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Global information
- Generated on Wed Sep 17 12:00:38 2025
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2025-09-17_130000.log, ..., /home/postgres/pg_data/data/pg_log/postgresql-2025-09-17_133750.log
- Parsed 3,980,828 log entries in 1m37s
- Log start from 2025-09-17 13:00:00 to 2025-09-17 14:00:00
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Overview
Global Stats
- 233 Number of unique normalized queries
- 202,511 Number of queries
- 2h3m54s Total query duration
- 2025-09-17 13:00:00 First query
- 2025-09-17 13:59:59 Last query
- 2,695 queries/s at 2025-09-17 13:15:03 Query peak
- 2h3m54s Total query duration
- 31s852ms Prepare/parse total duration
- 2m Bind total duration
- 2h1m21s Execute total duration
- 2 Number of events
- 1 Number of unique normalized events
- 2 Max number of times the same event was reported
- 0 Number of cancellation
- 41 Total number of automatic vacuums
- 56 Total number of automatic analyzes
- 539 Number temporary file
- 127.00 MiB Max size of temporary file
- 8.35 MiB Average size of temporary file
- 11,427 Total number of sessions
- 12 sessions at 2025-09-17 13:17:49 Session peak
- 3d17h52m45s Total duration of sessions
- 28s315ms Average duration of sessions
- 17 Average queries per session
- 650ms Average queries duration per session
- 27s665ms Average idle time per session
- 11,425 Total number of connections
- 96 connections/s at 2025-09-17 13:17:20 Connection peak
- 2 Total number of databases
SQL Traffic
Key values
- 2,695 queries/s Query Peak
- 2025-09-17 13:15:03 Date
SELECT Traffic
Key values
- 2,600 queries/s Query Peak
- 2025-09-17 13:15:03 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 179 queries/s Query Peak
- 2025-09-17 13:30:56 Date
Queries duration
Key values
- 2h3m54s 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) Sep 17 13 202,511 0ms 37s651ms 35ms 4m32s 5m58s 6m57s 14 0 0ms 0ms 0ms 0ms 0ms 0ms Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Sep 17 13 136,788 26 2ms 5s664ms 17s268ms 29s572ms 14 0 0 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Sep 17 13 31,463 2,426 16 96 1ms 911ms 1s625ms 2s516ms 14 0 0 0 0 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Sep 17 13 72,609 178,144 2.45 40.01% 14 1 0 0.00 100.00% Day Hour Count Average / Second Sep 17 13 11,425 3.17/s 14 0 0.00/s Day Hour Count Average Duration Average idle time Sep 17 13 11,427 28s315ms 27s678ms 14 0 0ms 0ms -
Connections
Established Connections
Key values
- 96 connections Connection Peak
- 2025-09-17 13:17:20 Date
Connections per database
Key values
- acaweb_fx Main Database
- 11,425 connections Total
Connections per user
Key values
- postgres Main User
- 11,425 connections Total
Connections per host
Key values
- 192.168.1.15 Main host with 5559 connections
- 11,425 Total connections
Host Count 127.0.0.1 114 182.165.1.54 2 192.168.0.114 2 192.168.0.216 102 192.168.0.74 3,121 192.168.1.145 110 192.168.1.15 5,559 192.168.1.20 144 192.168.1.231 20 192.168.1.239 2 192.168.1.90 76 192.168.2.126 62 192.168.2.182 12 192.168.2.205 12 192.168.2.82 48 192.168.3.199 36 192.168.4.102 1 192.168.4.142 1,267 192.168.4.150 10 192.168.4.164 4 192.168.4.238 16 192.168.4.33 101 192.168.4.98 330 [local] 274 -
Sessions
Simultaneous sessions
Key values
- 12 sessions Session Peak
- 2025-09-17 13:17:49 Date
Histogram of session times
Key values
- 10,158 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 11,427 sessions Total
Sessions per user
Key values
- postgres Main User
- 11,427 sessions Total
Sessions per host
Key values
- 192.168.1.15 Main Host
- 11,427 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 114 10s815ms 94ms 182.165.1.54 2 3h38m37s 1h49m18s 192.168.0.114 2 10m 5m 192.168.0.216 102 2m3s 1s214ms 192.168.0.74 3,121 9h48m49s 11s319ms 192.168.1.145 111 10h30m58s 5m41s 192.168.1.15 5,559 15h58m5s 10s341ms 192.168.1.20 145 19h21m9s 8m 192.168.1.231 20 9h53m 29m39s 192.168.1.239 2 25ms 12ms 192.168.1.90 76 36s236ms 476ms 192.168.2.126 62 6s530ms 105ms 192.168.2.182 12 1s242ms 103ms 192.168.2.205 12 1s127ms 93ms 192.168.2.82 48 3s828ms 79ms 192.168.3.199 36 1s218ms 33ms 192.168.4.102 1 160ms 160ms 192.168.4.142 1,267 10m24s 493ms 192.168.4.150 10 20h29s 2h2s 192.168.4.164 4 3m45s 56s485ms 192.168.4.238 16 21s796ms 1s362ms 192.168.4.33 101 10m3s 5s975ms 192.168.4.98 330 14s394ms 43ms [local] 274 3m38s 798ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 10,273 buffers Checkpoint Peak
- 2025-09-17 13:05:52 Date
- 209.860 seconds Highest write time
- 0.027 seconds Sync time
Checkpoints Wal files
Key values
- 5 files Wal files usage Peak
- 2025-09-17 13:05:52 Date
Checkpoints distance
Key values
- 158.63 Mo Distance Peak
- 2025-09-17 13:05:52 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Sep 17 13 48,321 1,910.218s 0.099s 1,910.683s 14 0 0s 0s 0s Day Hour Added Removed Recycled Synced files Longest sync Average sync Sep 17 13 0 0 25 2,204 0.006s 0s 14 0 0 0 0 0s 0s Day Hour Count Avg time (sec) Sep 17 13 0 0s 14 0 0s Day Hour Mean distance Mean estimate Sep 17 13 34,458.33 kB 62,243.25 kB 14 0.00 kB 0.00 kB -
Temporary Files
Size of temporary files
Key values
- 175.77 MiB Temp Files size Peak
- 2025-09-17 13:10:07 Date
Number of temporary files
Key values
- 30 per second Temp Files Peak
- 2025-09-17 13:32:11 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Sep 17 13 539 4.39 GiB 8.35 MiB 14 0 0 0 Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 85 378.17 MiB 3.22 MiB 9.44 MiB 4.45 MiB with rar_max as ( ;-
WITH rar_max as ( ;
Date: 2025-09-17 13:40:59 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver
2 40 1.69 GiB 7.33 MiB 127.00 MiB 43.31 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), 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: 2025-09-17 13:00:09 Duration: 6s851ms 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: 2025-09-17 13:30:07 Duration: 5s397ms 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: 2025-09-17 13:50:08 Duration: 5s397ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
3 16 493.58 MiB 30.84 MiB 30.85 MiB 30.85 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: 2025-09-17 13:11:13 Duration: 1s944ms 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: 2025-09-17 13:01:13 Duration: 1s792ms 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: 2025-09-17 13:16:13 Duration: 1s449ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
4 16 968.48 MiB 60.52 MiB 60.54 MiB 60.53 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: 2025-09-17 13:01:17 Duration: 3s634ms 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: 2025-09-17 13:11:17 Duration: 3s551ms 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: 2025-09-17 13:26:17 Duration: 3s529ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
5 8 594.74 MiB 74.34 MiB 74.35 MiB 74.34 MiB select updateresultsmaterializedview ();-
select updateresultsmaterializedview ();
Date: 2025-09-17 13:17:28 Duration: 3s921ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-09-17 13:02:25 Duration: 3s306ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-09-17 13:47:21 Duration: 3s274ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
6 4 332.24 MiB 83.03 MiB 83.11 MiB 83.06 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2025-09-17 13:17:24 Duration: 21s786ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-09-17 13:02:21 Duration: 19s235ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-09-17 13:47:18 Duration: 15s246ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
Queries generating the largest temporary files
Rank Size Query 1 127.00 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: 2025-09-17 13:50:04 ]
2 112.62 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: 2025-09-17 13:40:05 ]
3 107.46 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: 2025-09-17 13:20:04 ]
4 102.76 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: 2025-09-17 13:40:05 ]
5 89.80 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: 2025-09-17 13:10:04 ]
6 86.46 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: 2025-09-17 13:00:06 ]
7 83.11 MiB select updateageforrelevantresults ();[ Date: 2025-09-17 13:02:07 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
8 83.07 MiB select updateageforrelevantresults ();[ Date: 2025-09-17 13:32:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
9 83.03 MiB select updateageforrelevantresults ();[ Date: 2025-09-17 13:17:08 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
10 83.03 MiB select updateageforrelevantresults ();[ Date: 2025-09-17 13:47:06 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
11 82.32 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: 2025-09-17 13:20:07 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
12 81.08 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: 2025-09-17 13:30:07 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
13 80.76 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: 2025-09-17 13:30:05 ]
14 78.15 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: 2025-09-17 13:50:05 ]
15 77.25 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: 2025-09-17 13:00:06 ]
16 74.35 MiB select updateresultsmaterializedview ();[ Date: 2025-09-17 13:17:25 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
17 74.35 MiB select updateresultsmaterializedview ();[ Date: 2025-09-17 13:32:17 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
18 74.35 MiB select updateresultsmaterializedview ();[ Date: 2025-09-17 13:47:18 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
19 74.34 MiB select updateresultsmaterializedview ();[ Date: 2025-09-17 13:02:22 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
20 74.34 MiB select updateresultsmaterializedview ();[ Date: 2025-09-17 13:50:33 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
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Vacuums
Vacuums / Analyzes Distribution
Key values
- 0 sec Highest CPU-cost vacuum
Table
Database - Date
- 0 sec Highest CPU-cost analyze
Table
Database - Date
Analyzes per table
Key values
- public.solr_relevance_old (16) Main table analyzed (database acaweb_fx)
- 56 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.public.relevance_autochartist_results 4 acaweb_fx.public.latest_t15_candle_view 3 acaweb_fx.pg_catalog.pg_type 3 acaweb_fx.pg_catalog.pg_index 1 acaweb_fx.public.autochartist_symbolupdates 1 socialmedia.public.processes 1 acaweb_fx.pg_catalog.pg_depend 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.relevance_consecutivecandles_results 1 acaweb_fx.public.symbollatestupdatetime 1 Total 56 Vacuums per table
Key values
- public.solr_relevance_old (16) Main table vacuumed on database acaweb_fx
- 41 vacuums Total
Index Buffer usage Skipped WAL usage Table Vacuums scans hits misses dirtied pins frozen records full page bytes acaweb_fx.public.solr_relevance_old 16 16 12,609 0 51 0 0 8,711 16 1,621,869 acaweb_fx.public.datafeeds_latestrun 5 0 602 0 13 0 0 73 12 80,871 acaweb_fx.public.relevance_fibonacci_results 4 4 4,988 0 175 2 209 767 325 995,194 acaweb_fx.pg_toast.pg_toast_2619 2 2 295 0 58 0 0 207 55 212,196 acaweb_fx.pg_catalog.pg_attribute 2 2 1,539 0 351 0 134 741 279 1,690,821 acaweb_fx.public.latest_t15_candle_view 2 2 184 0 2 0 0 12 2 18,068 acaweb_fx.public.relevance_keylevels_results 2 2 8,239 0 402 2 146 2,350 918 2,387,781 acaweb_fx.pg_catalog.pg_class 2 2 940 0 90 0 0 281 85 438,023 acaweb_fx.public.relevance_autochartist_results 2 2 6,981 0 239 2 494 1,391 959 2,104,029 acaweb_fx.pg_catalog.pg_index 1 1 89 0 11 0 0 28 10 75,242 acaweb_fx.pg_catalog.pg_type 1 1 133 0 24 0 0 53 18 99,654 acaweb_fx.public.autochartist_symbolupdates 1 1 28,909 0 3,638 4 36,522 10,822 904 967,259 acaweb_fx.pg_catalog.pg_statistic 1 1 971 0 209 0 581 431 182 703,060 Total 41 36 66,479 47,148 5,263 10 38,086 25,867 3,765 11,394,067 Tuples removed per table
Key values
- public.solr_relevance_old (47648) Main table with removed tuples on database acaweb_fx
- 61596 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 16 16 47,648 87,368 0 0 3,083 acaweb_fx.public.autochartist_symbolupdates 1 1 6,524 62,232 49 0 40,691 acaweb_fx.public.relevance_keylevels_results 2 2 2,358 23,572 0 0 558 acaweb_fx.pg_catalog.pg_attribute 2 2 2,343 19,228 252 0 480 acaweb_fx.pg_catalog.pg_statistic 1 1 622 3,717 0 0 1,194 acaweb_fx.public.relevance_autochartist_results 2 2 566 15,892 0 0 760 acaweb_fx.public.relevance_fibonacci_results 4 4 520 6,004 79 0 408 acaweb_fx.public.datafeeds_latestrun 5 0 280 82 12 0 80 acaweb_fx.pg_catalog.pg_class 2 2 271 3,244 54 0 300 acaweb_fx.pg_catalog.pg_type 1 1 189 1,338 0 0 38 acaweb_fx.pg_toast.pg_toast_2619 2 2 136 346 0 0 106 acaweb_fx.public.latest_t15_candle_view 2 2 115 28 0 0 2 acaweb_fx.pg_catalog.pg_index 1 1 24 813 0 0 22 Total 41 36 61,596 223,864 446 0 47,722 Pages removed per table
Key values
- unknown (0) Main table with removed pages on database unknown
- 0 pages Total removed
Pages removed per tables
NO DATASET
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_catalog.pg_index 1 1 24 0 acaweb_fx.pg_toast.pg_toast_2619 2 2 136 0 acaweb_fx.pg_catalog.pg_type 1 1 189 0 acaweb_fx.public.autochartist_symbolupdates 1 1 6524 0 acaweb_fx.public.datafeeds_latestrun 5 0 280 0 acaweb_fx.pg_catalog.pg_attribute 2 2 2343 0 acaweb_fx.pg_catalog.pg_statistic 1 1 622 0 acaweb_fx.public.latest_t15_candle_view 2 2 115 0 acaweb_fx.public.relevance_keylevels_results 2 2 2358 0 acaweb_fx.pg_catalog.pg_class 2 2 271 0 acaweb_fx.public.solr_relevance_old 16 16 47648 0 acaweb_fx.public.relevance_autochartist_results 2 2 566 0 acaweb_fx.public.relevance_fibonacci_results 4 4 520 0 Total 41 36 61,596 0 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Sep 17 13 41 56 14 0 0 - 0 sec Highest CPU-cost vacuum
-
Locks
Locks by types
Key values
- unknown Main Lock Type
- 0 locks Total
Most frequent waiting queries (N)
Rank Count Total time Min time Max time Avg duration Query NO DATASET
Queries that waited the most
Rank Wait time Query NO DATASET
-
Queries
Queries by type
Key values
- 136,788 Total read queries
- 44,700 Total write queries
Queries by database
Key values
- acaweb_fx Main database
- 193,942 Requests
- 2h1m11s (acaweb_fx)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 193,942 2h1m11s copy from 96 6s503ms copy to 26 9s734ms cte 9,993 1h55m17s ddl 16 497ms delete 16 24ms insert 23,527 21s603ms others 21,023 8s945ms select 136,266 4m43s tcl 664 190ms update 2,315 22s865ms socialmedia Total 8,569 10s709ms insert 7,936 9s181ms select 522 1s303ms update 111 224ms Queries by user
Key values
- postgres Main user
- 202,511 Requests
User Request type Count Duration postgres Total 202,511 2h1m21s copy from 96 6s503ms copy to 26 9s734ms cte 9,993 1h55m17s ddl 16 497ms delete 16 24ms insert 31,463 30s785ms others 21,023 8s945ms select 136,788 4m44s tcl 664 190ms update 2,426 23s89ms Duration by user
Key values
- 2h1m21s (postgres) Main time consuming user
User Request type Count Duration postgres Total 202,511 2h1m21s copy from 96 6s503ms copy to 26 9s734ms cte 9,993 1h55m17s ddl 16 497ms delete 16 24ms insert 31,463 30s785ms others 21,023 8s945ms select 136,788 4m44s tcl 664 190ms update 2,426 23s89ms Queries by host
Key values
- 192.168.1.15 Main host
- 61,264 Requests
- 36m43s (192.168.1.15)
- Main time consuming host
