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Global information
- Generated on Tue Jul 22 20:59:52 2025
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2025-07-22_220000.log
- Parsed 1,915,265 log entries in 51s
- Log start from 2025-07-22 22:00:00 to 2025-07-22 22:59:51
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Overview
Global Stats
- 189 Number of unique normalized queries
- 114,526 Number of queries
- 2h34m50s Total query duration
- 2025-07-22 22:00:00 First query
- 2025-07-22 22:59:51 Last query
- 2,469 queries/s at 2025-07-22 22:45:04 Query peak
- 2h34m50s Total query duration
- 13s456ms Prepare/parse total duration
- 1m10s Bind total duration
- 2h33m26s Execute total duration
- 0 Number of events
- 0 Number of unique normalized events
- 0 Max number of times the same event was reported
- 0 Number of cancellation
- 37 Total number of automatic vacuums
- 55 Total number of automatic analyzes
- 811 Number temporary file
- 153.28 MiB Max size of temporary file
- 5.54 MiB Average size of temporary file
- 5,630 Total number of sessions
- 15 sessions at 2025-07-22 22:38:08 Session peak
- 2d10h47m42s Total duration of sessions
- 37s595ms Average duration of sessions
- 20 Average queries per session
- 1s650ms Average queries duration per session
- 35s945ms Average idle time per session
- 5,631 Total number of connections
- 40 connections/s at 2025-07-22 22:11:00 Connection peak
- 2 Total number of databases
SQL Traffic
Key values
- 2,469 queries/s Query Peak
- 2025-07-22 22:45:04 Date
SELECT Traffic
Key values
- 2,400 queries/s Query Peak
- 2025-07-22 22:45:04 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 191 queries/s Query Peak
- 2025-07-22 22:17:51 Date
Queries duration
Key values
- 2h34m50s 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) Jul 22 22 114,526 0ms 1m2s 80ms 4m22s 5m33s 6m58s Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jul 22 22 65,142 26 2ms 2s995ms 12s902ms 14s551ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jul 22 22 31,296 2,215 16 96 1ms 1s115ms 1s509ms 2s650ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Jul 22 22 31,860 90,818 2.85 30.32% Day Hour Count Average / Second Jul 22 22 5,631 1.56/s Day Hour Count Average Duration Average idle time Jul 22 22 5,630 37s595ms 35s960ms -
Connections
Established Connections
Key values
- 40 connections Connection Peak
- 2025-07-22 22:11:00 Date
Connections per database
Key values
- acaweb_fx Main Database
- 5,631 connections Total
Connections per user
Key values
- postgres Main User
- 5,631 connections Total
Connections per host
Key values
- 192.168.1.15 Main host with 1862 connections
- 5,631 Total connections
Host Count 127.0.0.1 115 192.168.0.114 2 192.168.0.216 99 192.168.0.74 1,013 192.168.1.145 85 192.168.1.15 1,862 192.168.1.20 107 192.168.1.231 20 192.168.1.239 16 192.168.1.90 64 192.168.2.126 62 192.168.2.182 24 192.168.2.205 12 192.168.2.82 48 192.168.3.199 36 192.168.4.142 1,335 192.168.4.150 10 192.168.4.197 1 192.168.4.229 4 192.168.4.238 16 192.168.4.33 90 192.168.4.98 330 [local] 280 -
Sessions
Simultaneous sessions
Key values
- 15 sessions Session Peak
- 2025-07-22 22:38:08 Date
Histogram of session times
Key values
- 4,572 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 5,630 sessions Total
Sessions per user
Key values
- postgres Main User
- 5,630 sessions Total
Sessions per host
Key values
- 192.168.1.15 Main Host
- 5,630 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 115 7s545ms 65ms 192.168.0.114 2 10m 5m 192.168.0.216 99 53s220ms 537ms 192.168.0.74 1,013 3h19m24s 11s810ms 192.168.1.145 85 4h5m58s 2m53s 192.168.1.15 1,862 6h35m44s 12s752ms 192.168.1.20 107 14h13m18s 7m58s 192.168.1.231 20 9h53m51s 29m41s 192.168.1.239 16 190ms 11ms 192.168.1.90 64 47s885ms 748ms 192.168.2.126 62 6s741ms 108ms 192.168.2.182 24 6s507ms 271ms 192.168.2.205 12 497ms 41ms 192.168.2.82 48 7s965ms 165ms 192.168.3.199 36 1s345ms 37ms 192.168.4.142 1,335 21m22s 960ms 192.168.4.150 10 20h1m22s 2h8s 192.168.4.197 1 205ms 205ms 192.168.4.229 4 38ms 9ms 192.168.4.238 16 30s561ms 1s910ms 192.168.4.33 89 1m8s 768ms 192.168.4.98 330 15s196ms 46ms [local] 280 2m33s 547ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 10,924 buffers Checkpoint Peak
- 2025-07-22 22:04:24 Date
- 209.988 seconds Highest write time
- 0.017 seconds Sync time
Checkpoints Wal files
Key values
- 5 files Wal files usage Peak
- 2025-07-22 22:09:24 Date
Checkpoints distance
Key values
- 159.11 Mo Distance Peak
- 2025-07-22 22:09:24 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Jul 22 22 73,098 2,090.485s 0.061s 2,090.881s Day Hour Added Removed Recycled Synced files Longest sync Average sync Jul 22 22 0 0 27 2,060 0.006s 0s Day Hour Count Avg time (sec) Jul 22 22 0 0s Day Hour Mean distance Mean estimate Jul 22 22 36,543.00 kB 63,136.75 kB -
Temporary Files
Size of temporary files
Key values
- 166.89 MiB Temp Files size Peak
- 2025-07-22 22:00:11 Date
Number of temporary files
Key values
- 62 per second Temp Files Peak
- 2025-07-22 22:47:08 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Jul 22 22 811 4.39 GiB 5.54 MiB Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 185 800.81 MiB 3.30 MiB 9.61 MiB 4.33 MiB with rar_max as ( ;-
WITH rar_max as ( ;
Date: 2025-07-22 22:00:19 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver
2 40 1.65 GiB 3.01 MiB 153.28 MiB 42.16 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 = ? ), 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: 2025-07-22 22:00:11 Duration: 9s398ms 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: 2025-07-22 22:30:10 Duration: 7s919ms 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: 2025-07-22 22:10:10 Duration: 7s668ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
3 16 488.25 MiB 30.52 MiB 30.52 MiB 30.52 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: 2025-07-22 22:26:14 Duration: 2s773ms 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: 2025-07-22 22:31:14 Duration: 2s88ms 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: 2025-07-22 22:01:14 Duration: 1s975ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
4 16 876.73 MiB 54.79 MiB 54.80 MiB 54.80 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: 2025-07-22 22:26:19 Duration: 4s184ms 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: 2025-07-22 22:31:17 Duration: 3s500ms 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: 2025-07-22 22:01:17 Duration: 3s372ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
5 8 291.56 MiB 36.43 MiB 36.45 MiB 36.45 MiB select updateresultsmaterializedview ();-
select updateresultsmaterializedview ();
Date: 2025-07-22 22:02:14 Duration: 2s125ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-07-22 22:17:14 Duration: 2s95ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-07-22 22:50:34 Duration: 2s85ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
6 4 339.93 MiB 84.91 MiB 85.08 MiB 84.98 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2025-07-22 22:32:12 Duration: 10s284ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-07-22 22:17:12 Duration: 10s230ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-07-22 22:02:12 Duration: 10s207ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
7 1 4.24 MiB 4.24 MiB 4.24 MiB 4.24 MiB select resultuid from relevance_fibonacci_results order by resultuid desc limit ?), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp)))), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;-
SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4, $5, $6, $7, $8, $9, $10)) AND ($11 = 0 OR s.exchange in ($12)) AND ($13 = 0 OR coalesce(bim.code, s.symbol) in ($14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226)) AND ($227 = 0 OR fr.pattern in ($228)) AND ($229 = 0 OR fr.patternlengthbars <= $230) AND ($231 = 0 OR ($232 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($233 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $234 OR relevant = 1) AND ($235 = 0 OR age <= $236) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-07-22 22:12:08 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver
Queries generating the largest temporary files
Rank Size Query 1 153.28 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: 2025-07-22 22:10:07 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
2 132.05 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: 2025-07-22 22:40:05 ]
3 115.19 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: 2025-07-22 22:50:04 ]
4 88.13 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-07-22 22:20:04 ]
5 85.08 MiB select updateageforrelevantresults ();[ Date: 2025-07-22 22:02:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
6 85.00 MiB select updateageforrelevantresults ();[ Date: 2025-07-22 22:32:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
7 84.94 MiB select updateageforrelevantresults ();[ Date: 2025-07-22 22:17:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
8 84.91 MiB select updateageforrelevantresults ();[ Date: 2025-07-22 22:47:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
9 84.10 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: 2025-07-22 22:30:04 ]
10 80.12 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: 2025-07-22 22:00:05 ]
11 79.68 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-07-22 22:20:04 ]
12 74.89 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-07-22 22:30:04 ]
13 72.14 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: 2025-07-22 22:00:05 ]
14 67.32 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: 2025-07-22 22:30:04 ]
15 62.97 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-07-22 22:50:09 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
16 61.95 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-07-22 22:40:05 ]
17 61.15 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: 2025-07-22 22:20:05 ]
18 54.80 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: 2025-07-22 22:11:15 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
19 54.80 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: 2025-07-22 22:16:16 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
20 54.80 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: 2025-07-22 22:18:15 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
-
Vacuums
Vacuums / Analyzes Distribution
Key values
- 0 sec Highest CPU-cost vacuum
Table
Database - Date
- 0 sec Highest CPU-cost analyze
Table
Database - Date
Analyzes per table
Key values
- public.solr_relevance_old (16) Main table analyzed (database acaweb_fx)
- 55 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 16 acaweb_fx.pg_catalog.pg_attribute 7 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 3 acaweb_fx.public.relevance_autochartist_results 3 acaweb_fx.public.autochartist_symbolupdates 2 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.pg_catalog.pg_index 1 acaweb_fx.public.solr_imports 1 acaweb_fx.public.consecutivecandles_results 1 acaweb_fx.pg_catalog.pg_depend 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.relevance_consecutivecandles_results 1 Total 55 Vacuums per table
Key values
- public.solr_relevance_old (17) Main table vacuumed on database acaweb_fx
- 37 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 17 16 14,754 0 49 0 0 10,104 16 1,848,744 acaweb_fx.public.datafeeds_latestrun 4 0 456 0 10 0 0 65 8 60,603 acaweb_fx.pg_toast.pg_toast_2619 2 2 348 0 65 0 0 217 54 214,530 acaweb_fx.pg_catalog.pg_attribute 2 2 1,838 0 301 0 134 773 298 1,758,511 acaweb_fx.public.relevance_keylevels_results 2 2 8,248 0 368 4 155 2,083 502 1,854,952 acaweb_fx.public.relevance_autochartist_results 2 2 7,173 0 255 2 460 1,484 237 553,682 acaweb_fx.public.relevance_fibonacci_results 2 2 2,727 0 67 0 90 499 50 142,092 acaweb_fx.pg_catalog.pg_index 1 1 105 0 14 0 0 28 11 83,034 acaweb_fx.pg_catalog.pg_type 1 1 165 0 23 0 0 55 22 112,447 acaweb_fx.public.autochartist_symbolupdates 1 1 24,954 0 5,785 0 38,027 7,991 5,500 1,907,609 acaweb_fx.pg_catalog.pg_statistic 1 1 964 0 203 0 614 433 187 743,262 acaweb_fx.public.latest_t15_candle_view 1 1 66 0 1 0 0 6 1 9,055 acaweb_fx.pg_catalog.pg_class 1 1 378 0 31 0 40 125 30 159,328 Total 37 32 62,176 43,963 7,172 6 39,520 23,863 6,916 9,447,849 Tuples removed per table
Key values
- public.solr_relevance_old (62355) Main table with removed tuples on database acaweb_fx
- 76117 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 17 16 62,355 111,541 7,560 0 3,739 acaweb_fx.public.autochartist_symbolupdates 1 1 5,986 46,841 0 0 40,691 acaweb_fx.pg_catalog.pg_attribute 2 2 2,809 18,746 0 0 500 acaweb_fx.public.relevance_keylevels_results 2 2 2,100 24,168 0 0 558 acaweb_fx.public.relevance_autochartist_results 2 2 1,052 16,771 0 0 760 acaweb_fx.pg_catalog.pg_statistic 1 1 709 4,162 0 0 1,194 acaweb_fx.public.relevance_fibonacci_results 2 2 316 3,228 0 0 204 acaweb_fx.public.datafeeds_latestrun 4 0 258 61 5 0 64 acaweb_fx.pg_catalog.pg_type 1 1 156 1,338 0 0 38 acaweb_fx.pg_toast.pg_toast_2619 2 2 150 347 1 3 102 acaweb_fx.pg_catalog.pg_class 1 1 143 1,947 0 0 150 acaweb_fx.public.latest_t15_candle_view 1 1 63 14 0 0 1 acaweb_fx.pg_catalog.pg_index 1 1 20 813 0 0 22 Total 37 32 76,117 229,977 7,566 3 48,023 Pages removed per table
Key values
- pg_toast.pg_toast_2619 (3) Main table with removed pages on database acaweb_fx
- 3 pages Total removed
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_toast.pg_toast_2619 2 2 150 3 acaweb_fx.pg_catalog.pg_index 1 1 20 0 acaweb_fx.pg_catalog.pg_type 1 1 156 0 acaweb_fx.public.autochartist_symbolupdates 1 1 5986 0 acaweb_fx.public.datafeeds_latestrun 4 0 258 0 acaweb_fx.pg_catalog.pg_statistic 1 1 709 0 acaweb_fx.pg_catalog.pg_attribute 2 2 2809 0 acaweb_fx.public.latest_t15_candle_view 1 1 63 0 acaweb_fx.public.relevance_keylevels_results 2 2 2100 0 acaweb_fx.pg_catalog.pg_class 1 1 143 0 acaweb_fx.public.solr_relevance_old 17 16 62355 0 acaweb_fx.public.relevance_autochartist_results 2 2 1052 0 acaweb_fx.public.relevance_fibonacci_results 2 2 316 0 Total 37 32 76,117 3 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Jul 22 22 37 55 - 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
- 65,142 Total read queries
- 39,945 Total write queries
Queries by database
Key values
- acaweb_fx Main database
- 106,814 Requests
- 2h33m17s (acaweb_fx)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 106,814 2h33m17s copy from 96 6s961ms copy to 26 6s650ms cte 5,616 2h29m24s ddl 16 502ms delete 16 26ms insert 24,004 19s947ms others 9,439 10s272ms select 64,782 2m40s tcl 664 193ms update 2,155 28s263ms socialmedia Total 7,712 8s774ms insert 7,292 8s410ms select 360 253ms update 60 110ms Queries by user
Key values
- postgres Main user
