $4, $5);
Date: 2025-06-17 10:05:44 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.205
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INSERT INTO mt4datafeederrors (datafeedname, eventtimestamp, errordescription, status, serveraddress, username) values ($1, current_timestamp, $2, $3, $4, $5);
Date: 2025-06-17 10:47:50 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.205
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 39s517ms 77,190 0ms 50ms 0ms SELECT ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Jun 17 10 77,190 39s517ms 0ms [ User: postgres - Total duration: 3m5s - Times executed: 77190 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3m5s - Times executed: 76356 ]
[ Application: [unknown] - Total duration: 166ms - Times executed: 834 ]
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SELECT ;
Date: 2025-06-17 10:00:05 Duration: 50ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '515840243130983300'
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SELECT ;
Date: 2025-06-17 10:00:05 Duration: 32ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '538', $2 = '0', $3 = '0', $4 = 'CHFJPY', $5 = 'CHFJPY'
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SELECT ;
Date: 2025-06-17 10:00:05 Duration: 28ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '529', $2 = '0', $3 = '0', $4 = 'EURNZD', $5 = 'EURNZD'
2 38s994ms 5,009 0ms 42ms 7ms WITH rar_max as ( ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 10 5,009 38s994ms 7ms [ User: postgres - Total duration: 2h24m10s - Times executed: 5009 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2h16m56s - Times executed: 4940 ]
[ Application: [unknown] - Total duration: 7m14s - Times executed: 69 ]
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WITH rar_max as ( ;
Date: 2025-06-17 10:56:18 Duration: 42ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = 't', $2 = '667', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '84', $14 = 'AUDCAD', $15 = 'AUDCHF', $16 = 'AUDJPY', $17 = 'AUDNZD', $18 = 'AUDSGD', $19 = 'CADCHF', $20 = 'CADJPY', $21 = 'CHFJPY', $22 = 'EURAUD', $23 = 'EURCAD', $24 = 'EURCHF', $25 = 'EURCZK', $26 = 'EURGBP', $27 = 'EURHUF', $28 = 'EURJPY', $29 = 'EURNOK', $30 = 'EURNZD', $31 = 'EURPLN', $32 = 'EURSEK', $33 = 'EURSGD', $34 = 'EURTRY', $35 = 'EURZAR', $36 = 'GBPAUD', $37 = 'GBPCAD', $38 = 'GBPCHF', $39 = 'GBPJPY', $40 = 'GBPNZD', $41 = 'GBPPLN', $42 = 'GBPSEK', $43 = 'GBPSGD', $44 = 'NZDCAD', $45 = 'NZDCHF', $46 = 'NZDJPY', $47 = 'NZDSGD', $48 = 'USDCNH', $49 = 'USDCZK', $50 = 'USDHUF', $51 = 'USDNOK', $52 = 'USDPLN', $53 = 'USDSEK', $54 = 'USDSGD', $55 = 'USDTRY', $56 = 'USDZAR', $57 = 'WTI', $58 = 'XBRUSD', $59 = 'XTIUSD', $60 = 'BTCUSD', $61 = 'XAGAUD', $62 = 'XAGUSD', $63 = 'XAUAUD', $64 = 'XAUUSD', $65 = 'XPTUSD', $66 = 'XPDUSD', $67 = 'AUDUSD', $68 = 'EURUSD', $69 = 'GBPUSD', $70 = 'NZDUSD', $71 = 'USDCAD', $72 = 'USDCHF', $73 = 'USDHKD', $74 = 'USDJPY', $75 = 'AUS200', $76 = 'CHINA300', $77 = 'CHINA50', $78 = 'DJ30', $79 = 'ESP35t', $80 = 'EUR50', $81 = 'EURO50', $82 = 'FRA40', $83 = 'GDAXI', $84 = 'GDAXIm', $85 = 'HK50', $86 = 'ITA40', $87 = 'J225', $88 = 'JP225', $89 = 'NAS100', $90 = 'SING30', $91 = 'SPA35', $92 = 'STOXX50', $93 = 'SUI20', $94 = 'UK100', $95 = 'US100', $96 = 'US30', $97 = 'US500', $98 = '0', $99 = '', $100 = '0', $101 = '0', $102 = '0', $103 = '400', $104 = '400', $105 = 't', $106 = '10', $107 = '10'
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WITH rar_max as ( ;