Host Request type Count Duration 127.0.0.1 Total 12,730 51s421ms copy to 26 9s734ms cte 25 265ms insert 10,379 11s134ms select 526 29s290ms update 1,774 996ms 182.165.1.42 Total 80 172ms select 80 172ms 182.165.1.54 Total 769 104ms others 4 0ms select 765 104ms 192.168.0.114 Total 10 86ms others 2 0ms select 4 86ms tcl 4 0ms 192.168.0.216 Total 408 350ms others 204 21ms select 196 235ms update 8 93ms 192.168.0.23 Total 42 1ms select 42 1ms 192.168.0.239 Total 495 545ms select 495 545ms 192.168.0.42 Total 1,443 639ms insert 494 43ms select 949 595ms 192.168.0.74 Total 37,731 33m29s cte 3,798 33m13s others 6,242 65ms select 27,691 16s361ms 192.168.1.135 Total 138 464ms cte 6 302ms select 132 161ms 192.168.1.145 Total 24,323 22m50s cte 677 22m29s others 220 2ms select 23,426 21s325ms 192.168.1.15 Total 61,264 36m43s cte 4,140 36m10s others 11,118 121ms select 46,006 33s644ms 192.168.1.20 Total 28,710 22m11s cte 647 21m46s others 288 3ms select 27,775 25s425ms 192.168.1.201 Total 1,543 1s509ms select 1,543 1s509ms 192.168.1.210 Total 20 0ms select 20 0ms 192.168.1.23 Total 1,747 1s413ms select 1,747 1s413ms 192.168.1.231 Total 45 15ms others 40 0ms select 5 15ms 192.168.1.239 Total 8 4ms others 4 0ms select 4 4ms 192.168.1.90 Total 180 33s748ms cte 6 33s577ms others 56 0ms select 118 170ms 192.168.1.93 Total 2 0ms select 2 0ms 192.168.2.126 Total 80 62ms others 18 0ms select 62 62ms 192.168.2.182 Total 48 274ms others 24 2ms select 12 11ms update 12 260ms 192.168.2.205 Total 137 98ms insert 89 7ms others 24 2ms select 20 21ms update 4 66ms 192.168.2.82 Total 1,070 1s938ms insert 676 1s134ms others 96 10ms select 177 103ms update 121 689ms 192.168.3.199 Total 144 206ms others 72 7ms select 60 61ms update 12 137ms 192.168.4.102 Total 3 37ms cte 1 37ms others 2 0ms 192.168.4.142 Total 15,702 10s370ms insert 11,889 9s282ms others 2,534 26ms select 1,279 1s62ms 192.168.4.150 Total 22 1s64ms others 21 0ms select 1 1s64ms 192.168.4.164 Total 3,666 2s912ms cte 581 2s344ms others 12 0ms select 3,073 568ms 192.168.4.238 Total 48 20s598ms cte 16 20s597ms others 32 0ms 192.168.4.33 Total 8,509 9s728ms insert 7,936 9s181ms select 462 322ms update 111 224ms 192.168.4.98 Total 996 9s160ms others 6 8s338ms select 6 29ms tcl 660 190ms update 324 602ms 3.216.59.87 Total 60 981ms select 60 981ms [local] Total 338 3m37s copy from 96 6s503ms cte 96 41s194ms ddl 16 497ms delete 16 24ms others 4 341ms select 50 2m29s update 60 20s18ms Queries by application
Key values
- PostgreSQL JDBC Driver Main application
- 167,553 Requests
- 1h55m55s (PostgreSQL JDBC Driver)
- Main time consuming application
Application Request type Count Duration PostgreSQL JDBC Driver Total 167,553 1h55m55s cte 9,866 1h54m2s insert 12,383 9s326ms others 10,283 118ms select 135,021 1m43s [unknown] Total 34,446 1m37s cte 6 33s577ms insert 19,080 21s459ms others 10,736 8s485ms select 1,605 30s292ms tcl 664 190ms update 2,355 3s46ms pgAdmin 4 - DB:socialmedia Total 60 981ms select 60 981ms psql Total 452 3m48s copy from 96 6s503ms copy to 26 9s734ms cte 121 41s460ms ddl 16 497ms delete 16 24ms others 4 341ms select 102 2m29s update 71 20s42ms Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2025-09-17 13:13:38 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 137,081 0-1ms duration
Slowest individual queries
Rank Duration Query 1 37s651ms 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: 2025-09-17 13:00:13 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
2 37s281ms 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: 2025-09-17 13:15:27 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
3 36s859ms 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: 2025-09-17 13:05:52 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
4 36s795ms 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: 2025-09-17 13:53:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
5 36s575ms 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: 2025-09-17 13:14:56 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
6 36s426ms 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: 2025-09-17 13:57:43 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
7 36s410ms 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: 2025-09-17 13:10:23 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
8 36s271ms 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: 2025-09-17 13:50:57 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
9 36s257ms 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: 2025-09-17 13:10:41 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
10 36s129ms 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: 2025-09-17 13:50:50 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
11 36s111ms 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: 2025-09-17 13:19:21 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
12 36s70ms 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: 2025-09-17 13:57:59 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
13 35s761ms 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: 2025-09-17 13:53:25 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
14 35s250ms 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: 2025-09-17 13:04:37 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
15 25s527ms 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 ('700' = 0 OR kr.patternlengthbars <= '700') 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: 2025-09-17 13:26:01 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
16 23s605ms 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 ('700' = 0 OR kr.patternlengthbars <= '700') 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: 2025-09-17 13:12:22 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
17 23s516ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-09-17 13:06:22 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
18 22s32ms 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 ('700' = 0 OR kr.patternlengthbars <= '700') 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: 2025-09-17 13:25:53 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
19 21s823ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-09-17 13:11:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
20 21s786ms select updateageforrelevantresults ();[ Date: 2025-09-17 13:17:24 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
Time consuming queries
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 54m19s 354 134ms 37s651ms 9s206ms 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 Sep 17 13 354 54m19s 9s206ms [ User: postgres - Total duration: 54m19s - Times executed: 354 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 54m19s - Times executed: 354 ]
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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: 2025-09-17 13:00:13 Duration: 37s651ms 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: 2025-09-17 13:15:27 Duration: 37s281ms 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_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: 2025-09-17 13:05:52 Duration: 36s859ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
2 42m9s 355 347ms 23s516ms 7s126ms 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 Sep 17 13 355 42m9s 7s126ms [ User: postgres - Total duration: 42m9s - Times executed: 355 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 42m9s - Times executed: 355 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-09-17 13:06:22 Duration: 23s516ms 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 = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-09-17 13:11:10 Duration: 21s823ms 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 ('700' = 0 OR ar.patternlengthbars <= '700') 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: 2025-09-17 13:17:04 Duration: 20s931ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
3 15m2s 289 571ms 9s181ms 3s121ms 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 Sep 17 13 289 15m2s 3s121ms [ User: postgres - Total duration: 15m2s - Times executed: 289 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 15m2s - Times executed: 289 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR fr.pattern in ('')) AND ('0' = 0 OR fr.patternlengthbars <= '0') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-09-17 13:06:32 Duration: 9s181ms 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 ('700' = 0 OR fr.patternlengthbars <= '700') 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: 2025-09-17 13:17:08 Duration: 8s958ms 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 ('700' = 0 OR fr.patternlengthbars <= '700') 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: 2025-09-17 13:02:02 Duration: 8s699ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
4 1m11s 4 14s863ms 21s786ms 17s782ms select updateageforrelevantresults ();Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Sep 17 13 4 1m11s 17s782ms [ User: postgres - Total duration: 1m11s - Times executed: 4 ]
[ Application: psql - Total duration: 1m11s - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-09-17 13:17:24 Duration: 21s786ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-09-17 13:02:21 Duration: 19s235ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-09-17 13:47:18 Duration: 15s246ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
5 1m6s 187 33ms 1s173ms 357ms with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Sep 17 13 187 1m6s 357ms [ User: postgres - Total duration: 1m6s - Times executed: 187 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m6s - Times executed: 187 ]
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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 ('700' = 0 OR ccr.patternlengthbars <= '700') ), 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: 2025-09-17 13:25:54 Duration: 1s173ms 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 ('700' = 0 OR ccr.patternlengthbars <= '700') ), 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: 2025-09-17 13:17:27 Duration: 1s16ms 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 ('700' = 0 OR ccr.patternlengthbars <= '700') ), 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: 2025-09-17 13:26:02 Duration: 1s12ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
6 55s775ms 38,563 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 #6
Day Hour Count Duration Avg duration Sep 17 13 38,563 55s775ms 1ms [ User: postgres - Total duration: 55s775ms - Times executed: 38563 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 55s775ms - Times executed: 38563 ]
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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 = '515840249435063300';
Date: 2025-09-17 13:00:04 Duration: 21ms 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 = '958' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '958' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840248627808300';
Date: 2025-09-17 13:15:49 Duration: 19ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 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 = '958' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '958' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840216981120300';
Date: 2025-09-17 13:06:00 Duration: 18ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
7 47s352ms 34 19ms 16s668ms 1s392ms select fixcandlegaps (?, false);Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Sep 17 13 34 47s352ms 1s392ms [ User: postgres - Total duration: 47s352ms - Times executed: 34 ]
[ Application: psql - Total duration: 47s352ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-09-17 13:06:49 Duration: 16s668ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-09-17 13:06:12 Duration: 5s543ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('PEPPERSTONE', false);
Date: 2025-09-17 13:06:25 Duration: 4s882ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
8 39s209ms 114 91ms 1s15ms 343ms with last_candle as ( select acs.symbolid as symbolid, acs.latestpricedatetime as latest_candle_time, bsl.brokerid as broker_id, coalesce(bim.code, s.symbol) as symbol, bim.code as symbol_mapping, s.exchange as exchange, s.timegranularity as timegranularity from autochartist_symbolupdates acs inner join brokersymbollist bsl on acs.symbolid = bsl.symbolid inner join symbols s on acs.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bsl.brokerid = ? and s.deleted = ? and s.nonliquid = ? and acs.latestpricedatetime is not null ) select * from ( select lc.broker_id as brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / ?) + ? as sast_hh, mod(cast(psp.fromtime as int), ?) as sast_mm, current_timestamp as datetime, (powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice as closingprice, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / ?.?) as low_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / ?.?) as high_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / ?.?) as low_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / ?.?) as high_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / ?.?) as low_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / ?.?) as high_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / ?.?) as low_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / ?.?) as high_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / ?.?) as low_1440, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / ?.?) as high_1440, dtt.absolutetimezoneoffset as datafeedtimezoneoffset, dtt.timezone as datafeedtimezonename, (round((cast(? as float) - rank) / ? * ?)) as rank_rounded, ((cast(? as float) - rank) / ? * ?) as rank from last_candle lc inner join downloadersymbolsettings dss on lc.symbolid = dss.symbolid inner join datafeedstimetable dtt on trim(dss.classname) = trim(dtt.classname) and dtt.dayofweek = ? -- assuming timezone is same for whole week. inner join powerstats_symboldata psd on psd.symbolid = lc.symbolid left outer join powerstats_trumpet psp on psd.trumpetsymbolid = psp.symbolid and psp.dayofweek = extract(dow from lc.latest_candle_time) and psp.fromtime = cast(extract(? from lc.latest_candle_time) as integer) * ? + extract(? from (cast(extract(? from lc.latest_candle_time) as integer) / ?) * ? * interval ?) inner join prfsymboltree prf on psd.symbolid = prf.symbolid and date_trunc(?, prf.enddate) = date_trunc(?, psp.enddate) left join lateral ( select ph.hour, (ave + stddev) as volatility, rank() over (order by (ave + stddev) desc) as rank from powerstats_hourly ph where ph.symbolid = psd.hourlysymbolid and date_trunc(?,ph.enddate) = date_trunc(?, prf.enddate) ) rank_query on true where prf.brokerid = ? and rank_query.hour = floor((psp.fromtime) / ?) and volatility > ? order by rank desc, rank_rounded desc, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Sep 17 13 114 39s209ms 343ms [ User: postgres - Total duration: 39s209ms - Times executed: 114 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 39s209ms - Times executed: 114 ]
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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: 2025-09-17 13:16:01 Duration: 1s15ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-09-17 13:52:01 Duration: 916ms 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: 2025-09-17 13:12:01 Duration: 877ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