- 114,526 Requests
User Request type Count Duration postgres Total 114,526 2h33m26s copy from 96 6s961ms copy to 26 6s650ms cte 5,616 2h29m24s ddl 16 502ms delete 16 26ms insert 31,296 28s358ms others 9,439 10s272ms select 65,142 2m40s tcl 664 193ms update 2,215 28s374ms Duration by user
Key values
- 2h33m26s (postgres) Main time consuming user
User Request type Count Duration postgres Total 114,526 2h33m26s copy from 96 6s961ms copy to 26 6s650ms cte 5,616 2h29m24s ddl 16 502ms delete 16 26ms insert 31,296 28s358ms others 9,439 10s272ms select 65,142 2m40s tcl 664 193ms update 2,215 28s374ms Queries by host
Key values
- 192.168.1.15 Main host
- 21,675 Requests
- 37m18s (192.168.0.74)
- Main time consuming host
Host Request type Count Duration 127.0.0.1 Total 12,762 29s743ms copy to 26 6s650ms cte 24 272ms insert 10,268 8s482ms select 843 13s472ms update 1,601 865ms 182.165.1.42 Total 160 7m44s cte 60 7m43s select 100 78ms 192.168.0.114 Total 10 105ms others 2 0ms select 4 104ms tcl 4 0ms 192.168.0.216 Total 396 401ms others 198 26ms select 190 266ms update 8 108ms 192.168.0.236 Total 20 6ms cte 2 1ms select 18 5ms 192.168.0.239 Total 451 302ms select 451 302ms 192.168.0.42 Total 1,051 622ms insert 295 24ms select 756 597ms 192.168.0.74 Total 16,286 37m18s cte 1,977 37m10s others 2,026 23ms select 12,283 8s54ms 192.168.1.135 Total 74 795ms cte 8 719ms select 66 76ms 192.168.1.145 Total 14,574 33m19s cte 781 33m others 170 2ms select 13,623 19s98ms 192.168.1.15 Total 21,675 35m58s cte 1,859 35m46s others 3,724 59ms select 16,092 12s71ms 192.168.1.20 Total 16,496 34m8s cte 783 33m46s others 214 2ms select 15,499 21s850ms 192.168.1.201 Total 1,268 1s268ms select 1,268 1s268ms 192.168.1.210 Total 68 1ms select 68 1ms 192.168.1.23 Total 1,220 730ms select 1,220 730ms 192.168.1.231 Total 40 0ms others 40 0ms 192.168.1.239 Total 64 38ms others 32 2ms select 32 35ms 192.168.1.90 Total 120 45s479ms cte 6 45s359ms others 32 0ms select 82 118ms 192.168.1.97 Total 32 9ms cte 3 1ms select 29 7ms 192.168.2.126 Total 80 76ms others 18 0ms select 62 76ms 192.168.2.182 Total 96 841ms others 48 5ms select 24 23ms update 24 812ms 192.168.2.205 Total 138 139ms insert 90 7ms others 24 2ms select 20 23ms update 4 105ms 192.168.2.82 Total 1,138 2s90ms insert 739 1s199ms others 96 10ms select 181 107ms update 122 773ms 192.168.3.199 Total 144 293ms others 72 9ms select 60 79ms update 12 204ms 192.168.4.142 Total 17,026 11s660ms insert 12,612 10s233ms others 2,670 30ms select 1,744 1s396ms 192.168.4.150 Total 22 893ms others 21 0ms select 1 892ms 192.168.4.197 Total 3 56ms cte 1 56ms others 2 0ms 192.168.4.229 Total 12 1ms others 8 0ms select 4 1ms 192.168.4.238 Total 48 29s538ms cte 16 29s537ms others 32 0ms 192.168.4.33 Total 7,712 8s774ms insert 7,292 8s410ms select 360 253ms update 60 110ms 192.168.4.98 Total 996 10s723ms others 6 9s822ms select 6 33ms tcl 660 193ms update 324 674ms [local] Total 344 2m32s copy from 96 6s961ms cte 96 40s852ms ddl 16 502ms delete 16 26ms others 4 273ms select 56 1m19s update 60 24s718ms Queries by application
Key values
- PostgreSQL JDBC Driver Main application
- 85,909 Requests
- 2h21m30s (PostgreSQL JDBC Driver)
- Main time consuming application
Application Request type Count Duration PostgreSQL JDBC Driver Total 85,909 2h21m30s cte 5,425 2h20m14s insert 12,907 10s258ms others 4,466 63ms select 63,111 1m6s [unknown] Total 28,158 9m15s cte 71 8m29s insert 18,389 18s99ms others 4,969 9s936ms select 1,923 14s473ms tcl 664 193ms update 2,142 3s629ms psql Total 459 2m39s copy from 96 6s961ms copy to 26 6s650ms cte 120 41s125ms ddl 16 502ms delete 16 26ms others 4 273ms select 108 1m19s update 73 24s744ms Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2025-07-22 22:31:17 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 71,453 0-1ms duration
Slowest individual queries
Rank Duration Query 1 1m2s 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: 2025-07-22 22:27:09 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
2 46s552ms 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: 2025-07-22 22:40:05 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
3 44s932ms 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: 2025-07-22 22:00:44 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
4 44s406ms 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: 2025-07-22 22:10:26 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
5 43s921ms 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: 2025-07-22 22:50:16 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
6 40s711ms 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: 2025-07-22 22:10:31 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
7 38s352ms 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: 2025-07-22 22:15:23 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
8 37s343ms 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: 2025-07-22 22:15:55 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
9 37s132ms 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: 2025-07-22 22:21:13 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
10 37s120ms 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: 2025-07-22 22:20:21 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
11 36s914ms 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: 2025-07-22 22:41:34 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
12 36s880ms 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: 2025-07-22 22:50:59 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
13 36s880ms 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: 2025-07-22 22:32:12 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
14 36s602ms 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: 2025-07-22 22:29:35 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
15 36s591ms 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: 2025-07-22 22:25:02 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
16 36s506ms 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: 2025-07-22 22:36:33 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
17 36s227ms 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: 2025-07-22 22:02:14 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
18 29s529ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.patternlengthbars <= '400') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-07-22 22:26:28 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
19 27s432ms 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: 2025-07-22 22:26:21 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
20 26s634ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.patternlengthbars <= '400') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-07-22 22:31:20 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
Time consuming queries
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 1h9m1s 428 169ms 1m2s 9s677ms 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 #1
Day Hour Count Duration Avg duration Jul 22 22 428 1h9m1s 9s677ms [ User: postgres - Total duration: 1h9m1s - Times executed: 428 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h5m35s - Times executed: 416 ]
[ Application: [unknown] - Total duration: 3m26s - 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: 2025-07-22 22:27:09 Duration: 1m2s 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: 2025-07-22 22:40:05 Duration: 46s552ms 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: 2025-07-22 22:00:44 Duration: 44s932ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
2 57m 425 323ms 27s432ms 8s49ms 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 Jul 22 22 425 57m 8s49ms [ User: postgres - Total duration: 57m - Times executed: 425 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 54m2s - Times executed: 413 ]
[ Application: [unknown] - Total duration: 2m58s - 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: 2025-07-22 22:26:21 Duration: 27s432ms 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_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: 2025-07-22 22:26:17 Duration: 25s418ms 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: 2025-07-22 22:49:36 Duration: 25s186ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
3 18m50s 387 530ms 10s244ms 2s919ms 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 Jul 22 22 387 18m50s 2s919ms [ User: postgres - Total duration: 18m50s - Times executed: 387 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 17m43s - Times executed: 375 ]
[ Application: [unknown] - Total duration: 1m6s - 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: 2025-07-22 22:26:28 Duration: 10s244ms 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: 2025-07-22 22:26:31 Duration: 9s644ms 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_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: 2025-07-22 22:40:04 Duration: 9s248ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
4 1m35s 242 73ms 1s423ms 396ms 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 Jul 22 22 242 1m35s 396ms [ User: postgres - Total duration: 1m35s - Times executed: 242 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m24s - Times executed: 230 ]
[ Application: [unknown] - Total duration: 11s478ms - 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: 2025-07-22 22:26:30 Duration: 1s423ms 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: 2025-07-22 22:50:05 Duration: 1s379ms 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_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: 2025-07-22 22:56:08 Duration: 1s377ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
5 51s451ms 135 135ms 1s56ms 381ms 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 #5
Day Hour Count Duration Avg duration Jul 22 22 135 51s451ms 381ms [ User: postgres - Total duration: 51s451ms - Times executed: 135 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 51s451ms - Times executed: 135 ]
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '538' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '538' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-07-22 22:00:06 Duration: 1s56ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 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: 2025-07-22 22:00:02 Duration: 884ms 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: 2025-07-22 22:12:19 Duration: 880ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
6 45s359ms 6 5s510ms 9s398ms 7s559ms 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 #6
Day Hour Count Duration Avg duration Jul 22 22 6 45s359ms 7s559ms [ User: postgres - Total duration: 45s359ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 45s359ms - 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: 2025-07-22 22:00:11 Duration: 9s398ms 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: 2025-07-22 22:30:10 Duration: 7s919ms 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: 2025-07-22 22:10:10 Duration: 7s668ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
7 40s825ms 4 10s102ms 10s284ms 10s206ms select updateageforrelevantresults ();Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Jul 22 22 4 40s825ms 10s206ms [ User: postgres - Total duration: 40s825ms - Times executed: 4 ]
[ Application: psql - Total duration: 40s825ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-07-22 22:32:12 Duration: 10s284ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-07-22 22:17:12 Duration: 10s230ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-07-22 22:02:12 Duration: 10s207ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
8 38s477ms 16 1s936ms 4s184ms 2s404ms 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 #8
Day Hour Count Duration Avg duration Jul 22 22 16 38s477ms 2s404ms [ User: postgres - Total duration: 38s477ms - Times executed: 16 ]
[ Application: psql - Total duration: 38s477ms - 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: 2025-07-22 22:26:19 Duration: 4s184ms 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: 2025-07-22 22:31:17 Duration: 3s500ms 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: 2025-07-22 22:01:17 Duration: 3s372ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
9 31s111ms 20,084 0ms 21ms 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 #9
Day Hour Count Duration Avg duration Jul 22 22 20,084 31s111ms 1ms [ User: postgres - Total duration: 31s111ms - Times executed: 20084 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 31s111ms - Times executed: 20084 ]
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840249425757300';
Date: 2025-07-22 22:00:04 Duration: 21ms 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 = '515840243156977300';
Date: 2025-07-22 22:30:07 Duration: 19ms 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 = '515840216981464300';
Date: 2025-07-22 22:30:07 Duration: 18ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
10 29s537ms 16 1s300ms 3s337ms 1s846ms 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 #10
Day Hour Count Duration Avg duration Jul 22 22 16 29s537ms 1s846ms [ User: postgres - Total duration: 29s537ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 29s537ms - Times executed: 16 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '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: 2025-07-22 22:37:01 Duration: 3s337ms 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 = '692' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '692' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '692' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-07-22 22:37:10 Duration: 2s720ms 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: 2025-07-22 22:36:46 Duration: 2s270ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
11 26s138ms 8,101 0ms 38ms 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 #11
Day Hour Count Duration Avg duration Jul 22 22 8,101 26s138ms 3ms [ User: postgres - Total duration: 26s138ms - Times executed: 8101 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 26s138ms - Times executed: 8101 ]
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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 = 'EUSTX50' OR dss.downloadersymbol = 'EUSTX50') AND dss.enabled = 1;
Date: 2025-07-22 22:00:05 Duration: 38ms 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 = 'ETHUSD' OR dss.downloadersymbol = 'ETHUSD') AND dss.enabled = 1;
Date: 2025-07-22 22:00:06 Duration: 33ms 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 = 'XAGUSD' OR dss.downloadersymbol = 'XAGUSD') AND dss.enabled = 1;
Date: 2025-07-22 22:15:05 Duration: 33ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