Date: 2025-06-17 10:31:14 Duration: 39ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = 't', $2 = '667', $3 = '0', $4 = '0', $5 = '0', $6 = '', $7 = '0', $8 = '', $9 = '0', $10 = '', $11 = '0', $12 = '0', $13 = '0', $14 = '0', $15 = '0', $16 = 't', $17 = '0', $18 = '0'
-
WITH rar_max as ( ;
Date: 2025-06-17 10:22:23 Duration: 35ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = 't', $2 = '667', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '84', $14 = 'AUDCAD', $15 = 'AUDCHF', $16 = 'AUDJPY', $17 = 'AUDNZD', $18 = 'AUDSGD', $19 = 'CADCHF', $20 = 'CADJPY', $21 = 'CHFJPY', $22 = 'EURAUD', $23 = 'EURCAD', $24 = 'EURCHF', $25 = 'EURCZK', $26 = 'EURGBP', $27 = 'EURHUF', $28 = 'EURJPY', $29 = 'EURNOK', $30 = 'EURNZD', $31 = 'EURPLN', $32 = 'EURSEK', $33 = 'EURSGD', $34 = 'EURTRY', $35 = 'EURZAR', $36 = 'GBPAUD', $37 = 'GBPCAD', $38 = 'GBPCHF', $39 = 'GBPJPY', $40 = 'GBPNZD', $41 = 'GBPPLN', $42 = 'GBPSEK', $43 = 'GBPSGD', $44 = 'NZDCAD', $45 = 'NZDCHF', $46 = 'NZDJPY', $47 = 'NZDSGD', $48 = 'USDCNH', $49 = 'USDCZK', $50 = 'USDHUF', $51 = 'USDNOK', $52 = 'USDPLN', $53 = 'USDSEK', $54 = 'USDSGD', $55 = 'USDTRY', $56 = 'USDZAR', $57 = 'WTI', $58 = 'XBRUSD', $59 = 'XTIUSD', $60 = 'BTCUSD', $61 = 'XAGAUD', $62 = 'XAGUSD', $63 = 'XAUAUD', $64 = 'XAUUSD', $65 = 'XPTUSD', $66 = 'XPDUSD', $67 = 'AUDUSD', $68 = 'EURUSD', $69 = 'GBPUSD', $70 = 'NZDUSD', $71 = 'USDCAD', $72 = 'USDCHF', $73 = 'USDHKD', $74 = 'USDJPY', $75 = 'AUS200', $76 = 'CHINA300', $77 = 'CHINA50', $78 = 'DJ30', $79 = 'ESP35t', $80 = 'EUR50', $81 = 'EURO50', $82 = 'FRA40', $83 = 'GDAXI', $84 = 'GDAXIm', $85 = 'HK50', $86 = 'ITA40', $87 = 'J225', $88 = 'JP225', $89 = 'NAS100', $90 = 'SING30', $91 = 'SPA35', $92 = 'STOXX50', $93 = 'SUI20', $94 = 'UK100', $95 = 'US100', $96 = 'US30', $97 = 'US500', $98 = '0', $99 = '', $100 = '0', $101 = '0', $102 = '0', $103 = '400', $104 = '400', $105 = 't', $106 = '10', $107 = '10'
3 1s813ms 63 0ms 49ms 28ms with wh_patitioned as ( ;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 10 63 1s813ms 28ms [ User: postgres - Total duration: 1s753ms - Times executed: 63 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s753ms - Times executed: 63 ]
-
with wh_patitioned as ( ;
Date: 2025-06-17 10:40:42 Duration: 49ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529', $3 = '529', $4 = '529', $5 = '529', $6 = '529', $7 = '529', $8 = '529', $9 = '529'
-
with wh_patitioned as ( ;
Date: 2025-06-17 10:55:39 Duration: 48ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
-
with wh_patitioned as ( ;
Date: 2025-06-17 10:12:47 Duration: 48ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '529', $2 = '529', $3 = '529', $4 = '529', $5 = '529', $6 = '529', $7 = '529', $8 = '529', $9 = '529'
4 1s461ms 777 1ms 12ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 10 777 1s461ms 1ms [ User: postgres - Total duration: 1s211ms - Times executed: 777 ]
[ Application: [unknown] - Total duration: 1s211ms - Times executed: 777 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-17 10:31:04 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'ATFX'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-17 10:31:03 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'BDSWISS'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-17 10:31:26 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'ATFX'
5 979ms 52,642 0ms 14ms 0ms select 1;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 10 52,641 979ms 0ms 11 1 0ms 0ms [ User: postgres - Total duration: 276ms - Times executed: 52642 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 275ms - Times executed: 52503 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 139 ]
-
select 1;
Date: 2025-06-17 10:45:05 Duration: 14ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