9 39s61ms 16 2s50ms 3s634ms 2s441ms 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 #9
Day Hour Count Duration Avg duration Sep 17 13 16 39s61ms 2s441ms [ User: postgres - Total duration: 39s61ms - Times executed: 16 ]
[ Application: psql - Total duration: 39s61ms - 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: 2025-09-17 13:01:17 Duration: 3s634ms 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: 2025-09-17 13:11:17 Duration: 3s551ms 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: 2025-09-17 13:26:17 Duration: 3s529ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
10 33s577ms 6 5s186ms 6s851ms 5s596ms 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 #10
Day Hour Count Duration Avg duration Sep 17 13 6 33s577ms 5s596ms [ User: postgres - Total duration: 33s577ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 33s577ms - 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: 2025-09-17 13:00:09 Duration: 6s851ms 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: 2025-09-17 13:30:07 Duration: 5s397ms 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: 2025-09-17 13:50:08 Duration: 5s397ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
11 30s450ms 14,478 0ms 25ms 2ms 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 Sep 17 13 14,478 30s450ms 2ms [ User: postgres - Total duration: 30s450ms - Times executed: 14478 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 30s450ms - Times executed: 14478 ]
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'SGDJPY' OR dss.downloadersymbol = 'SGDJPY') AND dss.enabled = 1;
Date: 2025-09-17 13:00:04 Duration: 25ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'JP225' OR dss.downloadersymbol = 'JP225') AND dss.enabled = 1;
Date: 2025-09-17 13:00:04 Duration: 20ms 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 = 'USDSGD' OR dss.downloadersymbol = 'USDSGD') AND dss.enabled = 1;
Date: 2025-09-17 13:00:04 Duration: 17ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
12 25s719ms 8 2s971ms 3s921ms 3s214ms select updateresultsmaterializedview ();Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Sep 17 13 8 25s719ms 3s214ms [ User: postgres - Total duration: 25s719ms - Times executed: 8 ]
[ Application: psql - Total duration: 25s719ms - Times executed: 8 ]
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select updateresultsmaterializedview ();
Date: 2025-09-17 13:17:28 Duration: 3s921ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-09-17 13:02:25 Duration: 3s306ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-09-17 13:47:21 Duration: 3s274ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
13 20s597ms 16 1s269ms 1s303ms 1s287ms 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 #13
Day Hour Count Duration Avg duration Sep 17 13 16 20s597ms 1s287ms [ User: postgres - Total duration: 20s597ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 20s597ms - 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 = '620' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '620' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '620' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-09-17 13:21:44 Duration: 1s303ms 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 = '620' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '620' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '620' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-09-17 13:36:41 Duration: 1s302ms 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: 2025-09-17 13:06:58 Duration: 1s298ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
14 19s609ms 16 817ms 1s944ms 1s225ms 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 #14
Day Hour Count Duration Avg duration Sep 17 13 16 19s609ms 1s225ms [ User: postgres - Total duration: 19s609ms - Times executed: 16 ]
[ Application: psql - Total duration: 19s609ms - 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: 2025-09-17 13:11:13 Duration: 1s944ms 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: 2025-09-17 13:01:13 Duration: 1s792ms 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: 2025-09-17 13:16:13 Duration: 1s449ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
15 16s771ms 158 17ms 405ms 106ms select distinct k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid from relevance_keylevels_results p inner join keylevels_results k on p.resultuid = k.resultuid inner join autochartist_stocklist asl on k.symbolid = asl.symbolid where k.patternclassid in (...) and asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Sep 17 13 158 16s771ms 106ms [ User: postgres - Total duration: 16s771ms - Times executed: 158 ]
[ Application: [unknown] - Total duration: 16s771ms - Times executed: 158 ]
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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 'PEPPERSTONE - 1';
Date: 2025-09-17 13:06:42 Duration: 405ms 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 'IQFEED_FX - 1';
Date: 2025-09-17 13:00:04 Duration: 348ms 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 'PEPPERSTONE - 1';
Date: 2025-09-17 13:02:04 Duration: 281ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
16 12s351ms 158 16ms 327ms 78ms 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 Sep 17 13 158 12s351ms 78ms [ User: postgres - Total duration: 12s351ms - Times executed: 158 ]
[ Application: [unknown] - Total duration: 12s351ms - Times executed: 158 ]
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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: 2025-09-17 13:06:29 Duration: 327ms 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: 2025-09-17 13:45:57 Duration: 280ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2025-09-17 13:00:55 Duration: 272ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
17 12s154ms 4,677 0ms 32ms 2ms 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 #17
Day Hour Count Duration Avg duration Sep 17 13 4,677 12s154ms 2ms [ User: postgres - Total duration: 12s154ms - Times executed: 4677 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12s154ms - Times executed: 4677 ]
-
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 = '606827372930462301' 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 = '606827372930462301' OR a.resultuid = '606827372930462301') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:25:48 Duration: 32ms 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 = '606828085908377301' 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 = '606828085908377301' OR a.resultuid = '606828085908377301') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:56:56 Duration: 28ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 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 = '606790819861944301' 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 = '606790819861944301' OR a.resultuid = '606790819861944301') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:25:48 Duration: 26ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
18 8s577ms 7,582 0ms 9ms 1ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Sep 17 13 7,582 8s577ms 1ms [ User: postgres - Total duration: 8s577ms - Times executed: 7582 ]
[ Application: [unknown] - Total duration: 8s577ms - Times executed: 7582 ]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 155, schedule: 0 15 * * 2 Africa/Johannesburg', NULL, NULL);
Date: 2025-09-17 13:00:53 Duration: 9ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 28, schedule: 0 15 * * 5 Africa/Johannesburg', NULL, NULL);
Date: 2025-09-17 13:25:49 Duration: 8ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 27, schedule: 0 * * * * Africa/Johannesburg', NULL, NULL);
Date: 2025-09-17 13:10:50 Duration: 7ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
19 8s338ms 6 1s22ms 1s773ms 1s389ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Sep 17 13 6 8s338ms 1s389ms [ User: postgres - Total duration: 8s338ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 8s338ms - Times executed: 6 ]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-09-17 13:46:18 Duration: 1s773ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-09-17 13:01:18 Duration: 1s671ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-09-17 13:31:18 Duration: 1s665ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
20 6s586ms 6,169 0ms 15ms 1ms insert into autochartist_results (resultid, symbolid, bandwidth, pattern, qtytp, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, relevancestartdistance, simulation, writtendatetime) values (?, ?, ?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Sep 17 13 6,169 6s586ms 1ms [ User: postgres - Total duration: 6s586ms - Times executed: 6169 ]
[ Application: [unknown] - Total duration: 6s586ms - Times executed: 6169 ]
-
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 ('515840245922195300-1|45917.125|45917.5521|45916.7083|45917.4792|45815.4|45792.9|45655.4|45717.9', 515840245922195300, 3.000000000000000000000000000000, 'Triangle', 4, '2025-09-17 11:10:47'::timestamp without time zone, - 1, 0.716139651606310323400000000000, - 1.000000000000000000000000000000, 0.000000000000000000000000000000, 0.682441101319760989800000000000, 0.387952628599215587600000000000, 45659.414324551311440000000000000000, 45712.489301896377580000000000000000, '2025-09-17 13:45:00'::timestamp without time zone, '2025-09-18 00:07:30'::timestamp without time zone, '2025-09-16 16:15:00'::timestamp without time zone, '2025-09-17 13:45:00'::timestamp without time zone, 45962.900000000001460000000000000000, 45746.199999999997090000000000000000, '2025-09-17 03:00:00'::timestamp without time zone, '2025-09-17 13:15:00'::timestamp without time zone, '2025-09-16 17:00:00'::timestamp without time zone, '2025-09-17 11:30:00'::timestamp without time zone, 45815.400000000001460000000000000000, 45792.900000000001460000000000000000, 45655.400000000001460000000000000000, 45717.900000000001460000000000000000, 0.892857142857142904700000000000, - 0.548780487804878092100000000000, 1.900720525062483013000000000000, 0.473883726295254992200000000000, 'Continuation', 0.000000000000000000000000000000, '2025-09-17 13:45:00'::timestamp without time zone, 45750.400000000001460000000000000000, 79, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-09-17 13:16:01 Duration: 15ms 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 ('515840233915106300-1|45916.6458|45917.4167|45916.4167|45916.75|7894.6|7848.2|7860.6|7809.8', 515840233915106300, 2.000000000000000000000000000000, 'Channel Down', 4, '2025-09-17 10:55:53'::timestamp without time zone, - 1, 0.387434107981701692000000000000, - 1.000000000000000000000000000000, 0.536747029328937364000000000000, 0.141564288061337528700000000000, 0.737063292145573423200000000000, 7773.032109675903484000000000000000, 7788.763379031626755000000000000000, '2025-09-17 13:30:00'::timestamp without time zone, '2025-09-18 03:15:00'::timestamp without time zone, '2025-09-16 09:00:00'::timestamp without time zone, '2025-09-17 13:30:00'::timestamp without time zone, 7912.500000000000000000000000000000, 7795.899999999999636000000000000000, '2025-09-16 15:30:00'::timestamp without time zone, '2025-09-17 10:00:00'::timestamp without time zone, '2025-09-16 10:00:00'::timestamp without time zone, '2025-09-16 18:00:00'::timestamp without time zone, 7894.600000000000364000000000000000, 7848.199999999999818000000000000000, 7860.600000000000364000000000000000, 7809.800000000000182000000000000000, - 3.175000000000011369000000000000, - 2.729411764705914400000000000000, 2.949658508786782374000000000000, 0.660977704021979195500000000000, 'Continuation', 0.000000000000000000000000000000, '2025-09-17 13:30:00'::timestamp without time zone, 7800.000000000000000000000000000000, 35, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-09-17 13:01:07 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('6056793637973123000.2717|45916.7708|45917.5104|45916.5417|45917.5833|431.13|429.38|424.38|428.13', 605679363797312300, 5.000000000000000000000000000000, 'Triangle', 5, '2025-09-17 11:41:59'::timestamp without time zone, 1, 0.097074618529683437410000000000, 0.271731746419930253500000000000, 0.802298850574712507600000000000, 0.196450200720041406900000000000, 0.532315914723402894300000000000, 430.568317066616543800000000000000, 432.581960959879779700000000000000, '2025-09-17 14:30:00'::timestamp without time zone, '2025-09-18 03:15:00'::timestamp without time zone, '2025-09-16 04:45:00'::timestamp without time zone, '2025-09-17 14:30:00'::timestamp without time zone, 424.879999999999995400000000000000, 429.044893617021273200000000000000, '2025-09-16 18:30:00'::timestamp without time zone, '2025-09-17 12:15:00'::timestamp without time zone, '2025-09-16 13:00:00'::timestamp without time zone, '2025-09-17 14:00:00'::timestamp without time zone, 431.129999999999995400000000000000, 429.379999999999995400000000000000, 424.379999999999995400000000000000, 428.129999999999995400000000000000, 0.051369863013698627280000000000, - 0.037234042553191487590000000000, 1.742670388540989324000000000000, 0.426168019738243808400000000000, 'Reversal', 0.085106382978722194820000000000, '2025-09-17 14:30:00'::timestamp without time zone, 429.129999999999995400000000000000, 75, 0, 1.593750000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-09-17 13:47:13 Duration: 12ms 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 62,859 265ms 0ms 5ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Sep 17 13 62,859 265ms 0ms [ User: postgres - Total duration: 265ms - Times executed: 62859 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 255ms - Times executed: 62694 ]
[ Application: [unknown] - Total duration: 10ms - Times executed: 165 ]
-
select 1;
Date: 2025-09-17 13:10:33 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-09-17 13:55:56 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-09-17 13:00:06 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
2 38,563 55s775ms 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 Sep 17 13 38,563 55s775ms 1ms [ User: postgres - Total duration: 55s775ms - Times executed: 38563 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 55s775ms - Times executed: 38563 ]
-
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 = '515840249435063300';
Date: 2025-09-17 13:00:04 Duration: 21ms 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 = '958' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '958' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840248627808300';
Date: 2025-09-17 13:15:49 Duration: 19ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 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 = '958' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '958' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840216981120300';
Date: 2025-09-17 13:06:00 Duration: 18ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
3 14,478 30s450ms 0ms 25ms 2ms 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 Sep 17 13 14,478 30s450ms 2ms [ User: postgres - Total duration: 30s450ms - Times executed: 14478 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 30s450ms - Times executed: 14478 ]
-
SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'SGDJPY' OR dss.downloadersymbol = 'SGDJPY') AND dss.enabled = 1;