12 24s228ms 16 1s226ms 2s773ms 1s514ms 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 #12
Day Hour Count Duration Avg duration Jul 22 22 16 24s228ms 1s514ms [ User: postgres - Total duration: 24s228ms - Times executed: 16 ]
[ Application: psql - Total duration: 24s228ms - 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: 2025-07-22 22:26:14 Duration: 2s773ms 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: 2025-07-22 22:31:14 Duration: 2s88ms 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: 2025-07-22 22:01:14 Duration: 1s975ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
13 16s999ms 34 12ms 6s147ms 499ms select fixcandlegaps (?, false);Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jul 22 22 34 16s999ms 499ms [ User: postgres - Total duration: 16s999ms - Times executed: 34 ]
[ Application: psql - Total duration: 16s999ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-07-22 22:06:19 Duration: 6s147ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-07-22 22:06:06 Duration: 2s181ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('AXIORY', false);
Date: 2025-07-22 22:06:08 Duration: 1s537ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
14 16s514ms 8 2s3ms 2s125ms 2s64ms select updateresultsmaterializedview ();Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Jul 22 22 8 16s514ms 2s64ms [ User: postgres - Total duration: 16s514ms - Times executed: 8 ]
[ Application: psql - Total duration: 16s514ms - Times executed: 8 ]
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select updateresultsmaterializedview ();
Date: 2025-07-22 22:02:14 Duration: 2s125ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-07-22 22:17:14 Duration: 2s95ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-07-22 22:50:34 Duration: 2s85ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
15 9s822ms 6 1s54ms 2s403ms 1s637ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Jul 22 22 6 9s822ms 1s637ms [ User: postgres - Total duration: 9s822ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 9s822ms - Times executed: 6 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-07-22 22:31:18 Duration: 2s403ms 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: 2025-07-22 22:09:18 Duration: 2s17ms 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: 2025-07-22 22:49:18 Duration: 1s629ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
16 8s284ms 152 16ms 330ms 54ms select distinct a.symbolid, p.resultuid, case when a.breakout >= ? then ? else ? end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient from relevance_autochartist_results p inner join autochartist_results a on p.resultuid = a.resultuid inner join autochartist_stocklist asl on a.symbolid = asl.symbolid where asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Jul 22 22 152 8s284ms 54ms [ User: postgres - Total duration: 8s284ms - Times executed: 152 ]
[ Application: [unknown] - Total duration: 8s284ms - Times executed: 152 ]
-
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: 2025-07-22 22:31:14 Duration: 330ms 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 'AXIORY - 1';
Date: 2025-07-22 22:31:13 Duration: 256ms 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 'AXIORY - 1';
Date: 2025-07-22 22:30:57 Duration: 160ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
17 8s44ms 7,016 0ms 6ms 1ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Jul 22 22 7,016 8s44ms 1ms [ User: postgres - Total duration: 8s44ms - Times executed: 7016 ]
[ Application: [unknown] - Total duration: 8s44ms - Times executed: 7016 ]
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INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 33, schedule: 0 15 * * 2 Africa/Johannesburg', NULL, NULL);
Date: 2025-07-22 22:09:49 Duration: 6ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
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INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 174, schedule: 0 9 * * 1 Africa/Johannesburg', NULL, NULL);
Date: 2025-07-22 22:11:49 Duration: 5ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
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INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 95, schedule: 0 1 * * * Africa/Johannesburg', NULL, NULL);
Date: 2025-07-22 22:57:49 Duration: 4ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
18 6s726ms 6,601 0ms 16ms 1ms insert into t15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Jul 22 22 6,601 6s726ms 1ms [ User: postgres - Total duration: 6s726ms - Times executed: 6601 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 6s726ms - Times executed: 6601 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-07-22 20:15:00', '1.793085', '1.79323', '1.792865', '1.793095', '929500000', '515840249735021300', '0', '2025-07-22 22:30:57.466', '2025-07-22 22:30:52.364') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '1.793085', high = '1.79323', low = '1.792865', close = '1.793095', volume = '929500000', bsf = '0', sastdatetimewritten = '2025-07-22 22:30:57.466', sastdatetimereceived = '2025-07-22 22:30:52.364';
Date: 2025-07-22 22:30:57 Duration: 16ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-07-22 16:30:00', '233.675', '236.78', '233.31', '236.655', '170', '515840249449481300', '0', '2025-07-22 22:30:06.786', '2025-07-22 22:30:06.743') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '233.675', high = '236.78', low = '233.31', close = '236.655', volume = '170', bsf = '0', sastdatetimewritten = '2025-07-22 22:30:06.786', sastdatetimereceived = '2025-07-22 22:30:06.743';
Date: 2025-07-22 22:30:06 Duration: 12ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-07-22 23:15:00', '4.2508', '4.2508', '4.25064', '4.2507', '73', '515840216977303300', '0', '2025-07-22 22:30:51.246', '2025-07-22 22:30:46.624') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '4.2508', high = '4.2508', low = '4.25064', close = '4.2507', volume = '73', bsf = '0', sastdatetimewritten = '2025-07-22 22:30:51.246', sastdatetimereceived = '2025-07-22 22:30:46.624';
Date: 2025-07-22 22:30:51 Duration: 12ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
19 6s272ms 80 6ms 296ms 78ms copy solr_relevance_old (uuid, relevant, age, result_uid) from stdin with ( format csv, header);Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Jul 22 22 80 6s272ms 78ms [ User: postgres - Total duration: 6s272ms - Times executed: 80 ]
[ Application: psql - Total duration: 6s272ms - Times executed: 80 ]
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COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2025-07-22 22:56:14 Duration: 296ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2025-07-22 22:26:15 Duration: 196ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2025-07-22 22:03:13 Duration: 195ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
20 4s949ms 152 16ms 172ms 32ms 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 Jul 22 22 152 4s949ms 32ms [ User: postgres - Total duration: 4s949ms - Times executed: 152 ]
[ Application: [unknown] - Total duration: 4s949ms - Times executed: 152 ]
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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: 2025-07-22 22:31:01 Duration: 172ms 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: 2025-07-22 22:01:12 Duration: 122ms 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: 2025-07-22 22:15:35 Duration: 117ms 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 29,514 144ms 0ms 3ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jul 22 22 29,514 144ms 0ms [ User: postgres - Total duration: 144ms - Times executed: 29514 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 132ms - Times executed: 29264 ]
[ Application: [unknown] - Total duration: 11ms - Times executed: 250 ]
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select 1;
Date: 2025-07-22 22:40:59 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-07-22 22:31:03 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-07-22 22:39:59 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
2 20,084 31s111ms 0ms 21ms 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 Jul 22 22 20,084 31s111ms 1ms [ User: postgres - Total duration: 31s111ms - Times executed: 20084 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 31s111ms - Times executed: 20084 ]
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840249425757300';
Date: 2025-07-22 22:00:04 Duration: 21ms 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 = '515840243156977300';
Date: 2025-07-22 22:30:07 Duration: 19ms 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 = '515840216981464300';
Date: 2025-07-22 22:30:07 Duration: 18ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
3 8,101 26s138ms 0ms 38ms 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 Jul 22 22 8,101 26s138ms 3ms [ User: postgres - Total duration: 26s138ms - Times executed: 8101 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 26s138ms - Times executed: 8101 ]
-
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 = 'EUSTX50' OR dss.downloadersymbol = 'EUSTX50') AND dss.enabled = 1;
Date: 2025-07-22 22:00:05 Duration: 38ms 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 = 'ETHUSD' OR dss.downloadersymbol = 'ETHUSD') AND dss.enabled = 1;
Date: 2025-07-22 22:00:06 Duration: 33ms 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 = 'XAGUSD' OR dss.downloadersymbol = 'XAGUSD') AND dss.enabled = 1;
Date: 2025-07-22 22:15:05 Duration: 33ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
4 7,016 8s44ms 0ms 6ms 1ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Jul 22 22 7,016 8s44ms 1ms [ User: postgres - Total duration: 8s44ms - Times executed: 7016 ]
[ Application: [unknown] - Total duration: 8s44ms - Times executed: 7016 ]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 33, schedule: 0 15 * * 2 Africa/Johannesburg', NULL, NULL);
Date: 2025-07-22 22:09:49 Duration: 6ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 174, schedule: 0 9 * * 1 Africa/Johannesburg', NULL, NULL);
Date: 2025-07-22 22:11:49 Duration: 5ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 95, schedule: 0 1 * * * Africa/Johannesburg', NULL, NULL);
Date: 2025-07-22 22:57:49 Duration: 4ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
5 6,601 6s726ms 0ms 16ms 1ms insert into t15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Jul 22 22 6,601 6s726ms 1ms [ User: postgres - Total duration: 6s726ms - Times executed: 6601 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 6s726ms - Times executed: 6601 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-07-22 20:15:00', '1.793085', '1.79323', '1.792865', '1.793095', '929500000', '515840249735021300', '0', '2025-07-22 22:30:57.466', '2025-07-22 22:30:52.364') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '1.793085', high = '1.79323', low = '1.792865', close = '1.793095', volume = '929500000', bsf = '0', sastdatetimewritten = '2025-07-22 22:30:57.466', sastdatetimereceived = '2025-07-22 22:30:52.364';
Date: 2025-07-22 22:30:57 Duration: 16ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-07-22 16:30:00', '233.675', '236.78', '233.31', '236.655', '170', '515840249449481300', '0', '2025-07-22 22:30:06.786', '2025-07-22 22:30:06.743') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '233.675', high = '236.78', low = '233.31', close = '236.655', volume = '170', bsf = '0', sastdatetimewritten = '2025-07-22 22:30:06.786', sastdatetimereceived = '2025-07-22 22:30:06.743';
Date: 2025-07-22 22:30:06 Duration: 12ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-07-22 23:15:00', '4.2508', '4.2508', '4.25064', '4.2507', '73', '515840216977303300', '0', '2025-07-22 22:30:51.246', '2025-07-22 22:30:46.624') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '4.2508', high = '4.2508', low = '4.25064', close = '4.2507', volume = '73', bsf = '0', sastdatetimewritten = '2025-07-22 22:30:51.246', sastdatetimereceived = '2025-07-22 22:30:46.624';
Date: 2025-07-22 22:30:51 Duration: 12ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
6 5,573 4s310ms 0ms 11ms 0ms 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 #6
Day Hour Count Duration Avg duration Jul 22 22 5,573 4s310ms 0ms [ User: postgres - Total duration: 4s310ms - Times executed: 5573 ]
[ Application: [unknown] - Total duration: 4s310ms - Times executed: 5573 ]
-
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 ('5009916282625652000.3533|45860.7917|45860.9271|45860.7083|45860.9062|39.248|39.289|38.721|39.145', 500991628262565200, 2.000000000000000000000000000000, 'Rising Wedge', 4, '2025-07-22 20:26:19'::timestamp without time zone, - 1, 0.485649254540581054600000000000, 0.353266434568880349800000000000, 0.000000000000000000000000000000, 0.156847058823538443300000000000, 0.901197250605519029000000000000, 38.859585664231062200000000000000, 39.097827360096275130000000000000, '2025-07-22 23:15:00'::timestamp without time zone, '2025-07-23 02:22:30'::timestamp without time zone, '2025-07-22 16:00:00'::timestamp without time zone, '2025-07-22 23:15:00'::timestamp without time zone, 39.210000000000000850000000000000, 39.278894736842104860000000000000, '2025-07-22 19:00:00'::timestamp without time zone, '2025-07-22 22:15:00'::timestamp without time zone, '2025-07-22 17:00:00'::timestamp without time zone, '2025-07-22 21:45:00'::timestamp without time zone, 39.247999999999997560000000000000, 39.289000000000001480000000000000, 38.720999999999996530000000000000, 39.145000000000003130000000000000, 0.022315789473684555930000000000, 0.003153846153846455620000000000, 2.823394980080590422000000000000, 0.645816470222860483600000000000, 'Continuation', - 0.010894736842104180140000000000, '2025-07-22 23:15:00'::timestamp without time zone, 39.268000000000000680000000000000, 25, 0, 0.128999999999998976600000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-07-22 22:31:04 Duration: 11ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('515840249424905300-1|45756.8333|45853.6667|45754.6667|45768.8333|115.06|172.385|86.645|95.045', 515840249424905300, 5.000000000000000000000000000000, 'Channel Up', 4, '2025-07-22 20:16:45'::timestamp without time zone, - 1, 0.839195402274765411800000000000, - 1.000000000000000000000000000000, 0.403580859285895932000000000000, 0.336260421864604475200000000000, 0.173303271023444310800000000000, 148.702876034205644400000000000000, 159.816615014252335000000000000000, '2025-07-22 16:00:00'::timestamp without time zone, '2025-09-13 16:00:00'::timestamp without time zone, '2025-03-24 20:00:00'::timestamp without time zone, '2025-07-22 16:00:00'::timestamp without time zone, 122.069999999999993200000000000000, 164.599999999999994300000000000000, '2025-04-09 