select 1;
Date: 2025-06-17 10:45:05 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
select 1;
Date: 2025-06-17 10:30:06 Duration: 8ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
6 874ms 120 4ms 12ms 7ms WITH last_candle AS ( ;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 10 120 874ms 7ms [ User: postgres - Total duration: 48s329ms - Times executed: 120 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 48s329ms - Times executed: 120 ]
-
WITH last_candle AS ( ;
Date: 2025-06-17 10:16:00 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '529', $2 = '529'
-
WITH last_candle AS ( ;
Date: 2025-06-17 10:16:00 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529'
-
WITH last_candle AS ( ;
Date: 2025-06-17 10:36:03 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558'
7 751ms 60 9ms 21ms 12ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 10 60 751ms 12ms [ User: postgres - Total duration: 1ms - Times executed: 60 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1ms - Times executed: 60 ]
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-17 10:26:43 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '689', $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: 2025-06-17 10:52:25 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '689', $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: 2025-06-17 10:57:09 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
8 593ms 6,078 0ms 14ms 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 #8
Day Hour Count Duration Avg duration 10 6,078 593ms 0ms [ User: postgres - Total duration: 7s218ms - Times executed: 6078 ]
[ Application: [unknown] - Total duration: 7s218ms - Times executed: 6078 ]
-
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: 2025-06-17 10:31:00 Duration: 14ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 11:15:00', $2 = '31.561', $3 = '31.564', $4 = '31.499', $5 = '31.528', $6 = '939', $7 = '515840233494906300', $8 = '0', $9 = '2025-06-17 10:31:00.716', $10 = '2025-06-17 10:31:00.252', $11 = '31.561', $12 = '31.564', $13 = '31.499', $14 = '31.528', $15 = '939', $16 = '0', $17 = '2025-06-17 10:31:00.716', $18 = '2025-06-17 10:31:00.252'
-
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: 2025-06-17 10:30:49 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 11:15:00', $2 = '19624.9', $3 = '19631.1', $4 = '19590.6', $5 = '19625.5', $6 = '529', $7 = '515840248266900300', $8 = '0', $9 = '2025-06-17 10:30:49.175', $10 = '2025-06-17 10:30:45.53', $11 = '19624.9', $12 = '19631.1', $13 = '19590.6', $14 = '19625.5', $15 = '529', $16 = '0', $17 = '2025-06-17 10:30:49.175', $18 = '2025-06-17 10:30:45.53'
-
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: 2025-06-17 10:31:24 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 11:15:00', $2 = '69219', $3 = '69286.5', $4 = '68844.5', $5 = '69060', $6 = '687', $7 = '515840249399633300', $8 = '0', $9 = '2025-06-17 10:31:24.49', $10 = '2025-06-17 10:31:24.461', $11 = '69219', $12 = '69286.5', $13 = '68844.5', $14 = '69060', $15 = '687', $16 = '0', $17 = '2025-06-17 10:31:24.49', $18 = '2025-06-17 10:31:24.461'
9 482ms 12 28ms 46ms 40ms with sym_info as ( ;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 10 12 482ms 40ms [ User: postgres - Total duration: 18s204ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 18s204ms - Times executed: 12 ]
-
with sym_info as ( ;
Date: 2025-06-17 10:06:50 Duration: 46ms 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'
-
with sym_info as ( ;