Date: 2025-09-17 13:00:04 Duration: 25ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'JP225' OR dss.downloadersymbol = 'JP225') AND dss.enabled = 1;
Date: 2025-09-17 13:00:04 Duration: 20ms 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 = 'USDSGD' OR dss.downloadersymbol = 'USDSGD') AND dss.enabled = 1;
Date: 2025-09-17 13:00:04 Duration: 17ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
4 10,304 101ms 0ms 2ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Sep 17 13 10,304 101ms 0ms [ User: postgres - Total duration: 101ms - Times executed: 10304 ]
[ Application: [unknown] - Total duration: 101ms - Times executed: 10304 ]
-
SET extra_float_digits = 3;
Date: 2025-09-17 13:16:21 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2025-09-17 13:16:07 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2025-09-17 13:02:02 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: [unknown] Bind query: yes
5 10,278 118ms 0ms 2ms 0ms set application_name = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Sep 17 13 10,278 118ms 0ms [ User: postgres - Total duration: 118ms - Times executed: 10278 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 118ms - Times executed: 10278 ]
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-09-17 13:40:52 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: 2025-09-17 13:28:19 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-09-17 13:01:35 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
6 7,582 8s577ms 0ms 9ms 1ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Sep 17 13 7,582 8s577ms 1ms [ User: postgres - Total duration: 8s577ms - Times executed: 7582 ]
[ Application: [unknown] - Total duration: 8s577ms - Times executed: 7582 ]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 155, schedule: 0 15 * * 2 Africa/Johannesburg', NULL, NULL);
Date: 2025-09-17 13:00:53 Duration: 9ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 28, schedule: 0 15 * * 5 Africa/Johannesburg', NULL, NULL);
Date: 2025-09-17 13:25:49 Duration: 8ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 27, schedule: 0 * * * * Africa/Johannesburg', NULL, NULL);
Date: 2025-09-17 13:10:50 Duration: 7ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
7 6,173 6s364ms 0ms 23ms 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 #7
Day Hour Count Duration Avg duration Sep 17 13 6,173 6s364ms 1ms [ User: postgres - Total duration: 6s364ms - Times executed: 6173 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 6s364ms - Times executed: 6173 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-09-17 14:00:00', '17.37509', '17.38121', '17.37085', '17.38038', '2195', '515840247968204300', '0', '2025-09-17 13:16:01.223', '2025-09-17 13:16:01.157') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '17.37509', high = '17.38121', low = '17.37085', close = '17.38038', volume = '2195', bsf = '0', sastdatetimewritten = '2025-09-17 13:16:01.223', sastdatetimereceived = '2025-09-17 13:16:01.157';
Date: 2025-09-17 13:16:01 Duration: 23ms 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 ('2025-09-17 14:00:00', '26.7', '26.81', '26.68', '26.78', '104', '515840246003549300', '0', '2025-09-17 13:16:02.546', '2025-09-17 13:16:02.444') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '26.7', high = '26.81', low = '26.68', close = '26.78', volume = '104', bsf = '0', sastdatetimewritten = '2025-09-17 13:16:02.546', sastdatetimereceived = '2025-09-17 13:16:02.444';
Date: 2025-09-17 13:16:02 Duration: 22ms 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 ('2025-09-17 13:45:00', '82.43', '82.52', '82.37', '82.42', '115', '515840233307850300', '0', '2025-09-17 13:00:57.643', '2025-09-17 13:00:57.491') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '82.43', high = '82.52', low = '82.37', close = '82.42', volume = '115', bsf = '0', sastdatetimewritten = '2025-09-17 13:00:57.643', sastdatetimereceived = '2025-09-17 13:00:57.491';
Date: 2025-09-17 13:00:57 Duration: 17ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
8 6,169 6s586ms 0ms 15ms 1ms insert into autochartist_results (resultid, symbolid, bandwidth, pattern, qtytp, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, relevancestartdistance, simulation, writtendatetime) values (?, ?, ?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Sep 17 13 6,169 6s586ms 1ms [ User: postgres - Total duration: 6s586ms - Times executed: 6169 ]
[ Application: [unknown] - Total duration: 6s586ms - Times executed: 6169 ]
-
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 ('515840245922195300-1|45917.125|45917.5521|45916.7083|45917.4792|45815.4|45792.9|45655.4|45717.9', 515840245922195300, 3.000000000000000000000000000000, 'Triangle', 4, '2025-09-17 11:10:47'::timestamp without time zone, - 1, 0.716139651606310323400000000000, - 1.000000000000000000000000000000, 0.000000000000000000000000000000, 0.682441101319760989800000000000, 0.387952628599215587600000000000, 45659.414324551311440000000000000000, 45712.489301896377580000000000000000, '2025-09-17 13:45:00'::timestamp without time zone, '2025-09-18 00:07:30'::timestamp without time zone, '2025-09-16 16:15:00'::timestamp without time zone, '2025-09-17 13:45:00'::timestamp without time zone, 45962.900000000001460000000000000000, 45746.199999999997090000000000000000, '2025-09-17 03:00:00'::timestamp without time zone, '2025-09-17 13:15:00'::timestamp without time zone, '2025-09-16 17:00:00'::timestamp without time zone, '2025-09-17 11:30:00'::timestamp without time zone, 45815.400000000001460000000000000000, 45792.900000000001460000000000000000, 45655.400000000001460000000000000000, 45717.900000000001460000000000000000, 0.892857142857142904700000000000, - 0.548780487804878092100000000000, 1.900720525062483013000000000000, 0.473883726295254992200000000000, 'Continuation', 0.000000000000000000000000000000, '2025-09-17 13:45:00'::timestamp without time zone, 45750.400000000001460000000000000000, 79, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-09-17 13:16:01 Duration: 15ms 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 ('515840233915106300-1|45916.6458|45917.4167|45916.4167|45916.75|7894.6|7848.2|7860.6|7809.8', 515840233915106300, 2.000000000000000000000000000000, 'Channel Down', 4, '2025-09-17 10:55:53'::timestamp without time zone, - 1, 0.387434107981701692000000000000, - 1.000000000000000000000000000000, 0.536747029328937364000000000000, 0.141564288061337528700000000000, 0.737063292145573423200000000000, 7773.032109675903484000000000000000, 7788.763379031626755000000000000000, '2025-09-17 13:30:00'::timestamp without time zone, '2025-09-18 03:15:00'::timestamp without time zone, '2025-09-16 09:00:00'::timestamp without time zone, '2025-09-17 13:30:00'::timestamp without time zone, 7912.500000000000000000000000000000, 7795.899999999999636000000000000000, '2025-09-16 15:30:00'::timestamp without time zone, '2025-09-17 10:00:00'::timestamp without time zone, '2025-09-16 10:00:00'::timestamp without time zone, '2025-09-16 18:00:00'::timestamp without time zone, 7894.600000000000364000000000000000, 7848.199999999999818000000000000000, 7860.600000000000364000000000000000, 7809.800000000000182000000000000000, - 3.175000000000011369000000000000, - 2.729411764705914400000000000000, 2.949658508786782374000000000000, 0.660977704021979195500000000000, 'Continuation', 0.000000000000000000000000000000, '2025-09-17 13:30:00'::timestamp without time zone, 7800.000000000000000000000000000000, 35, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-09-17 13:01:07 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('6056793637973123000.2717|45916.7708|45917.5104|45916.5417|45917.5833|431.13|429.38|424.38|428.13', 605679363797312300, 5.000000000000000000000000000000, 'Triangle', 5, '2025-09-17 11:41:59'::timestamp without time zone, 1, 0.097074618529683437410000000000, 0.271731746419930253500000000000, 0.802298850574712507600000000000, 0.196450200720041406900000000000, 0.532315914723402894300000000000, 430.568317066616543800000000000000, 432.581960959879779700000000000000, '2025-09-17 14:30:00'::timestamp without time zone, '2025-09-18 03:15:00'::timestamp without time zone, '2025-09-16 04:45:00'::timestamp without time zone, '2025-09-17 14:30:00'::timestamp without time zone, 424.879999999999995400000000000000, 429.044893617021273200000000000000, '2025-09-16 18:30:00'::timestamp without time zone, '2025-09-17 12:15:00'::timestamp without time zone, '2025-09-16 13:00:00'::timestamp without time zone, '2025-09-17 14:00:00'::timestamp without time zone, 431.129999999999995400000000000000, 429.379999999999995400000000000000, 424.379999999999995400000000000000, 428.129999999999995400000000000000, 0.051369863013698627280000000000, - 0.037234042553191487590000000000, 1.742670388540989324000000000000, 0.426168019738243808400000000000, 'Reversal', 0.085106382978722194820000000000, '2025-09-17 14:30:00'::timestamp without time zone, 429.129999999999995400000000000000, 75, 0, 1.593750000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-09-17 13:47:13 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
9 4,677 12s154ms 0ms 32ms 2ms 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 #9
Day Hour Count Duration Avg duration Sep 17 13 4,677 12s154ms 2ms [ User: postgres - Total duration: 12s154ms - Times executed: 4677 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12s154ms - Times executed: 4677 ]
-
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 = '606827372930462301' 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 = '606827372930462301' OR a.resultuid = '606827372930462301') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:25:48 Duration: 32ms 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 = '606828085908377301' 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 = '606828085908377301' OR a.resultuid = '606828085908377301') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:56:56 Duration: 28ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 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 = '606790819861944301' 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 = '606790819861944301' OR a.resultuid = '606790819861944301') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:25:48 Duration: 26ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
10 3,520 204ms 0ms 2ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Sep 17 13 3,520 204ms 0ms [ User: postgres - Total duration: 204ms - Times executed: 3520 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 204ms - Times executed: 3520 ]
-
select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = '605633814904189307' and category = lower('initialtrend') union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = '605633814904189307' and category = lower('initialtrend') order by correct desc) as summdata group by category, name having sum(total) > 0 ORDER BY name;
Date: 2025-09-17 13:18:49 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = '515852059305993307' and category = lower('initialtrend') union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = '515852059305993307' and category = lower('initialtrend') order by correct desc) as summdata group by category, name having sum(total) > 0 ORDER BY name;
Date: 2025-09-17 13:18:24 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = '606605126048151307' and category = lower('initialtrend') union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = '606605126048151307' and category = lower('initialtrend') order by correct desc) as summdata group by category, name having sum(total) > 0 ORDER BY name;
Date: 2025-09-17 13:18:51 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
11 3,469 1s880ms 0ms 8ms 0ms insert into t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Sep 17 13 3,469 1s880ms 0ms [ User: postgres - Total duration: 1s880ms - Times executed: 3469 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s880ms - Times executed: 3469 ]
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-09-17 13:30:00', '39.6', '39.62', '39.38', '39.54', '42', '515840247893477300', '0', '2025-09-17 13:01:04.901', '2025-09-17 13:01:04.727') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '39.6', high = '39.62', low = '39.38', close = '39.54', volume = '42', bsf = '0', sastdatetimewritten = '2025-09-17 13:01:04.901', sastdatetimereceived = '2025-09-17 13:01:04.727';
Date: 2025-09-17 13:01:04 Duration: 8ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-09-17 13:30:00', '106.335', '106.346', '106.303', '106.326', '1955', '515840247880157300', '0', '2025-09-17 13:00:44.06', '2025-09-17 13:00:43.947') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '106.335', high = '106.346', low = '106.303', close = '106.326', volume = '1955', bsf = '0', sastdatetimewritten = '2025-09-17 13:00:44.06', sastdatetimereceived = '2025-09-17 13:00:43.947';
Date: 2025-09-17 13:00:44 Duration: 8ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-09-17 13:30:00', '1.36452', '1.36514', '1.3639', '1.36434', '1413', '515840247884826300', '0', '2025-09-17 13:00:52.525', '2025-09-17 13:00:52.378') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '1.36452', high = '1.36514', low = '1.3639', close = '1.36434', volume = '1413', bsf = '0', sastdatetimewritten = '2025-09-17 13:00:52.525', sastdatetimereceived = '2025-09-17 13:00:52.378';
Date: 2025-09-17 13:00:52 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
12 3,138 3s832ms 0ms 19ms 1ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ) select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as ruid, s.symbolid as sid, s.symbol as sym, longname, shortname, exchange as e, timegranularity as tg, a.patternid as pid, a.direction as d, a.patternprice as pp, atbaridentified as pet, case when (x9 != ?) then x9 when (x8 != ?) then x8 when (x7 != ?) then x7 when (x6 != ?) then x6 when (x5 != ?) then x5 when (x4 != ?) then x4 when (x3 != ?) then x3 when (x2 != ?) then x2 end as pst, patternprice as patp, x0, x1, x2, case when (x3 != ?) then x3 else ? end as x3, case when (x4 != ?) then x4 else ? end as x4, case when (x5 != ?) then x5 else ? end as x5, case when (x6 != ?) then x6 else ? end as x6, case when (x7 != ?) then x7 else ? end as x7, case when (x8 != ?) then x8 else ? end as x8, errormargin as erm, breakoutprice as pe, breakoutbars as be, breakout, atbaridentified as atbar, atpriceidentified as atprice, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzos, dtt.timezone as timezone, approachingtimestamp as apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, furthestprice as fp, newlevels.filtered, a.uniquepointsvalue as upv, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from keylevels_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join hrspatterns p on a.patternid = p.patternid inner join rar_max rm on ? = ? left outer join relevance_keylevels_results rar on a.resultuid = rar.resultuid left join lateral calc_kl_signal_filter (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Sep 17 13 3,138 3s832ms 1ms [ User: postgres - Total duration: 3s832ms - Times executed: 3138 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s832ms - Times executed: 3138 ]