20:00:00'::timestamp without time zone, '2025-07-15 16:00:00'::timestamp without time zone, '2025-04-07 16:00:00'::timestamp without time zone, '2025-04-21 20:00:00'::timestamp without time zone, 115.060000000000002300000000000000, 172.384999999999990900000000000000, 86.644999999999996020000000000000, 95.045000000000001710000000000000, 0.442105263157895056500000000000, 0.444379844961240222400000000000, 2.266268838217250892000000000000, 0.558746083811201721400000000000, 'Continuation', 0.000000000000000000000000000000, '2025-07-22 16:00:00'::timestamp without time zone, 167.754999999999995400000000000000, 144, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-07-22 22:21:29 Duration: 9ms 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 ('515840249514206300-1|45847.5|45860.3333|45840.3333|45856.3333|737.53|717.4867|711.8026|691.65', 515840249514206300, 3.000000000000000000000000000000, 'Channel Down', 4, '2025-07-22 20:11:33'::timestamp without time zone, - 1, 0.433101301948991324000000000000, - 1.000000000000000000000000000000, 0.292186063867404533000000000000, 0.301621616259742653100000000000, 0.449801121824233984800000000000, 690.347102461111035200000000000000, 699.839626025462962400000000000000, '2025-07-22 12:00:00'::timestamp without time zone, '2025-08-01 14:00:00'::timestamp without time zone, '2025-06-30 08:00:00'::timestamp without time zone, '2025-07-22 12:00:00'::timestamp without time zone, 748.600000000000022800000000000000, 702.419999999999959000000000000000, '2025-07-09 12:00:00'::timestamp without time zone, '2025-07-22 08:00:00'::timestamp without time zone, '2025-07-02 08:00:00'::timestamp without time zone, '2025-07-18 08:00:00'::timestamp without time zone, 737.529999999999972700000000000000, 717.486700000000041600000000000000, 711.802599999999984000000000000000, 691.649999999999977200000000000000, - 0.610684848484848719000000000000, - 0.770896153846151177600000000000, 2.114583362153613866000000000000, 0.527093602504494218600000000000, 'Continuation', 0.000000000000000000000000000000, '2025-07-22 12:00:00'::timestamp without time zone, 706.620000000000004600000000000000, 40, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-07-22 22:16:17 Duration: 9ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
7 4,491 56ms 0ms 7ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Jul 22 22 4,491 56ms 0ms [ User: postgres - Total duration: 56ms - Times executed: 4491 ]
[ Application: [unknown] - Total duration: 56ms - Times executed: 4491 ]
-
SET extra_float_digits = 3;
Date: 2025-07-22 22:05:47 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2025-07-22 22:17:23 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2025-07-22 22:15:40 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: [unknown] Bind query: yes
8 4,465 63ms 0ms 2ms 0ms set application_name = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Jul 22 22 4,465 63ms 0ms [ User: postgres - Total duration: 63ms - Times executed: 4465 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 63ms - Times executed: 4465 ]
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-07-22 22:17:10 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-07-22 22:47:43 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-07-22 22:09:00 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
9 3,626 2s118ms 0ms 21ms 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 #9
Day Hour Count Duration Avg duration Jul 22 22 3,626 2s118ms 0ms [ User: postgres - Total duration: 2s118ms - Times executed: 3626 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s118ms - Times executed: 3626 ]
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-07-22 23:00:00', '2920.09', '2921.84', '2918.97', '2919.53', '3056', '515840247937025300', '0', '2025-07-22 22:30:04.581', '2025-07-22 22:30:04.52') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '2920.09', high = '2921.84', low = '2918.97', close = '2919.53', volume = '3056', bsf = '0', sastdatetimewritten = '2025-07-22 22:30:04.581', sastdatetimereceived = '2025-07-22 22:30:04.52';
Date: 2025-07-22 22:30:04 Duration: 21ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-07-22 23:00:00', '2.06481', '2.06492', '2.0642', '2.06465', '1890', '515840216972953300', '0', '2025-07-22 22:30:51.852', '2025-07-22 22:30:51.851') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '2.06481', high = '2.06492', low = '2.0642', close = '2.06465', volume = '1890', bsf = '0', sastdatetimewritten = '2025-07-22 22:30:51.852', sastdatetimereceived = '2025-07-22 22:30:51.851';
Date: 2025-07-22 22:30:51 Duration: 8ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-07-22 23:00:00', '8.223', '8.229', '8.22', '8.227', '190', '515840247926031300', '0', '2025-07-22 22:31:06.851', '2025-07-22 22:31:06.524') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '8.223', high = '8.229', low = '8.22', close = '8.227', volume = '190', bsf = '0', sastdatetimewritten = '2025-07-22 22:31:06.851', sastdatetimereceived = '2025-07-22 22:31:06.524';
Date: 2025-07-22 22:31:06 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
10 2,752 1s463ms 0ms 9ms 0ms insert into fibonacci_results (bandwidth, pattern, gmttimefound, direction, patternstarttime, patternendtime, patternstartprice, patternendprice, qtytp, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, patternlengthbars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) values (?.?, ?, ?::timestamp without time zone, ?, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?, ?, ?, ?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Jul 22 22 2,752 1s463ms 0ms [ User: postgres - Total duration: 1s463ms - Times executed: 2752 ]
[ Application: [unknown] - Total duration: 1s463ms - Times executed: 2752 ]
-
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, '3 Drive', '2025-07-22 19:57:28'::timestamp without time zone, - 1, '2025-07-22 06:00:00'::timestamp without time zone, '2025-07-22 22:30:00'::timestamp without time zone, 0.520789999999999975200000000000, - 1.000000000000000000000000000000, 5, 0.520789999999999975200000000000, '2025-07-22 06:00:00'::timestamp without time zone, 0.518429999999999946400000000000, '2025-07-22 10:30:00'::timestamp without time zone, 0.521540000000000003600000000000, '2025-07-22 16:30:00'::timestamp without time zone, 0.519020000000000036900000000000, '2025-07-22 20:00:00'::timestamp without time zone, 0.522225489516739971300000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.689342476743421084200000000000, - 1.000000000000000000000000000000, 25.305974152282612260000000000000, 37, 0.519020000000000036900000000000, 0.520244388044973193900000000000, 0.517038898528233259400000000000, 0.519705489516631424800000000000, 0.518148043865180540900000000000, 0.520622744758370004100000000000, 0.521001101471766814300000000000, 515840243159885300, 0.621315046513157720500000000000, 'AB=1.272*XA (1.318) BC=0.786*AB (0.81) ', 0, '3 Drive|-1|2025-07-22 06:00:00|0.52079|-1|5|37|AB=1.272*XA (1.318)","BC=0.786*AB (0.81)|0|515840243159885300|2025-07-22 06:00:00|2025-07-22 10:30:00|2025-07-22 16:30:00|2025-07-22 20:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-07-22 22:02:13 Duration: 9ms 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, '3 Point Extension', '2025-07-22 20:12:01'::timestamp without time zone, 1, '2025-07-16 08:00:00'::timestamp without time zone, '2025-07-22 12:00:00'::timestamp without time zone, 65.420000000000001700000000000000, 65.519999999999996020000000000000, 3, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 65.420000000000001700000000000000, '2025-07-16 08:00:00'::timestamp without time zone, 67.689999999999997720000000000000, '2025-07-17 12:00:00'::timestamp without time zone, 64.819999999999993180000000000000, '2025-07-22 12:00:00'::timestamp without time zone, 0.301447227114890248200000000000, - 1.000000000000000000000000000000, 0.121106130495442609900000000000, 26, 67.689999999999997720000000000000, 66.593757547568998240000000000000, 69.463757547569002780000000000000, 67.076254454286001300000000000000, 68.470696394065001300000000000000, 66.254999999999995460000000000000, 65.916242452430992670000000000000, 515840224839238300, 0.518211676265662113400000000000, 'CD=1.272*BC (1.264) ', 0, '3 Point Extension|1|2025-07-16 08:00:00|65.42|65.52|3|26|CD=1.272*BC (1.264)|0|515840224839238300|1899-12-29 00:00:00|1899-12-29 00:00:00|2025-07-16 08:00:00|2025-07-17 12:00:00|2025-07-22 12:00:00', 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-07-22 22:16:45 Duration: 5ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, 'ABCD', '2025-07-22 20:27:26'::timestamp without time zone, 1, '2025-07-22 07:00:00'::timestamp without time zone, '2025-07-22 23:00:00'::timestamp without time zone, 24168.409999999999860000000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 24242.770000000000440000000000000000, '2025-07-22 10:00:00'::timestamp without time zone, 23917.500000000000000000000000000000, '2025-07-22 17:00:00'::timestamp without time zone, 24108.560000000001310000000000000000, '2025-07-22 22:30:00'::timestamp without time zone, 23783.290000000000870000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.872502658284519228000000000000, - 1.000000000000000000000000000000, 121.554038613007975300000000000000, 39, 24108.560000000001310000000000000000, 23984.317915504449050000000000000000, 24309.587915504449480000000000000000, 24039.001458657006880000000000000000, 24197.039831392867200000000000000000, 23945.925000000002910000000000000000, 23907.532084495553140000000000000000, 605679104902420300, 0.254994683430961433000000000000, 'BC=0.618*AB (0.587) ', 0, 'ABCD|1|2025-07-22 07:00:00|24168.41|-1|4|39|BC=0.618*AB (0.587)|0|605679104902420300|1899-12-29 00:00:00|2025-07-22 10:00:00|2025-07-22 17:00:00|2025-07-22 22:30:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-07-22 22:32:10 Duration: 5ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
11 2,303 1s267ms 0ms 21ms 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jul 22 22 2,303 1s267ms 0ms [ User: postgres - Total duration: 1s267ms - Times executed: 2303 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s267ms - Times executed: 2303 ]
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-07-22 22:00:00', '36.52', '37.03', '36.5', '36.59', '1691', '515840247893649300', '0', '2025-07-22 22:00:06.965', '2025-07-22 22:00:06.894') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '36.52', high = '37.03', low = '36.5', close = '36.59', volume = '1691', bsf = '0', sastdatetimewritten = '2025-07-22 22:00:06.965', sastdatetimereceived = '2025-07-22 22:00:06.894';
Date: 2025-07-22 22:00:06 Duration: 21ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-07-22 22:00:00', '44481.25', '44542.25', '44470.25', '44501.25', '6940', '515840248000890300', '0', '2025-07-22 22:11:00.703', '2025-07-22 22:11:00.66') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '44481.25', high = '44542.25', low = '44470.25', close = '44501.25', volume = '6940', bsf = '0', sastdatetimewritten = '2025-07-22 22:11:00.703', sastdatetimereceived = '2025-07-22 22:11:00.66';
Date: 2025-07-22 22:11:00 Duration: 10ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-07-22 22:00:00', '318.22', '319.3', '315.53', '316.15', '664', '515840247954113300', '0', '2025-07-22 22:01:05.509', '2025-07-22 22:01:05.438') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '318.22', high = '319.3', low = '315.53', close = '316.15', volume = '664', bsf = '0', sastdatetimewritten = '2025-07-22 22:01:05.509', sastdatetimereceived = '2025-07-22 22:01:05.438';
Date: 2025-07-22 22:01:05 Duration: 8ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
12 1,893 3s577ms 0ms 30ms 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 Jul 22 22 1,893 3s577ms 1ms [ User: postgres - Total duration: 3s577ms - Times executed: 1893 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s575ms - Times executed: 1888 ]
[ Application: [unknown] - Total duration: 2ms - Times executed: 5 ]
-
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 = '606506982606840301' 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 = '606506982606840301' OR a.resultuid = '606506982606840301') AND dtt.dayofweek = 3;
Date: 2025-07-22 22:00:16 Duration: 30ms 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_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 = '606507454257824301' 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 = '606507454257824301' OR a.resultuid = '606507454257824301') AND dtt.dayofweek = 3;
Date: 2025-07-22 22:25:59 Duration: 20ms 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_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 = '606506861583190301' 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 = '606506861583190301' OR a.resultuid = '606506861583190301') AND dtt.dayofweek = 3;
Date: 2025-07-22 22:26:14 Duration: 20ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
13 1,809 2s438ms 0ms 7ms 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 #13
Day Hour Count Duration Avg duration Jul 22 22 1,809 2s438ms 1ms [ User: postgres - Total duration: 2s438ms - Times executed: 1809 ]
[ Application: [unknown] - Total duration: 2s438ms - Times executed: 1809 ]
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INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (9.000000000000000000000000000000, - 1, 1, '2025-07-22 20:26:27'::timestamp without time zone, '', 0.500000000000000000000000000000, 6, 190, 17622.000000000000000000000000000000, '2025-07-22 21:15:00', '2025-07-21 17:45:00', '2025-07-21 14:15:00', '2025-07-21 07:30:00', '2025-07-21 05:00:00', '2025-07-20 21:45:00', '', '', '', '', 665, 17691.275000000001460000000000000000, '2025-07-22 23:15:00'::timestamp without time zone, '2025-07-22 23:15:00', 0.000000000000000000000000000000, 74.475000000000008520000000000000, - 1, 515840249396921300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249396921300|17622|1|2025-07-22 23:15:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-07-20 21:45:00', 18045.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-07-22 22:31:11 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (10.000000000000000000000000000000, - 1, 1, '2025-07-22 20:16:07'::timestamp without time zone, '', 0.500000000000000000000000000000, 5, 396, 159.169999999999987500000000000000, '2025-07-22 16:45:00', '2025-07-02 18:30:00', '2025-06-30 21:15:00', '2025-06-30 16:30:00', '2025-06-27 18:45:00', '', '', '', '', '', 1188, 159.844999999999998900000000000000, '2025-07-22 22:45:00'::timestamp without time zone, '2025-07-22 22:45:00', 0.000000000000000000000000000000, 0.675000000000000044400000000000, - 1, 515840249447810300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249447810300|159.17|1|2025-07-22 22:45:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-06-27 18:45:00', 160.789999999999992000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-07-22 22:20:52 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (4.000000000000000000000000000000, - 1, 2, '2025-07-22 20:16:19'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 119, 226.115000000000009100000000000000, '2025-07-22 19:15:00', '2025-07-22 17:00:00', '2025-07-15 22:00:00', '', '', '', '', '', '', '', 238, 225.758750000000020500000000000000, '2025-07-22 22:45:00'::timestamp without time zone, '2025-07-22 22:45:00', 0.000000000000000000000000000000, 0.356250000000000011100000000000, 1, 515840249418515300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249418515300|226.115|2|2025-07-22 22:45:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-07-15 22:00:00', 222.210000000000008000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-07-22 22:21:03 Duration: 6ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