Date: 2025-06-17 10:51:46 Duration: 45ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '617', $2 = 'Forex', $3 = 'Forex', $4 = '617', $5 = 'Forex', $6 = '617', $7 = '617', $8 = 'Forex', $9 = '617'
-
with sym_info as ( ;
Date: 2025-06-17 10:07:01 Duration: 45ms 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'
10 320ms 3,471 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 3,471 320ms 0ms [ User: postgres - Total duration: 2s173ms - Times executed: 3471 ]
[ Application: [unknown] - Total duration: 2s173ms - Times executed: 3471 ]
-
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: 2025-06-17 10:00:55 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-16 20:30:00', $2 = '38550', $3 = '38560', $4 = '38510', $5 = '38515', $6 = '656', $7 = '515840230561211300', $8 = '0', $9 = '2025-06-17 10:00:55.767', $10 = '2025-06-17 10:00:55.747', $11 = '38550', $12 = '38560', $13 = '38510', $14 = '38515', $15 = '656', $16 = '0', $17 = '2025-06-17 10:00:55.767', $18 = '2025-06-17 10:00:55.747'
-
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: 2025-06-17 10:15:43 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 10:30:00', $2 = '0.939185', $3 = '0.939685', $4 = '0.938965', $5 = '0.939175', $6 = '2958', $7 = '515840230468601300', $8 = '0', $9 = '2025-06-17 10:15:43.171', $10 = '2025-06-17 10:15:43.143', $11 = '0.939185', $12 = '0.939685', $13 = '0.938965', $14 = '0.939175', $15 = '2958', $16 = '0', $17 = '2025-06-17 10:15:43.171', $18 = '2025-06-17 10:15:43.143'
-
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: 2025-06-17 10:10:56 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 10:00:00', $2 = '21825.3', $3 = '21838.3', $4 = '21770.3', $5 = '21799.4', $6 = '7815', $7 = '515840248039147300', $8 = '0', $9 = '2025-06-17 10:10:56.515', $10 = '2025-06-17 10:10:56.455', $11 = '21825.3', $12 = '21838.3', $13 = '21770.3', $14 = '21799.4', $15 = '7815', $16 = '0', $17 = '2025-06-17 10:10:56.515', $18 = '2025-06-17 10:10:56.455'
11 229ms 247 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 #11
Day Hour Count Duration Avg duration 10 247 229ms 0ms [ User: postgres - Total duration: 1s498ms - Times executed: 247 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s402ms - Times executed: 235 ]
[ Application: [unknown] - Total duration: 96ms - Times executed: 12 ]
-
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: 2025-06-17 10:31:14 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42 parameters: $1 = '538', $2 = 'USA100', $3 = '538'
-
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: 2025-06-17 10:34:35 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: 2025-06-17 10:10:36 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.42 parameters: $1 = '689', $2 = 'XAUUSD', $3 = '689'
12 216ms 2,252 0ms 0ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 10 2,252 216ms 0ms [ User: postgres - Total duration: 1s108ms - Times executed: 2252 ]
[ Application: [unknown] - Total duration: 1s108ms - Times executed: 2252 ]
-
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: 2025-06-17 10:00:42 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 10:00:00', $2 = '0.53112', $3 = '0.53182', $4 = '0.53076', $5 = '0.53122', $6 = '4699', $7 = '515840247868983300', $8 = '0', $9 = '2025-06-17 10:00:42.734', $10 = '2025-06-17 10:00:42.684', $11 = '0.53112', $12 = '0.53182', $13 = '0.53076', $14 = '0.53122', $15 = '4699', $16 = '0', $17 = '2025-06-17 10:00:42.734', $18 = '2025-06-17 10:00:42.684'
-