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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 = '606827844950313303' 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 = '606827844950313303' OR a.resultuid = '606827844950313303') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:44:53 Duration: 19ms 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 = '606827614577157303' 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 = '606827614577157303' OR a.resultuid = '606827614577157303') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:01:59 Duration: 19ms 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 = '606828089078013303' 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 = '606828089078013303' OR a.resultuid = '606828089078013303') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:41:51 Duration: 19ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
13 2,510 1s361ms 0ms 8ms 0ms insert into fibonacci_results (bandwidth, pattern, gmttimefound, direction, patternstarttime, patternendtime, patternstartprice, patternendprice, qtytp, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, patternlengthbars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) values (?.?, ?, ?::timestamp without time zone, ?, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?, ?, ?, ?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Sep 17 13 2,510 1s361ms 0ms [ User: postgres - Total duration: 1s361ms - Times executed: 2510 ]
[ Application: [unknown] - Total duration: 1s361ms - Times executed: 2510 ]
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INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, 'ABCD', '2025-09-17 11:11:30'::timestamp without time zone, - 1, '2025-08-22 00:00:00'::timestamp without time zone, '2025-09-16 00:00:00'::timestamp without time zone, 201.800000000000011400000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 191.250000000000000000000000000000, '2025-09-02 00:00:00'::timestamp without time zone, 202.849999999999994300000000000000, '2025-09-08 00:00:00'::timestamp without time zone, 195.419999999999987500000000000000, '2025-09-12 00:00:00'::timestamp without time zone, 207.019999999999981800000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.859366082752065163500000000000, - 1.000000000000000000000000000000, 15.581410940310929550000000000000, 12, 195.419999999999987500000000000000, 199.850805731079987000000000000000, 188.250805731079992700000000000000, 197.900644017519994100000000000000, 192.264572065799995900000000000000, 201.219999999999970400000000000000, 202.589194268919982300000000000000, 515840249536185300, 0.281267834495869673000000000000, 'BC=0.618*AB (0.641) ', 0, 'ABCD|-1|2025-08-22 00:00:00|201.8|-1|4|12|BC=0.618*AB (0.641)|0|515840249536185300|1899-12-29 00:00:00|2025-09-02 00:00:00|2025-09-08 00:00:00|2025-09-12 00:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-09-17 13:16:44 Duration: 8ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, 'ABCD', '2025-09-17 11:11:30'::timestamp without time zone, - 1, '2025-08-22 00:00:00'::timestamp without time zone, '2025-09-16 00:00:00'::timestamp without time zone, 201.800000000000011400000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 191.250000000000000000000000000000, '2025-09-02 00:00:00'::timestamp without time zone, 202.849999999999994300000000000000, '2025-09-08 00:00:00'::timestamp without time zone, 195.419999999999987500000000000000, '2025-09-12 00:00:00'::timestamp without time zone, 207.019999999999981800000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.859366082752065163500000000000, - 1.000000000000000000000000000000, 15.581410940310929550000000000000, 12, 195.419999999999987500000000000000, 199.850805731079987000000000000000, 188.250805731079992700000000000000, 197.900644017519994100000000000000, 192.264572065799995900000000000000, 201.219999999999970400000000000000, 202.589194268919982300000000000000, 515840249536185300, 0.281267834495869673000000000000, 'BC=0.618*AB (0.641) ', 0, 'ABCD|-1|2025-08-22 00:00:00|201.8|-1|4|12|BC=0.618*AB (0.641)|0|515840249536185300|1899-12-29 00:00:00|2025-09-02 00:00:00|2025-09-08 00:00:00|2025-09-12 00:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-09-17 13:16:44 Duration: 8ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, '3 Point Extension', '2025-09-17 11:11:17'::timestamp without time zone, 1, '2025-09-17 06:45:00'::timestamp without time zone, '2025-09-17 11:00:00'::timestamp without time zone, 87.442999999999997840000000000000, 87.418499999999994540000000000000, 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, 87.442999999999997840000000000000, '2025-09-17 06:45:00'::timestamp without time zone, 87.581999999999993640000000000000, '2025-09-17 08:00:00'::timestamp without time zone, 87.362999999999999540000000000000, '2025-09-17 11:00:00'::timestamp without time zone, 0.468908499934979627900000000000, - 1.000000000000000000000000000000, 0.525259922244438515200000000000, 17, 87.581999999999993640000000000000, 87.498349443525299300000000000000, 87.717349443525293400000000000000, 87.535167151738193070000000000000, 87.641572303240494080000000000000, 87.472499999999996590000000000000, 87.446650556474693870000000000000, 515840249735832300, 0.587442922374479259400000000000, 'CD=1.618*BC (1.576) ', 0, '3 Point Extension|1|2025-09-17 06:45:00|87.443|87.4185|3|17|CD=1.618*BC (1.576)|0|515840249735832300|1899-12-29 00:00:00|1899-12-29 00:00:00|2025-09-17 06:45:00|2025-09-17 08:00:00|2025-09-17 11:00:00', 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-09-17 13:16:32 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
14 2,247 1s38ms 0ms 9ms 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 #14
Day Hour Count Duration Avg duration Sep 17 13 2,247 1s38ms 0ms [ User: postgres - Total duration: 1s38ms - Times executed: 2247 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s38ms - Times executed: 2247 ]
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-09-17 13:00:00', '3.59001', '3.59501', '3.59001', '3.59345', '2706', '515840247873988300', '0', '2025-09-17 13:01:00.703', '2025-09-17 13:01:00.588') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '3.59001', high = '3.59501', low = '3.59001', close = '3.59345', volume = '2706', bsf = '0', sastdatetimewritten = '2025-09-17 13:01:00.703', sastdatetimereceived = '2025-09-17 13:01:00.588';
Date: 2025-09-17 13:01:00 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-09-17 13:00:00', '17.37547', '17.38711', '17.36655', '17.37556', '8587', '515840247968908300', '0', '2025-09-17 13:01:02.886', '2025-09-17 13:01:02.819') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '17.37547', high = '17.38711', low = '17.36655', close = '17.37556', volume = '8587', bsf = '0', sastdatetimewritten = '2025-09-17 13:01:02.886', sastdatetimereceived = '2025-09-17 13:01:02.819';
Date: 2025-09-17 13:01:02 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-09-17 13:00:00', '1.98205', '1.9823', '1.98083', '1.98116', '5724', '515840247884031300', '0', '2025-09-17 13:00:50.461', '2025-09-17 13:00:50.268') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '1.98205', high = '1.9823', low = '1.98083', close = '1.98116', volume = '5724', bsf = '0', sastdatetimewritten = '2025-09-17 13:00:50.461', sastdatetimereceived = '2025-09-17 13:00:50.268';
Date: 2025-09-17 13:00:50 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
15 1,920 76ms 0ms 1ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Sep 17 13 1,920 76ms 0ms [ User: postgres - Total duration: 76ms - Times executed: 1920 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 76ms - Times executed: 1920 ]
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select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = '605733127268055307' and category = lower('direction') order by correct desc) as summdata group by category, name having sum(total) > 0 order by name;
Date: 2025-09-17 13:18:50 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = '604583677957083307' and category = lower('overall') order by correct desc) as summdata group by category, name having sum(total) > 0 order by name;
Date: 2025-09-17 13:18:46 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = '604104683408419307' and category = lower('hourofday') order by correct desc) as summdata group by category, name having sum(total) > 0 order by name;
Date: 2025-09-17 13:18:44 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
16 1,763 972ms 0ms 4ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Sep 17 13 1,763 972ms 0ms [ User: postgres - Total duration: 972ms - Times executed: 1763 ]
[ Application: [unknown] - Total duration: 972ms - Times executed: 1763 ]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-09-17 13:00:00', reason = 'Approaching pattern wick broke through price level.' WHERE uniqueIndex = '|515840216877827300|10.95951|1|2025-09-17 12:00:00|2025-09-17 12:00:00|1|-1' and relevant = 1;
Date: 2025-09-17 13:02:11 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 = '2025-09-17 13:00:00', reason = 'Emerging pattern formed a completed pattern.' WHERE uniqueIndex = '515840246120662300-1|45897.4583|45916.625|45876.6667|45912.625|390.6|423.35|292.4|384.2' and relevant = 1;
Date: 2025-09-17 13:01:59 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 = '2025-09-17 13:30:00', reason = 'Price has entered the prediction area for a completed pattern' WHERE uniqueIndex = '5158402177294353000.6542|45916.7292|45917.3958|45916.6458|45917.3333|1.9827|1.9859|1.9748|1.9822' and relevant = 1;
Date: 2025-09-17 13:00:48 Duration: 3ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
17 1,686 614ms 0ms 4ms 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars as length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternstartprice, resy1, supporty1, dtt.timezone, cps.pip, newlevels.profit from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern left join currencypips cps on cps.symbol = s.symbol left join lateral calc_cp_signal (a.resultuid) newlevels on true where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Sep 17 13 1,686 614ms 0ms [ User: postgres - Total duration: 614ms - Times executed: 1686 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 614ms - Times executed: 1686 ]
-
SELECT CASE WHEN a.old_resultuid = '606828081395358301' 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 = '606828081395358301' OR a.resultuid = '606828081395358301') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:11:07 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT CASE WHEN a.old_resultuid = '606828082976060301' 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 = '606828082976060301' OR a.resultuid = '606828082976060301') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:46:55 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT CASE WHEN a.old_resultuid = '606823839698782301' 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 = '606823839698782301' OR a.resultuid = '606823839698782301') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:46:55 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
18 1,602 2s930ms 0ms 9ms 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 #18
Day Hour Count Duration Avg duration Sep 17 13 1,602 2s930ms 1ms [ User: postgres - Total duration: 2s930ms - Times executed: 1602 ]
[ Application: [unknown] - Total duration: 2s930ms - Times executed: 1602 ]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, - 1, 1, '2025-09-17 11:10:42'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 25, 66.439999999999997720000000000000, '2025-09-17 06:30:00', '2025-09-17 04:30:00', '2025-09-16 09:30:00', '', '', '', '', '', '', '', 50, 66.460499999999996140000000000000, '2025-09-17 06:30:00'::timestamp without time zone, '2025-09-17 06:30:00', 0.000000000000000000000000000000, 0.020499999999999830860000000000, - 1, 515840249537406300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249537406300|66.44|1|2025-09-17 06:30:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-09-16 09:30:00', 66.510000000000005120000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-09-17 13:15:56 Duration: 9ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (3.000000000000000000000000000000, - 1, 2, '2025-09-17 10:55:51'::timestamp without time zone, '2025-09-17 13:00:00', 0.001315000000000018411000000000, 4, 108, 0.916259999999999963400000000000, '2025-09-16 17:00:00', '2025-09-11 12:00:00', '2025-09-11 04:00:00', '2025-09-11 00:00:00', '', '', '', '', '', '', 220, 0.915926499999999976800000000000, '2025-09-17 13:00:00'::timestamp without time zone, '2025-09-17 13:00:00', 0.917455000000000020500000000000, 0.000391750000000002014200000000, - 1, 515840230419498300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840230419498300|0.91626|2|2025-09-17 13:00:00|2025-09-17 13:00:00|-1|-1', 0.918074700000000021300000000000, 0.001814700000000057933000000000, 2, '2025-09-11 00:00:00', 0.919080000000000008000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-09-17 13:01:05 Duration: 9ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (3.000000000000000000000000000000, - 1, 2, '2025-09-17 10:55:45'::timestamp without time zone, '2025-09-17 13:00:00', 0.001449999999999989058000000000, 4, 105, 0.915930000000000021900000000000, '2025-09-16 15:00:00', '2025-09-11 15:00:00', '2025-09-11 09:00:00', '2025-09-11 04:00:00', '', '', '', '', '', '', 207, 0.915602499999999985800000000000, '2025-09-17 13:00:00'::timestamp without time zone, '2025-09-17 13:00:00', 0.917329999999999978800000000000, 0.000334499999999999023400000000, - 1, 515840243909699300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840243909699300|0.91593|2|2025-09-17 13:00:00|2025-09-17 13:00:00|-1|-1', 0.917931000000000052400000000000, 0.002001000000000030532000000000, 2, '2025-09-11 04:00:00', 0.918959999999999999100000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-09-17 13:00:59 Duration: 8ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
19 1,332 14ms 0ms 0ms 0ms select null as table_cat, n.nspname as table_schem, c.relname as table_name, case n.nspname ~ ? or n.nspname = ? when true then case when n.nspname = ? or n.nspname = ? then case c.relkind when ? then ? when ? then ? when ? then ? else null end when n.nspname = ? then case c.relkind when ? then ? when ? then ? else null end else case c.relkind when ? then ? when ? then ? when ? then ? when ? then ? when ? then ? else null end end when false then case c.relkind when ? then ? when ? then ? when ? then ? when ? then ? when ? then ? when ? then ? when ? then ? when ? then ? else null end else null end as table_type, d.description as remarks, ? as type_cat, ? as type_schem, ? as type_name, ? as self_referencing_col_name, ? as ref_generation from pg_catalog.pg_namespace n, pg_catalog.pg_class c left join pg_catalog.pg_description d on (c.oid = d.objoid and d.objsubid = ?) left join pg_catalog.pg_class dc on (d.classoid = dc.oid and dc.relname = ?) left join pg_catalog.pg_namespace dn on (dn.oid = dc.relnamespace and dn.nspname = ?) where c.relnamespace = n.oid and c.relname like ? and (false or (c.relkind = ? and n.nspname !~ ? and n.nspname <> ?)) order by table_type, table_schem, table_name;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Sep 17 13 1,332 14ms 0ms [ User: postgres - Total duration: 14ms - Times executed: 1332 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14ms - Times executed: 1332 ]