14 1,588 839ms 0ms 4ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Jul 22 22 1,588 839ms 0ms [ User: postgres - Total duration: 839ms - Times executed: 1588 ]
[ Application: [unknown] - Total duration: 839ms - Times executed: 1588 ]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-07-22 21:00:00', reason = 'Price has entered the prediction area for a completed pattern' WHERE uniqueIndex = '5158402494247333001|45856.6667|45859.875|45854.75|45859.7917|174.22|172.81|168.92|171.46' and relevant = 1;
Date: 2025-07-22 22:21:29 Duration: 4ms 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 = '2025-07-22 16:00:00', reason = 'Emerging pattern formed a completed pattern.' WHERE uniqueIndex = '515840249436800300-1|45807.8333|45839.6667|45826.8333|45853.6667|170.985|162.51|157.66|151.9' and relevant = 1;
Date: 2025-07-22 22:21:19 Duration: 3ms 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 = '2025-07-22 12:00:00', reason = 'Emerging pattern formed a completed pattern.' WHERE uniqueIndex = '515840249488377300-1|45856.3333|45859.3333|45855|45859|1.5996|1.603|1.5883|1.5946' and relevant = 1;
Date: 2025-07-22 22:01:05 Duration: 3ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
15 1,544 1s139ms 0ms 14ms 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 Jul 22 22 1,544 1s139ms 0ms [ User: postgres - Total duration: 1s139ms - Times executed: 1544 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s139ms - Times executed: 1544 ]
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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 = '606506747592565303' 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 = '606506747592565303' OR a.resultuid = '606506747592565303') AND dtt.dayofweek = 3;
Date: 2025-07-22 22:09:11 Duration: 14ms 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 ) SELECT CASE WHEN a.old_resultuid = '606507221789465303' 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 = '606507221789465303' OR a.resultuid = '606507221789465303') AND dtt.dayofweek = 3;
Date: 2025-07-22 22:10:18 Duration: 12ms 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 ) SELECT CASE WHEN a.old_resultuid = '606506751783421303' 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 = '606506751783421303' OR a.resultuid = '606506751783421303') AND dtt.dayofweek = 3;
Date: 2025-07-22 22:12:30 Duration: 10ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
16 822 1s243ms 0ms 9ms 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 #16
Day Hour Count Duration Avg duration Jul 22 22 822 1s243ms 1ms [ User: postgres - Total duration: 1s243ms - Times executed: 822 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s243ms - Times executed: 822 ]
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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 = 'MILLENNIUMPF' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-07-22 22:30:50 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver 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 = 'AXIORY' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-07-22 22:16:02 Duration: 6ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver 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: 2025-07-22 22:31:03 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
17 822 142ms 0ms 0ms 0ms select downloadersymbol, spike_threshold from price_datafeed_spike_threshold where classname = ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Jul 22 22 822 142ms 0ms [ User: postgres - Total duration: 142ms - Times executed: 822 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 142ms - Times executed: 822 ]
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SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'BDSWISS';
Date: 2025-07-22 22:00:59 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'PEPPERSTONEMT5';
Date: 2025-07-22 22:30:08 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'BDSWISS';
Date: 2025-07-22 22:15:52 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
18 576 251ms 0ms 5ms 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 #18
Day Hour Count Duration Avg duration Jul 22 22 576 251ms 0ms [ User: postgres - Total duration: 251ms - Times executed: 576 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 251ms - Times executed: 576 ]
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SELECT CASE WHEN a.old_resultuid = '606503916641871301' 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 = '606503916641871301' OR a.resultuid = '606503916641871301') AND dtt.dayofweek = 3;
Date: 2025-07-22 22:10:00 Duration: 5ms 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 = '606507572202634301' 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 = '606507572202634301' OR a.resultuid = '606507572202634301') AND dtt.dayofweek = 3;
Date: 2025-07-22 22:43:52 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '606507454006967301' 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 = '606507454006967301' OR a.resultuid = '606507454006967301') AND dtt.dayofweek = 3;
Date: 2025-07-22 22:20:01 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
19 482 15ms 0ms 0ms 0ms select df.absolutetimezoneoffset from datafeedstimetable df inner join downloadersymbolsettings dss on df.classname = dss.classname where dss.symbolid = ? group by df.absolutetimezoneoffset limit ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Jul 22 22 482 15ms 0ms [ User: postgres - Total duration: 15ms - Times executed: 482 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 15ms - Times executed: 482 ]
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '515840249648326300' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-07-22 22:53:24 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '515840243266602300' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-07-22 22:03:01 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '515840217503418300' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-07-22 22:33:28 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
20 428 1h9m1s 169ms 1m2s 9s677ms 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 #20
Day Hour Count Duration Avg duration Jul 22 22 428 1h9m1s 9s677ms [ User: postgres - Total duration: 1h9m1s - Times executed: 428 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h5m35s - Times executed: 416 ]
[ Application: [unknown] - Total duration: 3m26s - 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: 2025-07-22 22:27:09 Duration: 1m2s 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: 2025-07-22 22:40:05 Duration: 46s552ms 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: 2025-07-22 22:00:44 Duration: 44s932ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 10s102ms 10s284ms 10s206ms 4 40s825ms select updateageforrelevantresults ();Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jul 22 22 4 40s825ms 10s206ms [ User: postgres - Total duration: 40s825ms - Times executed: 4 ]
[ Application: psql - Total duration: 40s825ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-07-22 22:32:12 Duration: 10s284ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-07-22 22:17:12 Duration: 10s230ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-07-22 22:02:12 Duration: 10s207ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
2 169ms 1m2s 9s677ms 428 1h9m1s 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 Jul 22 22 428 1h9m1s 9s677ms [ User: postgres - Total duration: 1h9m1s - Times executed: 428 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h5m35s - Times executed: 416 ]
[ Application: [unknown] - Total duration: 3m26s - 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: 2025-07-22 22:27:09 Duration: 1m2s 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: 2025-07-22 22:40:05 Duration: 46s552ms 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: 2025-07-22 22:00:44 Duration: 44s932ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
3 323ms 27s432ms 8s49ms 425 57m 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 #3
Day Hour Count Duration Avg duration Jul 22 22 425 57m 8s49ms [ User: postgres - Total duration: 57m - Times executed: 425 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 54m2s - Times executed: 413 ]
[ Application: [unknown] - Total duration: 2m58s - 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: 2025-07-22 22:26:21 Duration: 27s432ms 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_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: 2025-07-22 22:26:17 Duration: 25s418ms 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: 2025-07-22 22:49:36 Duration: 25s186ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
4 5s510ms 9s398ms 7s559ms 6 45s359ms 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 Jul 22 22 6 45s359ms 7s559ms [ User: postgres - Total duration: 45s359ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 45s359ms - 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: 2025-07-22 22:00:11 Duration: 9s398ms 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: 2025-07-22 22:30:10 Duration: 7s919ms 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: 2025-07-22 22:10:10 Duration: 7s668ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
5 530ms 10s244ms 2s919ms 387 18m50s 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 Jul 22 22 387 18m50s 2s919ms [ User: postgres - Total duration: 18m50s - Times executed: 387 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 17m43s - Times executed: 375 ]
[ Application: [unknown] - Total duration: 1m6s - 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: 2025-07-22 22:26:28 Duration: 10s244ms 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: 2025-07-22 22:26:31 Duration: 9s644ms 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_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: 2025-07-22 22:40:04 Duration: 9s248ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
6 1s936ms 4s184ms 2s404ms 16 38s477ms 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 Jul 22 22 16 38s477ms 2s404ms [ User: postgres - Total duration: 38s477ms - Times executed: 16 ]
[ Application: psql - Total duration: 38s477ms - 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: 2025-07-22 22:26:19 Duration: 4s184ms 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: 2025-07-22 22:31:17 Duration: 3s500ms 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: 2025-07-22 22:01:17 Duration: 3s372ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
7 2s3ms 2s125ms 2s64ms 8 16s514ms select updateresultsmaterializedview ();Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Jul 22 22 8 16s514ms 2s64ms [ User: postgres - Total duration: 16s514ms - Times executed: 8 ]
[ Application: psql - Total duration: 16s514ms - Times executed: 8 ]
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select updateresultsmaterializedview ();
Date: 2025-07-22 22:02:14 Duration: 2s125ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-07-22 22:17:14 Duration: 2s95ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-07-22 22:50:34 Duration: 2s85ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
8 1s300ms 3s337ms 1s846ms 16 29s537ms 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 Jul 22 22 16 29s537ms 1s846ms [ User: postgres - Total duration: 29s537ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 29s537ms - Times executed: 16 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '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: 2025-07-22 22:37:01 Duration: 3s337ms 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 = '692' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '692' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '692' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-07-22 22:37:10 Duration: 2s720ms 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: 2025-07-22 22:36:46 Duration: 2s270ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
9 1s54ms 2s403ms 1s637ms 6 9s822ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jul 22 22 6 9s822ms 1s637ms [ User: postgres - Total duration: 9s822ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 9s822ms - Times executed: 6 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-07-22 22:31:18 Duration: 2s403ms 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: 2025-07-22 22:09:18 Duration: 2s17ms 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: 2025-07-22 22:49:18 Duration: 1s629ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
10 1s226ms 2s773ms 1s514ms 16 24s228ms 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 Jul 22 22 16 24s228ms 1s514ms [ User: postgres - Total duration: 24s228ms - Times executed: 16 ]
[ Application: psql - Total duration: 24s228ms - 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: 2025-07-22 22:26:14 Duration: 2s773ms 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: 2025-07-22 22:31:14 Duration: 2s88ms 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: 2025-07-22 22:01:14 Duration: 1s975ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 12ms 6s147ms 499ms 34 16s999ms select fixcandlegaps (?, false);Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jul 22 22 34 16s999ms 499ms [ User: postgres - Total duration: 16s999ms - Times executed: 34 ]
[ Application: psql - Total duration: 16s999ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-07-22 22:06:19 Duration: 6s147ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-07-22 22:06:06 Duration: 2s181ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('AXIORY', false);
Date: 2025-07-22 22:06:08 Duration: 1s537ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