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: 2025-06-17 10:11:42 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 10:00:00', $2 = '8526.4', $3 = '8535.4', $4 = '8509', $5 = '8532.4', $6 = '760', $7 = '515840248015562300', $8 = '0', $9 = '2025-06-17 10:11:42.905', $10 = '2025-06-17 10:11:42.87', $11 = '8526.4', $12 = '8535.4', $13 = '8509', $14 = '8532.4', $15 = '760', $16 = '0', $17 = '2025-06-17 10:11:42.905', $18 = '2025-06-17 10:11:42.87'
-
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: 2025-06-17 10:10:40 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-16 21:00:00', $2 = '478.57', $3 = '478.77', $4 = '477.74', $5 = '478.48', $6 = '3214', $7 = '515840247896450300', $8 = '0', $9 = '2025-06-17 10:10:40.319', $10 = '2025-06-17 10:10:40.277', $11 = '478.57', $12 = '478.77', $13 = '477.74', $14 = '478.48', $15 = '3214', $16 = '0', $17 = '2025-06-17 10:10:40.319', $18 = '2025-06-17 10:10:40.277'
13 68ms 13 3ms 6ms 5ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 10 13 68ms 5ms [ User: postgres - Total duration: 2s416ms - Times executed: 13 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s416ms - Times executed: 13 ]
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-06-17 10:01:17 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '627', $2 = '627'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-06-17 10:20:44 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '538', $2 = '538'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-06-17 10:11:21 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '958', $2 = '958'
14 55ms 698 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 10 698 55ms 0ms [ User: postgres - Total duration: 63ms - Times executed: 698 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 63ms - Times executed: 698 ]
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2025-06-17 10:49:19 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '606306436796189301'
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2025-06-17 10:59:42 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '606306207325979301'
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2025-06-17 10:02:53 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42 parameters: $1 = '606306142725942301'
15 31ms 1 31ms 31ms 31ms with maxwhid as ( ;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 10 1 31ms 31ms [ User: postgres - Total duration: 37ms - Times executed: 1 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 37ms - Times executed: 1 ]
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with maxwhid as ( ;
Date: 2025-06-17 10:12:12 Duration: 31ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.215 parameters: $1 = '335', $2 = '621', $3 = '637', $4 = '642', $5 = '666', $6 = '660', $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'
16 28ms 717 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 #16
Day Hour Count Duration Avg duration 10 717 28ms 0ms [ User: postgres - Total duration: 24ms - Times executed: 717 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 24ms - Times executed: 717 ]
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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: 2025-06-17 10:02:22 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '515840233927984300'
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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: 2025-06-17 10:55:30 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '515840233379735300'
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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: 2025-06-17 10:14:29 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '515840233917433300'