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-09-17 13:14:01 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.164 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-09-17 13:14:19 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.164 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-09-17 13:14:06 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.164 Application: PostgreSQL JDBC Driver Bind query: yes
20 949 50ms 0ms 1ms 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, a.patternprice, atbaridentified as patternendtime, breakout, p.patternname, dtt.timezone, a.direction, case when a.patternclassid = ? then a.predictionpricefrom else a.patternprice end as predictionpricefrom, case when a.patternclassid = ? then a.predictionpriceto else a.patternprice end as predictionpriceto, s.timegranularity as interval, patternlengthbars as length, 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 left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Sep 17 13 949 50ms 0ms [ User: postgres - Total duration: 50ms - Times executed: 949 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 50ms - Times executed: 949 ]
-
SELECT CASE WHEN a.old_resultuid = '606824066162226303' THEN a.old_resultuid ELSE a.resultuid END AS ResultUID, s.symbol, a.patternprice, atbaridentified AS patternendtime, breakout, p.patternname, dtt.timezone, a.direction, case when a.patternclassid = 1 then a.predictionpricefrom else a.patternprice end as predictionpricefrom, case when a.patternclassid = 1 then a.predictionpriceto else a.patternprice end as predictionpriceto, s.timegranularity AS interval, patternlengthbars AS length, 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 LEFT JOIN currencypips cps on cps.symbol = s.symbol WHERE (a.old_resultuid = '606824066162226303' OR a.resultuid = '606824066162226303') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:06:00 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT CASE WHEN a.old_resultuid = '606828081586799303' THEN a.old_resultuid ELSE a.resultuid END AS ResultUID, s.symbol, a.patternprice, atbaridentified AS patternendtime, breakout, p.patternname, dtt.timezone, a.direction, case when a.patternclassid = 1 then a.predictionpricefrom else a.patternprice end as predictionpricefrom, case when a.patternclassid = 1 then a.predictionpriceto else a.patternprice end as predictionpriceto, s.timegranularity AS interval, patternlengthbars AS length, 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 LEFT JOIN currencypips cps on cps.symbol = s.symbol WHERE (a.old_resultuid = '606828081586799303' OR a.resultuid = '606828081586799303') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:10:00 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT CASE WHEN a.old_resultuid = '606828081657938303' THEN a.old_resultuid ELSE a.resultuid END AS ResultUID, s.symbol, a.patternprice, atbaridentified AS patternendtime, breakout, p.patternname, dtt.timezone, a.direction, case when a.patternclassid = 1 then a.predictionpricefrom else a.patternprice end as predictionpricefrom, case when a.patternclassid = 1 then a.predictionpriceto else a.patternprice end as predictionpriceto, s.timegranularity AS interval, patternlengthbars AS length, 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 LEFT JOIN currencypips cps on cps.symbol = s.symbol WHERE (a.old_resultuid = '606828081657938303' OR a.resultuid = '606828081657938303') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:52:35 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 14s863ms 21s786ms 17s782ms 4 1m11s select updateageforrelevantresults ();Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Sep 17 13 4 1m11s 17s782ms [ User: postgres - Total duration: 1m11s - Times executed: 4 ]
[ Application: psql - Total duration: 1m11s - Times executed: 4 ]
-
select updateageforrelevantresults ();
Date: 2025-09-17 13:17:24 Duration: 21s786ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-09-17 13:02:21 Duration: 19s235ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-09-17 13:47:18 Duration: 15s246ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
2 134ms 37s651ms 9s206ms 354 54m19s 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 Sep 17 13 354 54m19s 9s206ms [ User: postgres - Total duration: 54m19s - Times executed: 354 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 54m19s - Times executed: 354 ]
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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: 2025-09-17 13:00:13 Duration: 37s651ms 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: 2025-09-17 13:15:27 Duration: 37s281ms 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_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: 2025-09-17 13:05:52 Duration: 36s859ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
3 347ms 23s516ms 7s126ms 355 42m9s 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 Sep 17 13 355 42m9s 7s126ms [ User: postgres - Total duration: 42m9s - Times executed: 355 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 42m9s - Times executed: 355 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-09-17 13:06:22 Duration: 23s516ms 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 = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-09-17 13:11:10 Duration: 21s823ms 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 ('700' = 0 OR ar.patternlengthbars <= '700') 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: 2025-09-17 13:17:04 Duration: 20s931ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
4 5s186ms 6s851ms 5s596ms 6 33s577ms 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 Sep 17 13 6 33s577ms 5s596ms [ User: postgres - Total duration: 33s577ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 33s577ms - 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: 2025-09-17 13:00:09 Duration: 6s851ms 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: 2025-09-17 13:30:07 Duration: 5s397ms 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: 2025-09-17 13:50:08 Duration: 5s397ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
5 2s971ms 3s921ms 3s214ms 8 25s719ms select updateresultsmaterializedview ();Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Sep 17 13 8 25s719ms 3s214ms [ User: postgres - Total duration: 25s719ms - Times executed: 8 ]
[ Application: psql - Total duration: 25s719ms - Times executed: 8 ]
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select updateresultsmaterializedview ();
Date: 2025-09-17 13:17:28 Duration: 3s921ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-09-17 13:02:25 Duration: 3s306ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-09-17 13:47:21 Duration: 3s274ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
6 571ms 9s181ms 3s121ms 289 15m2s 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 #6
Day Hour Count Duration Avg duration Sep 17 13 289 15m2s 3s121ms [ User: postgres - Total duration: 15m2s - Times executed: 289 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 15m2s - Times executed: 289 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR fr.pattern in ('')) AND ('0' = 0 OR fr.patternlengthbars <= '0') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-09-17 13:06:32 Duration: 9s181ms 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 ('700' = 0 OR fr.patternlengthbars <= '700') 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: 2025-09-17 13:17:08 Duration: 8s958ms 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 ('700' = 0 OR fr.patternlengthbars <= '700') 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: 2025-09-17 13:02:02 Duration: 8s699ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
7 2s50ms 3s634ms 2s441ms 16 39s61ms 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 #7
Day Hour Count Duration Avg duration Sep 17 13 16 39s61ms 2s441ms [ User: postgres - Total duration: 39s61ms - Times executed: 16 ]
[ Application: psql - Total duration: 39s61ms - 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: 2025-09-17 13:01:17 Duration: 3s634ms 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: 2025-09-17 13:11:17 Duration: 3s551ms 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: 2025-09-17 13:26:17 Duration: 3s529ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
8 19ms 16s668ms 1s392ms 34 47s352ms select fixcandlegaps (?, false);Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Sep 17 13 34 47s352ms 1s392ms [ User: postgres - Total duration: 47s352ms - Times executed: 34 ]
[ Application: psql - Total duration: 47s352ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-09-17 13:06:49 Duration: 16s668ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-09-17 13:06:12 Duration: 5s543ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('PEPPERSTONE', false);
Date: 2025-09-17 13:06:25 Duration: 4s882ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
9 1s22ms 1s773ms 1s389ms 6 8s338ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Sep 17 13 6 8s338ms 1s389ms [ User: postgres - Total duration: 8s338ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 8s338ms - Times executed: 6 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-09-17 13:46:18 Duration: 1s773ms 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: 2025-09-17 13:01:18 Duration: 1s671ms 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: 2025-09-17 13:31:18 Duration: 1s665ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
10 1s269ms 1s303ms 1s287ms 16 20s597ms 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 Sep 17 13 16 20s597ms 1s287ms [ User: postgres - Total duration: 20s597ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 20s597ms - 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 = '620' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '620' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '620' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-09-17 13:21:44 Duration: 1s303ms 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 = '620' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '620' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '620' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-09-17 13:36:41 Duration: 1s302ms 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: 2025-09-17 13:06:58 Duration: 1s298ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
11 817ms 1s944ms 1s225ms 16 19s609ms update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Sep 17 13 16 19s609ms 1s225ms [ User: postgres - Total duration: 19s609ms - Times executed: 16 ]
[ Application: psql - Total duration: 19s609ms - 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: 2025-09-17 13:11:13 Duration: 1s944ms 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: 2025-09-17 13:01:13 Duration: 1s792ms 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: 2025-09-17 13:16:13 Duration: 1s449ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
12 33ms 1s173ms 357ms 187 1m6s 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 Sep 17 13 187 1m6s 357ms [ User: postgres - Total duration: 1m6s - Times executed: 187 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m6s - Times executed: 187 ]
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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 ('700' = 0 OR ccr.patternlengthbars <= '700') ), 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: 2025-09-17 13:25:54 Duration: 1s173ms 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 ('700' = 0 OR ccr.patternlengthbars <= '700') ), 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: 2025-09-17 13:17:27 Duration: 1s16ms 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 ('700' = 0 OR ccr.patternlengthbars <= '700') ), 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: 2025-09-17 13:26:02 Duration: 1s12ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
13 91ms 1s15ms 343ms 114 39s209ms 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 Sep 17 13 114 39s209ms 343ms [ User: postgres - Total duration: 39s209ms - Times executed: 114 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 39s209ms - Times executed: 114 ]
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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: 2025-09-17 13:16:01 Duration: 1s15ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-09-17 13:52:01 Duration: 916ms 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: 2025-09-17 13:12:01 Duration: 877ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
14 17ms 405ms 106ms 158 16s771ms select distinct k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid from relevance_keylevels_results p inner join keylevels_results k on p.resultuid = k.resultuid inner join autochartist_stocklist asl on k.symbolid = asl.symbolid where k.patternclassid in (...) and asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Sep 17 13 158 16s771ms 106ms [ User: postgres - Total duration: 16s771ms - Times executed: 158 ]
[ Application: [unknown] - Total duration: 16s771ms - Times executed: 158 ]
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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 'PEPPERSTONE - 1';
Date: 2025-09-17 13:06:42 Duration: 405ms 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 'IQFEED_FX - 1';
Date: 2025-09-17 13:00:04 Duration: 348ms 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 'PEPPERSTONE - 1';
Date: 2025-09-17 13:02:04 Duration: 281ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
15 16ms 327ms 78ms 158 12s351ms 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 Sep 17 13 158 12s351ms 78ms [ User: postgres - Total duration: 12s351ms - Times executed: 158 ]
[ Application: [unknown] - Total duration: 12s351ms - Times executed: 158 ]
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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: 2025-09-17 13:06:29 Duration: 327ms 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: 2025-09-17 13:45:57 Duration: 280ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2025-09-17 13:00:55 Duration: 272ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
16 0ms 32ms 2ms 4,677 12s154ms with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ) select a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, s.exchange, s.symbol, s.longname, s.shortname, breakout, dtt.timezone, patternstartprice, patternendprice, qtytp, newlevels.profit, newlevels.stop, newlevels.filtered, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern inner join rar_max rm on ? = ? left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid left join lateral calc_cp_signal (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Sep 17 13 4,677 12s154ms 2ms [ User: postgres - Total duration: 12s154ms - Times executed: 4677 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12s154ms - Times executed: 4677 ]
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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 = '606827372930462301' 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 = '606827372930462301' OR a.resultuid = '606827372930462301') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:25:48 Duration: 32ms 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 = '606828085908377301' 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 = '606828085908377301' OR a.resultuid = '606828085908377301') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:56:56 Duration: 28ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ) SELECT a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, CASE WHEN a.old_resultuid = '606790819861944301' 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 = '606790819861944301' OR a.resultuid = '606790819861944301') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:25:48 Duration: 26ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