12 73ms 1s423ms 396ms 242 1m35s 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 Jul 22 22 242 1m35s 396ms [ User: postgres - Total duration: 1m35s - Times executed: 242 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m24s - Times executed: 230 ]
[ Application: [unknown] - Total duration: 11s478ms - 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: 2025-07-22 22:26:30 Duration: 1s423ms 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: 2025-07-22 22:50:05 Duration: 1s379ms 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_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: 2025-07-22 22:56:08 Duration: 1s377ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
13 135ms 1s56ms 381ms 135 51s451ms 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 Jul 22 22 135 51s451ms 381ms [ User: postgres - Total duration: 51s451ms - Times executed: 135 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 51s451ms - Times executed: 135 ]
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '538' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '538' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-07-22 22:00:06 Duration: 1s56ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 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: 2025-07-22 22:00:02 Duration: 884ms 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: 2025-07-22 22:12:19 Duration: 880ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
14 6ms 296ms 78ms 80 6s272ms copy solr_relevance_old (uuid, relevant, age, result_uid) from stdin with ( format csv, header);Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Jul 22 22 80 6s272ms 78ms [ User: postgres - Total duration: 6s272ms - Times executed: 80 ]
[ Application: psql - Total duration: 6s272ms - Times executed: 80 ]
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COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2025-07-22 22:56:14 Duration: 296ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2025-07-22 22:26:15 Duration: 196ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2025-07-22 22:03:13 Duration: 195ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
15 16ms 330ms 54ms 152 8s284ms 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 Jul 22 22 152 8s284ms 54ms [ User: postgres - Total duration: 8s284ms - Times executed: 152 ]
[ Application: [unknown] - Total duration: 8s284ms - Times executed: 152 ]
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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: 2025-07-22 22:31:14 Duration: 330ms 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 'AXIORY - 1';
Date: 2025-07-22 22:31:13 Duration: 256ms 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 'AXIORY - 1';
Date: 2025-07-22 22:30:57 Duration: 160ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
16 16ms 172ms 32ms 152 4s949ms 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 #16
Day Hour Count Duration Avg duration Jul 22 22 152 4s949ms 32ms [ User: postgres - Total duration: 4s949ms - Times executed: 152 ]
[ Application: [unknown] - Total duration: 4s949ms - Times executed: 152 ]
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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: 2025-07-22 22:31:01 Duration: 172ms 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: 2025-07-22 22:01:12 Duration: 122ms 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: 2025-07-22 22:15:35 Duration: 117ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
17 0ms 38ms 3ms 8,101 26s138ms 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 Jul 22 22 8,101 26s138ms 3ms [ User: postgres - Total duration: 26s138ms - Times executed: 8101 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 26s138ms - Times executed: 8101 ]
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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 = 'EUSTX50' OR dss.downloadersymbol = 'EUSTX50') AND dss.enabled = 1;
Date: 2025-07-22 22:00:05 Duration: 38ms 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 = 'ETHUSD' OR dss.downloadersymbol = 'ETHUSD') AND dss.enabled = 1;
Date: 2025-07-22 22:00:06 Duration: 33ms 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 = 'XAGUSD' OR dss.downloadersymbol = 'XAGUSD') AND dss.enabled = 1;
Date: 2025-07-22 22:15:05 Duration: 33ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
18 0ms 30ms 1ms 1,893 3s577ms 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 #18
Day Hour Count Duration Avg duration Jul 22 22 1,893 3s577ms 1ms [ User: postgres - Total duration: 3s577ms - Times executed: 1893 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s575ms - Times executed: 1888 ]
[ Application: [unknown] - Total duration: 2ms - Times executed: 5 ]
-
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 = '606506982606840301' 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 = '606506982606840301' OR a.resultuid = '606506982606840301') AND dtt.dayofweek = 3;
Date: 2025-07-22 22:00:16 Duration: 30ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ) SELECT a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, CASE WHEN a.old_resultuid = '606507454257824301' 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 = '606507454257824301' OR a.resultuid = '606507454257824301') AND dtt.dayofweek = 3;
Date: 2025-07-22 22:25:59 Duration: 20ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ) SELECT a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, CASE WHEN a.old_resultuid = '606506861583190301' 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 = '606506861583190301' OR a.resultuid = '606506861583190301') AND dtt.dayofweek = 3;
Date: 2025-07-22 22:26:14 Duration: 20ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
19 0ms 21ms 1ms 20,084 31s111ms 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 #19
Day Hour Count Duration Avg duration Jul 22 22 20,084 31s111ms 1ms [ User: postgres - Total duration: 31s111ms - Times executed: 20084 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 31s111ms - Times executed: 20084 ]
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840249425757300';
Date: 2025-07-22 22:00:04 Duration: 21ms 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 = '515840243156977300';
Date: 2025-07-22 22:30:07 Duration: 19ms 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 = '515840216981464300';
Date: 2025-07-22 22:30:07 Duration: 18ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
20 0ms 9ms 1ms 822 1s243ms 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 Jul 22 22 822 1s243ms 1ms [ User: postgres - Total duration: 1s243ms - Times executed: 822 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s243ms - Times executed: 822 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'MILLENNIUMPF' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-07-22 22:30:50 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver 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 = 'AXIORY' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-07-22 22:16:02 Duration: 6ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver 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: 2025-07-22 22:31:03 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 6s176ms 6,910 0ms 13ms 0ms SELECT ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Jul 22 22 6,910 6s176ms 0ms [ User: postgres - Total duration: 11s949ms - Times executed: 6910 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 11s938ms - Times executed: 6897 ]
[ Application: [unknown] - Total duration: 10ms - Times executed: 13 ]
-
SELECT ;
Date: 2025-07-22 22:13:01 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
SELECT ;
Date: 2025-07-22 22:20:12 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
SELECT ;
Date: 2025-07-22 22:40:29 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
2 3s739ms 3,478 0ms 13ms 1ms WITH rar_max as ( ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 22 3,478 3s739ms 1ms [ User: postgres - Total duration: 1h43m29s - Times executed: 3478 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h43m29s - Times executed: 3474 ]
[ Application: [unknown] - Total duration: 2ms - Times executed: 4 ]
-
WITH rar_max as ( ;
Date: 2025-07-22 22:08:00 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
WITH rar_max as ( ;
Date: 2025-07-22 22:22:11 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
WITH rar_max as ( ;
Date: 2025-07-22 22:22:41 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
3 1s50ms 822 0ms 10ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 22 822 1s50ms 1ms [ User: postgres - Total duration: 1s243ms - Times executed: 822 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s243ms - Times executed: 822 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-07-22 22:31:00 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-07-22 22:30:06 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-07-22 22:01:03 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
4 630ms 4,491 0ms 6ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 22 4,491 630ms 0ms [ User: postgres - Total duration: 56ms - Times executed: 4491 ]
[ Application: [unknown] - Total duration: 56ms - Times executed: 4491 ]
-
SET extra_float_digits = 3;
Date: 2025-07-22 22:12:30 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
SET extra_float_digits = 3;
Date: 2025-07-22 22:38:29 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
SET extra_float_digits = 3;
Date: 2025-07-22 22:30:04 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
5 502ms 1,199 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 #5
Day Hour Count Duration Avg duration 22 1,199 502ms 0ms [ User: postgres - Total duration: 3s652ms - Times executed: 1199 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s652ms - Times executed: 1199 ]
-
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: 2025-07-22 22:00:09 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: 2025-07-22 22:30:51 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: 2025-07-22 22:32:05 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
6 370ms 5,373 0ms 10ms 0ms select 1;Times Reported Time consuming prepare #6
Day Hour Count Duration Avg duration 22 5,373 370ms 0ms [ User: postgres - Total duration: 35ms - Times executed: 5373 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 35ms - Times executed: 5373 ]
-
select 1;
Date: 2025-07-22 22:26:14 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
select 1;
Date: 2025-07-22 22:21:22 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
select 1;
Date: 2025-07-22 22:34:59 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
7 300ms 2,871 0ms 1ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 22 2,871 300ms 0ms [ User: postgres - Total duration: 1s813ms - Times executed: 2871 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s813ms - Times executed: 2871 ]
-
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: 2025-07-22 22:31:14 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: 2025-07-22 22:31:08 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: 2025-07-22 22:30:48 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
8 219ms 1,781 0ms 0ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #8
Day Hour Count Duration Avg duration 22 1,781 219ms 0ms [ User: postgres - Total duration: 1s41ms - Times executed: 1781 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s41ms - Times executed: 1781 ]
-
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: 2025-07-22 22:01:03 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: 2025-07-22 22:02:36 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: 2025-07-22 22:00:43 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
9 82ms 16 4ms 7ms 5ms with sym_info as ( ;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 22 16 82ms 5ms [ User: postgres - Total duration: 29s537ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 29s537ms - Times executed: 16 ]
-
with sym_info as ( ;
Date: 2025-07-22 22:21:50 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
-
with sym_info as ( ;
Date: 2025-07-22 22:21:43 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
-
with sym_info as ( ;
Date: 2025-07-22 22:21:41 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
10 56ms 4,465 0ms 2ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 22 4,465 56ms 0ms [ User: postgres - Total duration: 63ms - Times executed: 4465 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 63ms - Times executed: 4465 ]
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-07-22 22:12:00 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-07-22 22:21:52 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-07-22 22:07:17 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
11 52ms 48 0ms 5ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 22 48 52ms 1ms [ User: postgres - Total duration: 20s634ms - Times executed: 48 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 20s634ms - Times executed: 48 ]
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WITH last_candle AS ( ;
Date: 2025-07-22 22:00:04 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
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WITH last_candle AS ( ;
Date: 2025-07-22 22:16:14 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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WITH last_candle AS ( ;
Date: 2025-07-22 22:00:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
12 50ms 18 1ms 4ms 2ms select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 22 18 50ms 2ms [ User: postgres - Total duration: 45ms - Times executed: 18 ]
[ Application: [unknown] - Total duration: 45ms - Times executed: 18 ]
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select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-07-22 22:01:01 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
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select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-07-22 22:01:01 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-07-22 22:31:01 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
13 21ms 6 3ms 3ms 3ms 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 #13
Day Hour Count Duration Avg duration 22 6 21ms 3ms [ User: postgres - Total duration: 45s359ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 45s359ms - 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: 2025-07-22 22:50:02 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: 2025-07-22 22:00:02 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: 2025-07-22 22:40:02 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