17 25ms 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 25ms 4ms [ User: postgres - Total duration: 39s401ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 39s401ms - 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: 2025-06-17 10:40:02 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: 2025-06-17 10:10:02 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: 2025-06-17 10:50:02 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
18 25ms 288 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 #18
Day Hour Count Duration Avg duration 10 288 25ms 0ms [ User: postgres - Total duration: 18ms - Times executed: 288 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 18ms - Times executed: 288 ]
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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: 2025-06-17 10:21:55 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '606306442882163303'
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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: 2025-06-17 10:48:51 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '606306323026166303'
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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: 2025-06-17 10:40:31 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42 parameters: $1 = '606306143742193303'
19 25ms 249 0ms 0ms 0ms select category, ;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 10 249 25ms 0ms [ User: postgres - Total duration: 38ms - Times executed: 249 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 38ms - Times executed: 249 ]
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select category, ;
Date: 2025-06-17 10:03:58 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.54 parameters: $1 = '515852059309933307', $2 = 'symbol', $3 = 'NZDJPY', $4 = 'EURJPY', $5 = 'GBPJPY', $6 = 'CADJPY', $7 = 'CHFJPY', $8 = 'USDJPY', $9 = 'XAGUSD', $10 = 'XAUUSD', $11 = 'GBPNZD', $12 = 'EURNZD', $13 = 'GBPCAD', $14 = 'EURCAD', $15 = 'GBPCAD', $16 = 'GBPUSD', $17 = 'AUDUSD', $18 = 'CADCHF', $19 = 'EURCAD', $20 = 'NZDUSD', $21 = 'XAGUSD', $22 = 'GBPCHF', $23 = 'EURUSD', $24 = 'USDCAD', $25 = 'USDCAD', $26 = 'EURCHF', $27 = 'GBPJPY', $28 = 'CADJPY', $29 = 'EURJPY', $30 = 'GBPCHF', $31 = 'USDJPY', $32 = 'GBPUSD', $33 = 'XAUUSD', $34 = 'CHFJPY', $35 = 'USDCHF', $36 = 'EURNZD', $37 = 'GBPNZD', $38 = 'EURUSD', $39 = 'NZDJPY', $40 = 'EURCHF', $41 = 'AUDUSD', $42 = 'NZDUSD', $43 = 'USDCHF', $44 = 'CADCHF', $45 = '515852059309933307', $46 = 'symbol', $47 = 'NZDJPY', $48 = 'EURJPY', $49 = 'GBPJPY', $50 = 'CADJPY', $51 = 'CHFJPY', $52 = 'USDJPY', $53 = 'XAGUSD', $54 = 'XAUUSD', $55 = 'GBPNZD', $56 = 'EURNZD', $57 = 'GBPCAD', $58 = 'EURCAD', $59 = 'GBPCAD', $60 = 'GBPUSD', $61 = 'AUDUSD', $62 = 'CADCHF', $63 = 'EURCAD', $64 = 'NZDUSD', $65 = 'XAGUSD', $66 = 'GBPCHF', $67 = 'EURUSD', $68 = 'USDCAD', $69 = 'USDCAD', $70 = 'EURCHF', $71 = 'GBPJPY', $72 = 'CADJPY', $73 = 'EURJPY', $74 = 'GBPCHF', $75 = 'USDJPY', $76 = 'GBPUSD', $77 = 'XAUUSD', $78 = 'CHFJPY', $79 = 'USDCHF', $80 = 'EURNZD', $81 = 'GBPNZD', $82 = 'EURUSD', $83 = 'NZDJPY', $84 = 'EURCHF', $85 = 'AUDUSD', $86 = 'NZDUSD', $87 = 'USDCHF', $88 = 'CADCHF'
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select category, ;