17 0ms 25ms 2ms 14,478 30s450ms 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 Sep 17 13 14,478 30s450ms 2ms [ User: postgres - Total duration: 30s450ms - Times executed: 14478 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 30s450ms - Times executed: 14478 ]
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'SGDJPY' OR dss.downloadersymbol = 'SGDJPY') AND dss.enabled = 1;
Date: 2025-09-17 13:00:04 Duration: 25ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'JP225' OR dss.downloadersymbol = 'JP225') AND dss.enabled = 1;
Date: 2025-09-17 13:00:04 Duration: 20ms 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 = 'USDSGD' OR dss.downloadersymbol = 'USDSGD') AND dss.enabled = 1;
Date: 2025-09-17 13:00:04 Duration: 17ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
18 0ms 9ms 1ms 1,602 2s930ms 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 #18
Day Hour Count Duration Avg duration Sep 17 13 1,602 2s930ms 1ms [ User: postgres - Total duration: 2s930ms - Times executed: 1602 ]
[ Application: [unknown] - Total duration: 2s930ms - Times executed: 1602 ]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, - 1, 1, '2025-09-17 11:10:42'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 25, 66.439999999999997720000000000000, '2025-09-17 06:30:00', '2025-09-17 04:30:00', '2025-09-16 09:30:00', '', '', '', '', '', '', '', 50, 66.460499999999996140000000000000, '2025-09-17 06:30:00'::timestamp without time zone, '2025-09-17 06:30:00', 0.000000000000000000000000000000, 0.020499999999999830860000000000, - 1, 515840249537406300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249537406300|66.44|1|2025-09-17 06:30:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-09-16 09:30:00', 66.510000000000005120000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-09-17 13:15:56 Duration: 9ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (3.000000000000000000000000000000, - 1, 2, '2025-09-17 10:55:51'::timestamp without time zone, '2025-09-17 13:00:00', 0.001315000000000018411000000000, 4, 108, 0.916259999999999963400000000000, '2025-09-16 17:00:00', '2025-09-11 12:00:00', '2025-09-11 04:00:00', '2025-09-11 00:00:00', '', '', '', '', '', '', 220, 0.915926499999999976800000000000, '2025-09-17 13:00:00'::timestamp without time zone, '2025-09-17 13:00:00', 0.917455000000000020500000000000, 0.000391750000000002014200000000, - 1, 515840230419498300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840230419498300|0.91626|2|2025-09-17 13:00:00|2025-09-17 13:00:00|-1|-1', 0.918074700000000021300000000000, 0.001814700000000057933000000000, 2, '2025-09-11 00:00:00', 0.919080000000000008000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-09-17 13:01:05 Duration: 9ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (3.000000000000000000000000000000, - 1, 2, '2025-09-17 10:55:45'::timestamp without time zone, '2025-09-17 13:00:00', 0.001449999999999989058000000000, 4, 105, 0.915930000000000021900000000000, '2025-09-16 15:00:00', '2025-09-11 15:00:00', '2025-09-11 09:00:00', '2025-09-11 04:00:00', '', '', '', '', '', '', 207, 0.915602499999999985800000000000, '2025-09-17 13:00:00'::timestamp without time zone, '2025-09-17 13:00:00', 0.917329999999999978800000000000, 0.000334499999999999023400000000, - 1, 515840243909699300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840243909699300|0.91593|2|2025-09-17 13:00:00|2025-09-17 13:00:00|-1|-1', 0.917931000000000052400000000000, 0.002001000000000030532000000000, 2, '2025-09-11 04:00:00', 0.918959999999999999100000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-09-17 13:00:59 Duration: 8ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
19 0ms 21ms 1ms 38,563 55s775ms 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 Sep 17 13 38,563 55s775ms 1ms [ User: postgres - Total duration: 55s775ms - Times executed: 38563 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 55s775ms - Times executed: 38563 ]
-
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 = '515840249435063300';
Date: 2025-09-17 13:00:04 Duration: 21ms 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 = '958' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '958' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840248627808300';
Date: 2025-09-17 13:15:49 Duration: 19ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 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 = '958' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '958' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840216981120300';
Date: 2025-09-17 13:06:00 Duration: 18ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
20 0ms 19ms 1ms 3,138 3s832ms 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 #20
Day Hour Count Duration Avg duration Sep 17 13 3,138 3s832ms 1ms [ User: postgres - Total duration: 3s832ms - Times executed: 3138 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s832ms - Times executed: 3138 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '606827844950313303' 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 = '606827844950313303' OR a.resultuid = '606827844950313303') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:44:53 Duration: 19ms 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_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '606827614577157303' 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 = '606827614577157303' OR a.resultuid = '606827614577157303') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:01:59 Duration: 19ms 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_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '606828089078013303' 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 = '606828089078013303' OR a.resultuid = '606828089078013303') AND dtt.dayofweek = 3;
Date: 2025-09-17 13:41:51 Duration: 19ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 16s418ms 17,358 0ms 17ms 0ms SELECT ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Sep 17 13 17,358 16s418ms 0ms [ User: postgres - Total duration: 32s163ms - Times executed: 17358 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 32s163ms - Times executed: 17358 ]
-
SELECT ;
Date: 2025-09-17 13:16:29 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
SELECT ;
Date: 2025-09-17 13:06:00 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
SELECT ;
Date: 2025-09-17 13:15:17 Duration: 15ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
2 9s965ms 7,820 0ms 23ms 1ms WITH rar_max as ( ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 13 7,820 9s965ms 1ms [ User: postgres - Total duration: 1h42m23s - Times executed: 7820 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h42m23s - Times executed: 7820 ]
-
WITH rar_max as ( ;
Date: 2025-09-17 13:31:50 Duration: 23ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
WITH rar_max as ( ;
Date: 2025-09-17 13:15:49 Duration: 22ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
WITH rar_max as ( ;
Date: 2025-09-17 13:02:05 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
3 1s431ms 10,304 0ms 20ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 13 10,304 1s431ms 0ms [ User: postgres - Total duration: 101ms - Times executed: 10304 ]
[ Application: [unknown] - Total duration: 101ms - Times executed: 10304 ]
-
SET extra_float_digits = 3;
Date: 2025-09-17 13:26:48 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
SET extra_float_digits = 3;
Date: 2025-09-17 13:07:39 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
SET extra_float_digits = 3;
Date: 2025-09-17 13:51:54 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
4 1s92ms 17,103 0ms 9ms 0ms select 1;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 13 17,103 1s92ms 0ms [ User: postgres - Total duration: 74ms - Times executed: 17103 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 74ms - Times executed: 17103 ]
-
select 1;
Date: 2025-09-17 13:36:21 Duration: 9ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
select 1;
Date: 2025-09-17 13:26:49 Duration: 8ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
select 1;
Date: 2025-09-17 13:04:52 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
5 805ms 626 0ms 10ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 13 626 805ms 1ms [ User: postgres - Total duration: 946ms - Times executed: 626 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 946ms - Times executed: 626 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-09-17 13:15:53 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-09-17 13:00:26 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-09-17 13:16:25 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
6 527ms 1,136 0ms 2ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #6
Day Hour Count Duration Avg duration 13 1,136 527ms 0ms [ User: postgres - Total duration: 3s628ms - Times executed: 1136 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s628ms - Times executed: 1136 ]
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-09-17 13:16:25 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-09-17 13:16:29 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-09-17 13:16:37 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
7 331ms 3,294 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 13 3,294 331ms 0ms [ User: postgres - Total duration: 1s742ms - Times executed: 3294 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s742ms - Times executed: 3294 ]
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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: 2025-09-17 13:00:44 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-09-17 13:00:50 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-09-17 13:01:43 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
8 255ms 2,080 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 13 2,080 255ms 0ms [ User: postgres - Total duration: 936ms - Times executed: 2080 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 936ms - Times executed: 2080 ]
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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: 2025-09-17 13:01:55 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-09-17 13:01:43 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-09-17 13:01:59 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
9 235ms 1,332 0ms 0ms 0ms SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 13 1,332 235ms 0ms [ User: postgres - Total duration: 14ms - Times executed: 1332 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14ms - Times executed: 1332 ]
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-09-17 13:14:20 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.164
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-09-17 13:13:48 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.164
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-09-17 13:14:00 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.164
10 144ms 10,278 0ms 6ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 13 10,278 144ms 0ms [ User: postgres - Total duration: 118ms - Times executed: 10278 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 118ms - Times executed: 10278 ]
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-09-17 13:56:26 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-09-17 13:50:54 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-09-17 13:13:48 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
11 101ms 16 4ms 7ms 6ms with sym_info as ( ;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 13 16 101ms 6ms [ User: postgres - Total duration: 20s597ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 20s597ms - Times executed: 16 ]
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with sym_info as ( ;
Date: 2025-09-17 13:06:57 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
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with sym_info as ( ;
Date: 2025-09-17 13:51:44 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
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with sym_info as ( ;
Date: 2025-09-17 13:06:44 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
12 68ms 492 0ms 0ms 0ms select category, ;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 13 492 68ms 0ms [ User: postgres - Total duration: 47ms - Times executed: 492 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 47ms - Times executed: 492 ]
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select category, ;
Date: 2025-09-17 13:26:30 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
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select category, ;
Date: 2025-09-17 13:43:25 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.54
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select category, ;
Date: 2025-09-17 13:22:35 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
13 61ms 53 0ms 3ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 13 53 61ms 1ms [ User: postgres - Total duration: 21s349ms - Times executed: 53 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 21s349ms - Times executed: 53 ]
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WITH last_candle AS ( ;
Date: 2025-09-17 13:45:03 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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WITH last_candle AS ( ;
Date: 2025-09-17 13:32:01 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
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WITH last_candle AS ( ;
Date: 2025-09-17 13:04:00 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
14 53ms 116 0ms 3ms 0ms WITH pre_symbols AS ( /* find relevant symbols */ ;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 13 116 53ms 0ms [ User: postgres - Total duration: 2s27ms - Times executed: 116 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s27ms - Times executed: 116 ]
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WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-09-17 13:13:48 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.164
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WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-09-17 13:13:48 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.164
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WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-09-17 13:14:41 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.164
15 47ms 18 2ms 3ms 2ms select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;Times Reported Time consuming prepare #15
Day Hour Count Duration Avg duration 13 18 47ms 2ms [ User: postgres - Total duration: 30ms - Times executed: 18 ]
[ Application: [unknown] - Total duration: 30ms - 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: 2025-09-17 13:01:15 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