14 20ms 6 3ms 3ms 3ms select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 22 6 20ms 3ms [ User: postgres - Total duration: 17ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 17ms - 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: 2025-07-22 22:40:04 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: 2025-07-22 22:50:04 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: 2025-07-22 22:20:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
15 18ms 12 0ms 8ms 1ms 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 #15
Day Hour Count Duration Avg duration 22 12 18ms 1ms [ User: postgres - Total duration: 16ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 16ms - Times executed: 12 ]
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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: 2025-07-22 22:30:52 Duration: 8ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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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: 2025-07-22 22:40:54 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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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: 2025-07-22 22:10:50 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
16 17ms 24 0ms 0ms 0ms select count(*) from datafeed_restarter_events where is_current_entry = 1;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 22 24 17ms 0ms [ User: postgres - Total duration: 62ms - Times executed: 24 ]
[ Application: [unknown] - Total duration: 62ms - Times executed: 24 ]
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select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-07-22 22:10:03 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-07-22 22:50:05 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
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select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-07-22 22:00:03 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
17 17ms 36 0ms 1ms 0ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 22 36 17ms 0ms [ User: postgres - Total duration: 0ms - Times executed: 36 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 0ms - Times executed: 36 ]
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WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-07-22 22:00:44 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
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WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-07-22 22:17:38 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
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WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-07-22 22:38:44 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
18 16ms 12 1ms 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 #18
Day Hour Count Duration Avg duration 22 12 16ms 1ms [ User: postgres - Total duration: 45ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 45ms - Times executed: 12 ]
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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: 2025-07-22 22:40:54 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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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: 2025-07-22 22:30:52 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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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: 2025-07-22 22:10:50 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
19 11ms 82 0ms 0ms 0ms INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 22 82 11ms 0ms [ User: postgres - Total duration: 121ms - Times executed: 82 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 121ms - Times executed: 82 ]
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INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-07-22 22:18:04 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-07-22 22:17:42 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-07-22 22:17:34 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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 22 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: 2025-07-22 22:05:39 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: 2025-07-22 22:21:01 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: 2025-07-22 22:16:20 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 41s305ms 5,258 0ms 65ms 7ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Jul 22 22 5,258 41s305ms 7ms [ User: postgres - Total duration: 2h25m21s - Times executed: 5258 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2h17m37s - Times executed: 5193 ]
[ Application: [unknown] - Total duration: 7m43s - Times executed: 65 ]
-
WITH rar_max as ( ;
Date: 2025-07-22 22:26:30 Duration: 65ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '529', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '183', $13 = 'AUDUSD', $14 = 'EURUSD', $15 = 'GBPUSD', $16 = 'USDCAD', $17 = 'USDCHF', $18 = 'USDJPY', $19 = 'XAGAUD', $20 = 'XAGEUR', $21 = 'XAGUSD', $22 = 'XAUAUD', $23 = 'XAUCHF', $24 = 'XAUEUR', $25 = 'XAUGBP', $26 = 'XAUJPY', $27 = 'XAUUSD', $28 = 'XPDUSD', $29 = 'XPTUSD', $30 = 'AUS200', $31 = 'CA60', $32 = 'CHINAH', $33 = 'CN50', $34 = 'EUSTX50', $35 = 'FRA40', $36 = 'GER40', $37 = 'GERTEC30', $38 = 'HK50', $39 = 'JPN225', $40 = 'MidDE50', $41 = 'NAS100', $42 = 'NETH25', $43 = 'NOR25', $44 = 'SA40', $45 = 'SCI25', $46 = 'SPA35', $47 = 'SWI20', $48 = 'UK100', $49 = 'US2000', $50 = 'US30', $51 = 'US500', $52 = 'VIX', $53 = 'AUDCAD', $54 = 'AUDCHF', $55 = 'AUDNZD', $56 = 'AUDSGD', $57 = 'EURAUD', $58 = 'EURCHF', $59 = 'EURGBP', $60 = 'GBPAUD', $61 = 'GBPCHF', $62 = 'NZDUSD', $63 = 'CHFSGD', $64 = 'EURCZK', $65 = 'EURHUF', $66 = 'EURMXN', $67 = 'EURNOK', $68 = 'EURPLN', $69 = 'EURSEK', $70 = 'EURSGD', $71 = 'EURTRY', $72 = 'EURZAR', $73 = 'GBPMXN', $74 = 'GBPNOK', $75 = 'GBPSEK', $76 = 'GBPSGD', $77 = 'GBPTRY', $78 = 'NOKJPY', $79 = 'NOKSEK', $80 = 'NZDCAD', $81 = 'NZDCHF', $82 = 'SEKJPY', $83 = 'SGDJPY', $84 = 'USDCNH', $85 = 'USDCZK', $86 = 'USDHKD', $87 = 'USDHUF', $88 = 'USDMXN', $89 = 'USDNOK', $90 = 'USDPLN', $91 = 'USDSEK', $92 = 'USDSGD', $93 = 'USDTHB', $94 = 'USDTRY', $95 = 'USDZAR', $96 = 'ZARJPY', $97 = 'ADAUSD', $98 = 'AVAXUSD', $99 = 'BCHUSD', $100 = 'BNBUSD', $101 = 'BTCUSD', $102 = 'Crypto10', $103 = 'Crypto20', $104 = 'Crypto30', $105 = 'DOGEUSD', $106 = 'DOTUSD', $107 = 'EOSUSD', $108 = 'ETHUSD', $109 = 'LINKUSD', $110 = 'LTCUSD', $111 = 'MATICUSD', $112 = 'SOLUSD', $113 = 'UNIUSD', $114 = 'XLMUSD', $115 = 'XRPUSD', $116 = 'XTZUSD', $117 = 'EURX', $118 = 'JPYX', $119 = 'USDX', $120 = 'Gasoline', $121 = 'NatGas', $122 = 'SpotBrent', $123 = 'SpotCrude', $124 = 'AAPL.US', $125 = 'ABNB.US', $126 = 'AMD.US', $127 = 'AMZN.US', $128 = 'AXP.US', $129 = 'BA.US', $130 = 'BABA.US', $131 = 'BIDU.US', $132 = 'BYND.US', $133 = 'C.US', $134 = 'COIN.US', $135 = 'CRM.US', $136 = 'DIS.US', $137 = 'EA.US', $138 = 'GOOG.US', $139 = 'GS.US', $140 = 'IBM.US', $141 = 'JPM.US', $142 = 'LMT.US', $143 = 'MA.US', $144 = 'MCD.US', $145 = 'META.US', $146 = 'MRNA.US', $147 = 'MSFT.US', $148 = 'NFLX.US', $149 = 'NKE.US', $150 = 'NVDA.US', $151 = 'ORCL.US', $152 = 'PFE.US', $153 = 'PG.US', $154 = 'PLTR.US', $155 = 'PTON.US', $156 = 'PYPL.US', $157 = 'QCOM.US', $158 = 'SNAP.US', $159 = 'SPCE.US', $160 = 'SPY.US', $161 = 'T.US', $162 = 'TMUS.US', $163 = 'TSLA.US', $164 = 'UBER.US', $165 = 'V.US', $166 = 'WMT.US', $167 = 'ZM.US', $168 = 'Cattle', $169 = 'Cocoa', $170 = 'Coffee', $171 = 'Corn', $172 = 'Cotton', $173 = 'LDSugar', $174 = 'LeanHogs', $175 = 'LondonSugar', $176 = 'Lumber', $177 = 'OJ', $178 = 'Oats', $179 = 'RghRice', $180 = 'SoyMeal', $181 = 'SoyOil', $182 = 'Soybeans', $183 = 'Sugar', $184 = 'Wheat', $185 = 'AUDJPY', $186 = 'CADCHF', $187 = 'CADJPY', $188 = 'CHFJPY', $189 = 'EURCAD', $190 = 'EURJPY', $191 = 'EURNZD', $192 = 'GBPCAD', $193 = 'GBPJPY', $194 = 'GBPNZD', $195 = 'NZDJPY', $196 = '400', $197 = '400', $198 = 't', $199 = '10', $200 = '10'
-
WITH rar_max as ( ;
Date: 2025-07-22 22:49:09 Duration: 60ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = 't', $2 = '627', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '213', $14 = '#ADBE', $15 = '#ALVG', $16 = '#AMZN', $17 = '#APPL', $18 = '#BA', $19 = '#BABA', $20 = '#BAYGn', $21 = '#BMWG', $22 = '#BNPP', $23 = '#CAT', $24 = '#CBKG', $25 = '#DAIGn', $26 = '#DIS', $27 = '#EA', $28 = '#FB', $29 = '#FDX', $30 = '#GE', $31 = '#GM', $32 = '#GOOGL', $33 = '#GS', $34 = '#INTC', $35 = '#JPM', $36 = '#KO', $37 = '#META', $38 = '#MSFT', $39 = '#NFLX', $40 = '#TSLA', $41 = '#VOWG', $42 = '#WMT', $43 = '#XOM', $44 = 'AUDCAD', $45 = 'AUDCHF', $46 = 'AUDJPY', $47 = 'AUDNZD', $48 = 'AUDUSD', $49 = 'AUS_200', $50 = 'BTCEUR', $51 = 'BTCGBP', $52 = 'BTCUSD', $53 = 'CADCHF', $54 = 'CADJPY', $55 = 'CHFJPY', $56 = 'CL_BRENT', $57 = 'DASHUSD', $58 = 'EOSUSD', $59 = 'ESP_35', $60 = 'ETHEUR', $61 = 'ETHGBP', $62 = 'ETHUSD', $63 = 'EURAUD', $64 = 'EURCAD', $65 = 'EURCHF', $66 = 'EURGBP', $67 = 'EURJPY', $68 = 'EURMXN', $69 = 'EURNOK', $70 = 'EURNZD', $71 = 'EURPLN', $72 = 'EURSEK', $73 = 'EURTRY', $74 = 'EURUSD', $75 = 'EUR_50', $76 = 'FRA_40', $77 = 'GBPAUD', $78 = 'GBPCAD', $79 = 'GBPCHF', $80 = 'GBPJPY', $81 = 'GBPNZD', $82 = 'GBPUSD', $83 = 'GBPZAR', $84 = 'GBR_100', $85 = 'HKDJPY', $86 = 'HKG_50', $87 = 'IOTAUSD', $88 = 'LTCEUR', $89 = 'LTCUSD', $90 = 'NAS100', $91 = 'NEOUSD', $92 = 'NOKJPY', $93 = 'NZDCAD', $94 = 'NZDCHF', $95 = 'NZDJPY', $96 = 'NZDUSD', $97 = 'OMGUSD', $98 = 'SPX500', $99 = 'TRXUSD', $100 = 'US30', $101 = 'USDCAD', $102 = 'USDCHF', $103 = 'USDCNH', $104 = 'USDDKK', $105 = 'USDJPY', $106 = 'USDMXN', $107 = 'USDNOK', $108 = 'USDPLN', $109 = 'USDSEK', $110 = 'USDSGD', $111 = 'USDZAR', $112 = 'USOIL', $113 = 'XAGUSD', $114 = 'XAUEUR', $115 = 'XAUUSD', $116 = 'XMRUSD', $117 = 'XPTUSD', $118 = 'XRPUSD', $119 = 'ZARJPY', $120 = 'ZECUSD', $121 = 'AUDCAD', $122 = 'AUDCHF', $123 = 'AUDJPY', $124 = 'AUDNZD', $125 = 'AUDUSD', $126 = 'CADCHF', $127 = 'CADJPY', $128 = 'CHFJPY', $129 = 'EURAUD', $130 = 'EURCAD', $131 = 'EURCHF', $132 = 'EURGBP', $133 = 'EURJPY', $134 = 'EURMXN', $135 = 'EURNOK', $136 = 'EURNZD', $137 = 'EURPLN', $138 = 'EURSEK', $139 = 'EURTRY', $140 = 'EURUSD', $141 = 'GBPAUD', $142 = 'GBPCAD', $143 = 'GBPCHF', $144 = 'GBPJPY', $145 = 'GBPNZD', $146 = 'GBPUSD', $147 = 'GBPZAR', $148 = 'HKDJPY', $149 = 'NOKJPY', $150 = 'NZDCAD', $151 = 'NZDCHF', $152 = 'NZDJPY', $153 = 'NZDUSD', $154 = 'USDCAD', $155 = 'USDCHF', $156 = 'USDCNH', $157 = 'USDDKK', $158 = 'USDJPY', $159 = 'USDMXN', $160 = 'USDNOK', $161 = 'USDPLN', $162 = 'USDSEK', $163 = 'USDSGD', $164 = 'USDZAR', $165 = 'ZARJPY', $166 = 'BTCEUR', $167 = 'BTCGBP', $168 = 'BTCUSD', $169 = 'DASHUSD', $170 = 'EOSUSD', $171 = 'ETHEUR', $172 = 'ETHGBP', $173 = 'ETHUSD', $174 = 'IOTAUSD', $175 = 'LTCEUR', $176 = 'LTCUSD', $177 = 'NEOUSD', $178 = 'OMGUSD', $179 = 'TRXUSD', $180 = 'XMRUSD', $181 = 'XRPUSD', $182 = 'ZECUSD', $183 = 'XAGUSD', $184 = 'XAUEUR', $185 = 'XAUUSD', $186 = 'XPTUSD', $187 = 'CL_BRENT', $188 = 'USOIL', $189 = '#ALVG', $190 = '#BAYGn', $191 = '#BMWG', $192 = '#BNPP', $193 = '#CBKG', $194 = '#DAIGn', $195 = '#VOWG', $196 = 'AUS_200', $197 = 'ESP_35', $198 = 'EUR_50', $199 = 'FRA_40', $200 = 'GBR_100', $201 = 'HKG_50', $202 = 'NAS100', $203 = 'SPX500', $204 = 'US30', $205 = '#ADBE', $206 = '#AMZN', $207 = '#APPL', $208 = '#BA', $209 = '#BABA', $210 = '#CAT', $211 = '#DIS', $212 = '#EA', $213 = '#FB', $214 = '#FDX', $215 = '#GE', $216 = '#GM', $217 = '#GOOGL', $218 = '#GS', $219 = '#INTC', $220 = '#JPM', $221 = '#KO', $222 = '#MSFT', $223 = '#NFLX', $224 = '#TSLA', $225 = '#WMT', $226 = '#XOM', $227 = '0', $228 = '', $229 = '400', $230 = '400', $231 = '0', $232 = '0', $233 = '0', $234 = 't', $235 = '10', $236 = '10'
-
WITH rar_max as ( ;
Date: 2025-07-22 22:50:05 Duration: 54ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = 't', $2 = '958', $3 = '3', $4 = '60', $5 = '240', $6 = '1440', $7 = '0', $8 = '', $9 = '50', $10 = 'AUDCAD', $11 = 'AUDJPY', $12 = 'AUDUSD', $13 = 'EURAUD', $14 = 'EURCHF', $15 = 'EURGBP', $16 = 'EURJPY', $17 = 'EURMXN', $18 = 'EURUSD', $19 = 'GBPJPY', $20 = 'GBPUSD', $21 = 'NZDUSD', $22 = 'USDCAD', $23 = 'USDCHF', $24 = 'USDJPY', $25 = 'USDMXN', $26 = 'BTCUSD', $27 = 'ETHUSD', $28 = 'LTCUSD', $29 = 'AAPL.US', $30 = 'AMD.US', $31 = 'AMZN.US', $32 = 'BABA.US', $33 = 'BRK.B.US', $34 = 'GOOG.US', $35 = 'INTC.US', $36 = 'META.US', $37 = 'MSFT.US', $38 = 'NFLX.US', $39 = 'NKE.US', $40 = 'NVDA.US', $41 = 'PYPL.US', $42 = 'TSLA.US', $43 = 'V.US', $44 = 'Cocoa', $45 = 'Coffee', $46 = 'NatGas', $47 = 'SpotBrent', $48 = 'XAGUSD', $49 = 'XAUUSD', $50 = 'AUS200', $51 = 'EUSTX50', $52 = 'FRA40', $53 = 'GER40', $54 = 'HK50', $55 = 'JPN225', $56 = 'NAS100', $57 = 'UK100', $58 = 'US30', $59 = 'US500', $60 = '0', $61 = '', $62 = '0', $63 = '0', $64 = '0', $65 = '400', $66 = '400', $67 = 't', $68 = '10', $69 = '10'
2 22s571ms 31,001 0ms 25ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 22 31,001 22s571ms 0ms [ User: postgres - Total duration: 59s659ms - Times executed: 31001 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 59s646ms - Times executed: 30980 ]
[ Application: [unknown] - Total duration: 12ms - Times executed: 21 ]
-
SELECT ;
Date: 2025-07-22 22:00:04 Duration: 25ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '515840233922495300'
-
SELECT ;
Date: 2025-07-22 22:00:06 Duration: 23ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '558', $3 = '515840243250333300'
-
SELECT ;
Date: 2025-07-22 22:00:05 Duration: 23ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '0', $3 = '0', $4 = 'USDCHF', $5 = 'USDCHF'
3 1s541ms 822 1ms 10ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 22 822 1s541ms 1ms [ User: postgres - Total duration: 1s243ms - Times executed: 822 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s243ms - Times executed: 822 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-07-22 22:30:04 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'PEPPERSTONE'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-07-22 22:01:02 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'BDSWISS'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-07-22 22:30:50 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'MILLENNIUMPF'
4 977ms 135 4ms 29ms 7ms WITH last_candle AS ( ;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 22 135 977ms 7ms [ User: postgres - Total duration: 51s451ms - Times executed: 135 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 51s451ms - Times executed: 135 ]
-
WITH last_candle AS ( ;
Date: 2025-07-22 22:00:05 Duration: 29ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '958', $2 = '958'
-
WITH last_candle AS ( ;