Date: 2025-06-17 10:01:43 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.54 parameters: $1 = '500996399109302207', $2 = 'symbol', $3 = 'EURO50', $4 = 'XTIUSD', $5 = 'UK100', $6 = 'WTI', $7 = 'XBRUSD', $8 = 'US100', $9 = 'XAUAUD', $10 = 'JP225', $11 = 'BTCUSD', $12 = 'FRA40', $13 = 'AUS200', $14 = 'SING30', $15 = 'US500', $16 = 'XAUUSD', $17 = 'XAGUSD', $18 = 'XAGAUD', $19 = 'CHINA50', $20 = 'XPDUSD', $21 = 'US30', $22 = 'XPTUSD', $23 = 'HK50', $24 = 'CHINA50', $25 = 'EURO50', $26 = 'WTI', $27 = 'XAGAUD', $28 = 'UK100', $29 = 'SING30', $30 = 'XAGUSD', $31 = 'XTIUSD', $32 = 'US500', $33 = 'XAUAUD', $34 = 'XPDUSD', $35 = 'US30', $36 = 'JP225', $37 = 'AUS200', $38 = 'FRA40', $39 = 'HK50', $40 = 'US100', $41 = 'XBRUSD', $42 = 'BTCUSD', $43 = 'XAUUSD', $44 = 'XPTUSD', $45 = 'SPA35', $46 = 'ITA40', $47 = 'SPA35', $48 = 'ITA40', $49 = '500996399109302207', $50 = 'symbol', $51 = 'EURO50', $52 = 'XTIUSD', $53 = 'UK100', $54 = 'WTI', $55 = 'XBRUSD', $56 = 'US100', $57 = 'XAUAUD', $58 = 'JP225', $59 = 'BTCUSD', $60 = 'FRA40', $61 = 'AUS200', $62 = 'SING30', $63 = 'US500', $64 = 'XAUUSD', $65 = 'XAGUSD', $66 = 'XAGAUD', $67 = 'CHINA50', $68 = 'XPDUSD', $69 = 'US30', $70 = 'XPTUSD', $71 = 'HK50', $72 = 'CHINA50', $73 = 'EURO50', $74 = 'WTI', $75 = 'XAGAUD', $76 = 'UK100', $77 = 'SING30', $78 = 'XAGUSD', $79 = 'XTIUSD', $80 = 'US500', $81 = 'XAUAUD', $82 = 'XPDUSD', $83 = 'US30', $84 = 'JP225', $85 = 'AUS200', $86 = 'FRA40', $87 = 'HK50', $88 = 'US100', $89 = 'XBRUSD', $90 = 'BTCUSD', $91 = 'XAUUSD', $92 = 'XPTUSD', $93 = 'SPA35', $94 = 'ITA40', $95 = 'SPA35', $96 = 'ITA40'
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select category, ;
Date: 2025-06-17 10:00:06 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.54 parameters: $1 = '601729875363291307', $2 = 'symbol', $3 = 'Adidas', $4 = 'Danone', $5 = 'LVMH', $6 = 'Daimler', $7 = 'Lufthansa', $8 = 'Volksw', $9 = 'Bayer', $10 = 'Lufthansa', $11 = 'Danone', $12 = 'Volksw', $13 = 'Adidas', $14 = 'Bayer', $15 = 'LVMH', $16 = 'Daimler', $17 = 'AIRFKLM', $18 = 'AIRFKLM', $19 = '601729875363291307', $20 = 'symbol', $21 = 'Adidas', $22 = 'Danone', $23 = 'LVMH', $24 = 'Daimler', $25 = 'Lufthansa', $26 = 'Volksw', $27 = 'Bayer', $28 = 'Lufthansa', $29 = 'Danone', $30 = 'Volksw', $31 = 'Adidas', $32 = 'Bayer', $33 = 'LVMH', $34 = 'Daimler', $35 = 'AIRFKLM', $36 = 'AIRFKLM'
20 22ms 247 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 10 247 22ms 0ms [ User: postgres - Total duration: 761ms - Times executed: 247 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 707ms - Times executed: 235 ]
[ Application: [unknown] - Total duration: 54ms - Times executed: 12 ]
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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: 2025-06-17 10:16:45 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '660', $3 = '515840248166557300'
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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: 2025-06-17 10:03:49 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '645', $3 = '515840217487984300'
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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: 2025-06-17 10:03:19 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.42 parameters: $1 = '2', $2 = '645', $3 = '515840245872387300'
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Events
Log levels
Key values
- 575,919 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 1 ERROR entries
- 0 WARNING entries
Most Frequent Errors/Events
Key values
- 1 Max number of times the same event was reported
- 1 Total events found
Rank Times reported Error 1 1 ERROR: relation "..." does not exist
Times Reported Most Frequent Error / Event #1
Day Hour Count Jun 17 10 1 - ERROR: relation "t0" does not exist at character 83
Statement: SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T0 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050 ) a ORDER BY PriceDateTime ASC
Date: 2025-06-17 10:24:21 Database: acaweb_fx Application: PostgreSQL JDBC Driver User: postgres Remote: 192.168.1.23