Date: 2025-07-22 22:00:04 Duration: 28ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '958', $2 = '958'
-
WITH last_candle AS ( ;
Date: 2025-07-22 22:16:14 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '558'
5 689ms 52 0ms 21ms 13ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 22 52 689ms 13ms [ User: postgres - Total duration: 0ms - Times executed: 52 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 0ms - Times executed: 52 ]
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-07-22 22:00:44 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 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: 2025-07-22 22:07:34 Duration: 20ms 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'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-07-22 22:07:37 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
6 660ms 29,370 0ms 12ms 0ms select 1;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 22 29,370 660ms 0ms [ User: postgres - Total duration: 132ms - Times executed: 29370 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 132ms - Times executed: 29264 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 106 ]
-
select 1;
Date: 2025-07-22 22:00:06 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
select 1;
Date: 2025-07-22 22:00:05 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
select 1;
Date: 2025-07-22 22:49:06 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
7 578ms 24 0ms 48ms 24ms with wh_patitioned as ( ;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 22 24 578ms 24ms [ User: postgres - Total duration: 1s946ms - Times executed: 24 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s946ms - Times executed: 24 ]
-
with wh_patitioned as ( ;
Date: 2025-07-22 22:10:02 Duration: 48ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
-
with wh_patitioned as ( ;
Date: 2025-07-22 22:00:02 Duration: 47ms 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: 2025-07-22 22:15:03 Duration: 40ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
8 543ms 6,601 0ms 0ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 22 6,601 543ms 0ms [ User: postgres - Total duration: 6s726ms - Times executed: 6601 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 6s726ms - Times executed: 6601 ]
-
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: 2025-07-22 22:00:09 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-07-22 22:45:00', $2 = '6317.62', $3 = '6320.37', $4 = '6311.62', $5 = '6311.62', $6 = '442', $7 = '515840238283769300', $8 = '0', $9 = '2025-07-22 22:00:09.761', $10 = '2025-07-22 22:00:09.717', $11 = '6317.62', $12 = '6320.37', $13 = '6311.62', $14 = '6311.62', $15 = '442', $16 = '0', $17 = '2025-07-22 22:00:09.761', $18 = '2025-07-22 22:00:09.717'
-
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: 2025-07-22 22:00:44 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-07-22 22:15:00', $2 = '23083.7', $3 = '23092.3', $4 = '23077', $5 = '23086.9', $6 = '4006', $7 = '515840245923121300', $8 = '0', $9 = '2025-07-22 22:00:44.84', $10 = '2025-07-22 22:00:44.767', $11 = '23083.7', $12 = '23092.3', $13 = '23077', $14 = '23086.9', $15 = '4006', $16 = '0', $17 = '2025-07-22 22:00:44.84', $18 = '2025-07-22 22:00:44.767'
-
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: 2025-07-22 22:00:44 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-07-22 22:45:00', $2 = '87.922', $3 = '87.967', $4 = '87.922', $5 = '87.947', $6 = '807', $7 = '515840245884987300', $8 = '0', $9 = '2025-07-22 22:00:44.84', $10 = '2025-07-22 22:00:44.767', $11 = '87.922', $12 = '87.967', $13 = '87.922', $14 = '87.947', $15 = '807', $16 = '0', $17 = '2025-07-22 22:00:44.84', $18 = '2025-07-22 22:00:44.767'
9 484ms 16 28ms 44ms 30ms with sym_info as ( ;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 22 16 484ms 30ms [ User: postgres - Total duration: 29s537ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 29s537ms - Times executed: 16 ]
-
with sym_info as ( ;
Date: 2025-07-22 22:21:50 Duration: 44ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '627', $2 = 'Forex', $3 = 'Forex', $4 = '627', $5 = 'Forex', $6 = '627', $7 = '627', $8 = 'Forex', $9 = '627'
-
with sym_info as ( ;
Date: 2025-07-22 22:21:44 Duration: 40ms 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: 2025-07-22 22:52:02 Duration: 28ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'
10 283ms 3,626 0ms 1ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 22 3,626 283ms 0ms [ User: postgres - Total duration: 2s118ms - Times executed: 3626 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s118ms - Times executed: 3626 ]
-
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: 2025-07-22 22:30:56 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-07-22 23:00:00', $2 = '24.6159', $3 = '24.6162', $4 = '24.6127', $5 = '24.6131', $6 = '926', $7 = '515840243923019300', $8 = '0', $9 = '2025-07-22 22:30:56.659', $10 = '2025-07-22 22:30:56.658', $11 = '24.6159', $12 = '24.6162', $13 = '24.6127', $14 = '24.6131', $15 = '926', $16 = '0', $17 = '2025-07-22 22:30:56.659', $18 = '2025-07-22 22:30:56.658'
-
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: 2025-07-22 22:30:51 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-07-22 23:00:00', $2 = '2.06481', $3 = '2.06492', $4 = '2.0642', $5 = '2.06465', $6 = '1890', $7 = '515840216972953300', $8 = '0', $9 = '2025-07-22 22:30:51.852', $10 = '2025-07-22 22:30:51.851', $11 = '2.06481', $12 = '2.06492', $13 = '2.0642', $14 = '2.06465', $15 = '1890', $16 = '0', $17 = '2025-07-22 22:30:51.852', $18 = '2025-07-22 22:30:51.851'
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-07-22 22:30:05 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-07-22 23:00:00', $2 = '1.35309', $3 = '1.35319', $4 = '1.35257', $5 = '1.35297', $6 = '1274', $7 = '515840243868141300', $8 = '0', $9 = '2025-07-22 22:30:05.641', $10 = '2025-07-22 22:30:05.64', $11 = '1.35309', $12 = '1.35319', $13 = '1.35257', $14 = '1.35297', $15 = '1274', $16 = '0', $17 = '2025-07-22 22:30:05.641', $18 = '2025-07-22 22:30:05.64'
11 194ms 2,303 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 #11
Day Hour Count Duration Avg duration 22 2,303 194ms 0ms [ User: postgres - Total duration: 1s267ms - Times executed: 2303 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s267ms - Times executed: 2303 ]
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-07-22 22:00:09 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-07-22 22:00:00', $2 = '5.70495', $3 = '5.70845', $4 = '5.70275', $5 = '5.70655', $6 = '1848', $7 = '515840243969984300', $8 = '0', $9 = '2025-07-22 22:00:09.81', $10 = '2025-07-22 22:00:09.809', $11 = '5.70495', $12 = '5.70845', $13 = '5.70275', $14 = '5.70655', $15 = '1848', $16 = '0', $17 = '2025-07-22 22:00:09.81', $18 = '2025-07-22 22:00:09.809'
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-07-22 22:00:50 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-07-22 22:00:00', $2 = '1.95822', $3 = '1.95858', $4 = '1.95762', $5 = '1.95775', $6 = '4716', $7 = '515840247884031300', $8 = '0', $9 = '2025-07-22 22:00:50.25', $10 = '2025-07-22 22:00:50.129', $11 = '1.95822', $12 = '1.95858', $13 = '1.95762', $14 = '1.95775', $15 = '4716', $16 = '0', $17 = '2025-07-22 22:00:50.25', $18 = '2025-07-22 22:00:50.129'
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-07-22 22:00:43 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-07-22 22:00:00', $2 = '0.65494', $3 = '0.65534', $4 = '0.65482', $5 = '0.65522', $6 = '1416', $7 = '515840247873079300', $8 = '0', $9 = '2025-07-22 22:00:43.743', $10 = '2025-07-22 22:00:43.672', $11 = '0.65494', $12 = '0.65534', $13 = '0.65482', $14 = '0.65522', $15 = '1416', $16 = '0', $17 = '2025-07-22 22:00:43.743', $18 = '2025-07-22 22:00:43.672'
12 80ms 91 0ms 1ms 0ms SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 22 91 80ms 0ms [ User: postgres - Total duration: 572ms - Times executed: 91 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 536ms - Times executed: 86 ]
[ Application: [unknown] - Total duration: 35ms - Times executed: 5 ]
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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: 2025-07-22 22:05:52 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.42 parameters: $1 = '689', $2 = 'WTI', $3 = '689'
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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: 2025-07-22 22:05:33 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '558', $2 = 'USDJPY', $3 = '558'
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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: 2025-07-22 22:46:52 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.42 parameters: $1 = '689', $2 = 'WTI', $3 = '689'
13 54ms 13 3ms 6ms 4ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 22 13 54ms 4ms [ User: postgres - Total duration: 1s299ms - Times executed: 13 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s299ms - Times executed: 13 ]
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-07-22 22:30:00 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '958', $2 = '958'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-07-22 22:29:59 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '958', $2 = '958'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-07-22 22:57:19 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '538', $2 = '538'
14 49ms 1 49ms 49ms 49ms with maxwhid as ( ;Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 22 1 49ms 49ms [ User: postgres - Total duration: 56ms - Times executed: 1 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 56ms - Times executed: 1 ]
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with maxwhid as ( ;
Date: 2025-07-22 22:12:44 Duration: 49ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.197 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'
15 30ms 6 5ms 5ms 5ms 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 #15
Day Hour Count Duration Avg duration 22 6 30ms 5ms [ User: postgres - Total duration: 45s359ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 45s359ms - 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: 2025-07-22 22:30:02 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: 2025-07-22 22:50:02 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: 2025-07-22 22:40:02 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
16 25ms 323 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 #16
Day Hour Count Duration Avg duration 22 323 25ms 0ms [ User: postgres - Total duration: 27ms - Times executed: 323 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 27ms - Times executed: 323 ]
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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: 2025-07-22 22:12:20 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '606507101139896301'
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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: 2025-07-22 22:50:49 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '606507531092550301'
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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: 2025-07-22 22:26:34 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '606507455581023301'
17 20ms 4,491 0ms 0ms 0ms SET extra_float_digits = 3;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 22 4,491 20ms 0ms [ User: postgres - Total duration: 56ms - Times executed: 4491 ]
[ Application: [unknown] - Total duration: 56ms - Times executed: 4491 ]
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SET extra_float_digits = 3;
Date: 2025-07-22 22:04:17 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
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SET extra_float_digits = 3;
Date: 2025-07-22 22:47:43 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
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SET extra_float_digits = 3;
Date: 2025-07-22 22:26:50 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
18 18ms 4,465 0ms 1ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 22 4,465 18ms 0ms [ User: postgres - Total duration: 63ms - Times executed: 4465 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 63ms - Times executed: 4465 ]
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-07-22 22:28:03 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-07-22 22:10:18 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: 2025-07-22 22:09:30 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
19 17ms 482 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 #19
Day Hour Count Duration Avg duration 22 482 17ms 0ms [ User: postgres - Total duration: 15ms - Times executed: 482 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 15ms - Times executed: 482 ]
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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: 2025-07-22 22:32:41 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.239 parameters: $1 = '500991628284134200'
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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: 2025-07-22 22:17:42 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42 parameters: $1 = '515840243907364300'
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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: 2025-07-22 22:32:44 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '515840248633460300'
20 17ms 112 0ms 0ms 0ms SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T30 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 22 112 17ms 0ms [ User: postgres - Total duration: 528ms - Times executed: 112 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 528ms - Times executed: 112 ]
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T30 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2025-07-22 22:33:13 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '515840243257861300'
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T30 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2025-07-22 22:33:16 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '515840248182301300'
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T30 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2025-07-22 22:32:32 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42 parameters: $1 = '515840243892127300'
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Events
Log levels
Key values
- 360,790 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 0 ERROR entries
- 0 WARNING entries
Errors per 5 minutes
NO DATASET
Most Frequent Errors/Events
Key values
- 0 Max number of times the same event was reported
- 0 Total events found
Rank Times reported Error NO DATASET