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select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-09-17 13:11:01 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: 2025-09-17 13:01:15 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
16 37ms 19 1ms 6ms 1ms with wh_patitioned as ( ;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 13 19 37ms 1ms [ User: postgres - Total duration: 857ms - Times executed: 19 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 857ms - Times executed: 19 ]
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with wh_patitioned as ( ;
Date: 2025-09-17 13:26:41 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
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with wh_patitioned as ( ;
Date: 2025-09-17 13:52:21 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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with wh_patitioned as ( ;
Date: 2025-09-17 13:22:29 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.135
17 33ms 24 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 #17
Day Hour Count Duration Avg duration 13 24 33ms 1ms [ User: postgres - Total duration: 93ms - Times executed: 24 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 93ms - Times executed: 24 ]
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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: 2025-09-17 13:51:51 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: 2025-09-17 13:01:44 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: 2025-09-17 13:01:20 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
18 26ms 24 0ms 4ms 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 #18
Day Hour Count Duration Avg duration 13 24 26ms 1ms [ User: postgres - Total duration: 35ms - Times executed: 24 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 35ms - Times executed: 24 ]
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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: 2025-09-17 13:46:24 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
-
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: 2025-09-17 13:01:44 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
-
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: 2025-09-17 13:01:20 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
19 19ms 6 2ms 3ms 3ms select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 13 6 19ms 3ms [ User: postgres - Total duration: 11ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 11ms - Times executed: 6 ]
-
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: 2025-09-17 13:40:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
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: 2025-09-17 13:10:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
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: 2025-09-17 13:20:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
20 17ms 6 2ms 3ms 2ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 13 6 17ms 2ms [ User: postgres - Total duration: 33s577ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 33s577ms - Times executed: 6 ]
-
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: 2025-09-17 13:20:02 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
-
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: 2025-09-17 13:00:02 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
-
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: 2025-09-17 13:40:02 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 1m6s 9,492 0ms 71ms 7ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Sep 17 13 9,492 1m6s 7ms [ User: postgres - Total duration: 1h52m21s - Times executed: 9492 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h52m21s - Times executed: 9492 ]
-
WITH rar_max as ( ;
Date: 2025-09-17 13:28:19 Duration: 71ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '606824610493816303', $2 = '606824610493816303', $3 = '606824610493816303'
-
WITH rar_max as ( ;
Date: 2025-09-17 13:25:54 Duration: 63ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '689', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '310', $13 = '#AAPL', $14 = '#ADS', $15 = '#AIG', $16 = '#ALV', $17 = '#AMZN', $18 = '#AXP', $19 = '#BA', $20 = '#BABA', $21 = '#BAC', $22 = '#BAS', $23 = '#BAYN', $24 = '#BEI', $25 = '#BIDU', $26 = '#BMW', $27 = '#C', $28 = '#CAT', $29 = '#CBK', $30 = '#CL', $31 = '#CSCO', $32 = '#CVX', $33 = '#DAI', $34 = '#DB1', $35 = '#DBK', $36 = '#DIS', $37 = '#DPW', $38 = '#DTE', $39 = '#EBAY', $40 = '#EON', $41 = '#F', $42 = '#FB', $43 = '#FDX', $44 = '#FME', $45 = '#GE', $46 = '#GM', $47 = '#GOOG', $48 = '#GS', $49 = '#HPQ', $50 = '#IBM', $51 = '#IFX', $52 = '#INTC', $53 = '#JD', $54 = '#JNJ', $55 = '#JPM', $56 = '#KO', $57 = '#LHA', $58 = '#LMT', $59 = '#MA', $60 = '#MCD', $61 = '#META', $62 = '#MMM', $63 = '#MSFT', $64 = '#MUV2', $65 = '#NFLX', $66 = '#NKE', $67 = '#NTES', $68 = '#ORCL', $69 = '#PFE', $70 = '#PG', $71 = '#QCOM', $72 = '#RACE', $73 = '#RWE', $74 = '#SAP', $75 = '#SIE', $76 = '#T', $77 = '#UBER', $78 = '#V', $79 = '#VOW', $80 = '#WB', $81 = '#XOM', $82 = 'AUDCAD', $83 = 'AUDCHF', $84 = 'AUDJPY', $85 = 'AUDNZD', $86 = 'AUDUSD', $87 = 'AUS200', $88 = 'BRENT', $89 = 'BTCUSD', $90 = 'CADCHF', $91 = 'CADJPY', $92 = 'CHFJPY', $93 = 'CHI50', $94 = 'ESP35', $95 = 'ETHUSD', $96 = 'EU50', $97 = 'EURAUD', $98 = 'EURCAD', $99 = 'EURCHF', $100 = 'EURGBP', $101 = 'EURHUF', $102 = 'EURJPY', $103 = 'EURNZD', $104 = 'EURPLN', $105 = 'EURUSD', $106 = 'FRA40', $107 = 'GBPAUD', $108 = 'GBPCAD', $109 = 'GBPCHF', $110 = 'GBPJPY', $111 = 'GBPNZD', $112 = 'GBPUSD', $113 = 'GER30', $114 = 'HK50', $115 = 'HKCH50', $116 = 'IT40', $117 = 'JP225', $118 = 'LTCUSD', $119 = 'NAS100', $120 = 'NZDCAD', $121 = 'NZDCHF', $122 = 'NZDJPY', $123 = 'NZDUSD', $124 = 'SPX500', $125 = 'UK100', $126 = 'US30', $127 = 'USDCAD', $128 = 'USDCHF', $129 = 'USDCNH', $130 = 'USDCZK', $131 = 'USDDKK', $132 = 'USDHKD', $133 = 'USDHUF', $134 = 'USDJPY', $135 = 'USDMXN', $136 = 'USDNOK', $137 = 'USDPLN', $138 = 'USDSEK', $139 = 'USDSGD', $140 = 'USDTRY', $141 = 'USDX', $142 = 'USDZAR', $143 = 'WTI', $144 = 'XAGUSD', $145 = 'XAUUSD', $146 = '#ADS', $147 = '#ALV', $148 = '#BAS', $149 = '#BAYN', $150 = '#BEI', $151 = '#BMW', $152 = '#CBK', $153 = '#DAI', $154 = '#DB1', $155 = '#DBK', $156 = '#DPW', $157 = '#DTE', $158 = '#EON', $159 = '#FME', $160 = '#IFX', $161 = '#LHA', $162 = '#MUV2', $163 = '#RWE', $164 = '#SAP', $165 = '#SIE', $166 = '#VOW', $167 = 'AUDCAD', $168 = 'AUDCHF', $169 = 'AUDJPY', $170 = 'AUDNZD', $171 = 'AUDUSD', $172 = 'CADCHF', $173 = 'CADJPY', $174 = 'CHFJPY', $175 = 'EURAUD', $176 = 'EURCAD', $177 = 'EURCHF', $178 = 'EURGBP', $179 = 'EURHUF', $180 = 'EURJPY', $181 = 'EURNZD', $182 = 'EURPLN', $183 = 'EURUSD', $184 = 'GBPAUD', $185 = 'GBPCAD', $186 = 'GBPCHF', $187 = 'GBPJPY', $188 = 'GBPNZD', $189 = 'GBPUSD', $190 = 'NZDCAD', $191 = 'NZDCHF', $192 = 'NZDJPY', $193 = 'NZDUSD', $194 = 'USDCAD', $195 = 'USDCHF', $196 = 'USDCNH', $197 = 'USDCZK', $198 = 'USDDKK', $199 = 'USDHKD', $200 = 'USDHUF', $201 = 'USDJPY', $202 = 'USDMXN', $203 = 'USDNOK', $204 = 'USDPLN', $205 = 'USDSEK', $206 = 'USDSGD', $207 = 'USDTRY', $208 = 'USDX', $209 = 'USDZAR', $210 = 'XAGUSD', $211 = 'XAUUSD', $212 = 'BTCUSD', $213 = 'ETHUSD', $214 = 'LTCUSD', $215 = 'AUDCAD', $216 = 'AUDCHF', $217 = 'AUDJPY', $218 = 'AUDNZD', $219 = 'CADCHF', $220 = 'CADJPY', $221 = 'CHFJPY', $222 = 'EURAUD', $223 = 'EURCAD', $224 = 'EURCHF', $225 = 'EURGBP', $226 = 'EURHUF', $227 = 'EURJPY', $228 = 'EURNZD', $229 = 'EURPLN', $230 = 'GBPAUD', $231 = 'GBPCAD', $232 = 'GBPCHF', $233 = 'GBPJPY', $234 = 'GBPNZD', $235 = 'NZDCAD', $236 = 'NZDCHF', $237 = 'NZDJPY', $238 = 'USDCNH', $239 = 'USDCZK', $240 = 'USDDKK', $241 = 'USDHKD', $242 = 'USDHUF', $243 = 'USDMXN', $244 = 'USDNOK', $245 = 'USDPLN', $246 = 'USDSEK', $247 = 'USDSGD', $248 = 'USDTRY', $249 = 'USDX', $250 = 'USDZAR', $251 = 'XAGUSD', $252 = 'XAUUSD', $253 = 'BRENT', $254 = 'WTI', $255 = 'AUS200', $256 = 'CHI50', $257 = 'ESP35', $258 = 'EU50', $259 = 'FRA40', $260 = 'GER30', $261 = 'HK50', $262 = 'HKCH50', $263 = 'IT40', $264 = 'JP225', $265 = 'NAS100', $266 = 'SPX500', $267 = 'UK100', $268 = 'US30', $269 = 'AUDUSD', $270 = 'EURUSD', $271 = 'GBPUSD', $272 = 'NZDUSD', $273 = 'USDCAD', $274 = 'USDCHF', $275 = 'USDJPY', $276 = '#AAPL', $277 = '#AIG', $278 = '#AMZN', $279 = '#AXP', $280 = '#BA', $281 = '#BABA', $282 = '#BAC', $283 = '#BIDU', $284 = '#C', $285 = '#CAT', $286 = '#CL', $287 = '#CSCO', $288 = '#CVX', $289 = '#DIS', $290 = '#EBAY', $291 = '#F', $292 = '#FB', $293 = '#FDX', $294 = '#GE', $295 = '#GM', $296 = '#GOOG', $297 = '#GS', $298 = '#HPQ', $299 = '#IBM', $300 = '#INTC', $301 = '#JD', $302 = '#JNJ', $303 = '#JPM', $304 = '#KO', $305 = '#LMT', $306 = '#MA', $307 = '#MCD', $308 = '#MMM', $309 = '#MSFT', $310 = '#NFLX', $311 = '#NKE', $312 = '#NTES', $313 = '#ORCL', $314 = '#PFE', $315 = '#PG', $316 = '#QCOM', $317 = '#RACE', $318 = '#T', $319 = '#UBER', $320 = '#V', $321 = '#WB', $322 = '#XOM', $323 = '700', $324 = '700', $325 = 't', $326 = '10', $327 = '10'
-
WITH rar_max as ( ;
Date: 2025-09-17 13:28:19 Duration: 52ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '606824775853333301', $2 = '606824775853333301', $3 = '606824775853333301'
2 45s329ms 60,132 0ms 30ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 13 60,132 45s329ms 0ms [ User: postgres - Total duration: 1m33s - Times executed: 60132 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m33s - Times executed: 60132 ]
-
SELECT ;
Date: 2025-09-17 13:04:52 Duration: 30ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '958', $2 = '958', $3 = '515840249414067300'
-
SELECT ;
Date: 2025-09-17 13:15:19 Duration: 30ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '958', $2 = '958', $3 = '515840216981120300'
-
SELECT ;
Date: 2025-09-17 13:04:52 Duration: 28ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '958', $2 = '958', $3 = '515840248627636300'
3 1s324ms 62,735 0ms 8ms 0ms select 1;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 13 62,735 1s324ms 0ms [ User: postgres - Total duration: 255ms - Times executed: 62735 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 255ms - Times executed: 62694 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 41 ]
-
select 1;
Date: 2025-09-17 13:51:54 Duration: 8ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
select 1;
Date: 2025-09-17 13:17:30 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
select 1;
Date: 2025-09-17 13:45:54 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
4 1s208ms 626 1ms 10ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 13 626 1s208ms 1ms [ User: postgres - Total duration: 946ms - Times executed: 626 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 946ms - Times executed: 626 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-09-17 13:16:03 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'GLOBALGTMT5'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-09-17 13:00:26 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'Alpari'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-09-17 13:00:50 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'MILLENNIUMPF'
5 821ms 114 4ms 24ms 7ms WITH last_candle AS ( ;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 13 114 821ms 7ms [ User: postgres - Total duration: 39s209ms - Times executed: 114 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 39s209ms - Times executed: 114 ]
-
WITH last_candle AS ( ;
Date: 2025-09-17 13:16:00 Duration: 24ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2025-09-17 13:36:08 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '667', $2 = '667'
-
WITH last_candle AS ( ;
Date: 2025-09-17 13:16:00 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '558'
6 650ms 22 16ms 53ms 29ms with wh_patitioned as ( ;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 13 22 650ms 29ms [ User: postgres - Total duration: 1s5ms - Times executed: 22 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s5ms - Times executed: 22 ]
-
with wh_patitioned as ( ;
Date: 2025-09-17 13:26:41 Duration: 53ms 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: 2025-09-17 13:16:37 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: 2025-09-17 13:11:00 Duration: 47ms 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'
7 607ms 1,332 0ms 2ms 0ms SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 13 1,332 607ms 0ms [ User: postgres - Total duration: 14ms - Times executed: 1332 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14ms - Times executed: 1332 ]
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-09-17 13:13:48 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.164
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-09-17 13:14:01 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.164
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-09-17 13:13:48 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.164
8 592ms 127 0ms 21ms 4ms select distinct s.statsid as statsid, sy.exchange as name;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 13 127 592ms 4ms [ User: postgres - Total duration: 373ms - Times executed: 127 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 373ms - Times executed: 127 ]
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2025-09-17 13:26:30 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '489', $2 = '489'
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2025-09-17 13:52:11 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.54 parameters: $1 = '538', $2 = '538'
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2025-09-17 13:50:20 Duration: 16ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.54 parameters: $1 = '529', $2 = '529'
9 590ms 16 28ms 45ms 36ms with sym_info as ( ;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 13 16 590ms 36ms [ User: postgres - Total duration: 20s597ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 20s597ms - Times executed: 16 ]
-
with sym_info as ( ;
Date: 2025-09-17 13:06:47 Duration: 45ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '617', $2 = 'Forex', $3 = 'Forex', $4 = '617', $5 = 'Forex', $6 = '617', $7 = '617', $8 = 'Forex', $9 = '617'
-
with sym_info as ( ;
Date: 2025-09-17 13:06:57 Duration: 45ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'
-
with sym_info as ( ;
Date: 2025-09-17 13:06:44 Duration: 44ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
10 543ms 6,173 0ms 4ms 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 #10
Day Hour Count Duration Avg duration 13 6,173 543ms 0ms [ User: postgres - Total duration: 6s364ms - Times executed: 6173 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 6s364ms - Times executed: 6173 ]
-
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: 2025-09-17 13:16:39 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-09-17 14:00:00', $2 = '1.183685', $3 = '1.184305', $4 = '1.183635', $5 = '1.184105', $6 = '457', $7 = '515840230473074300', $8 = '0', $9 = '2025-09-17 13:16:39.592', $10 = '2025-09-17 13:16:39.538', $11 = '1.183685', $12 = '1.184305', $13 = '1.183635', $14 = '1.184105', $15 = '457', $16 = '0', $17 = '2025-09-17 13:16:39.592', $18 = '2025-09-17 13:16:39.538'
-
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: 2025-09-17 13:15:59 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-09-17 14:00:00', $2 = '85.85', $3 = '85.86', $4 = '85.82', $5 = '85.82', $6 = '6', $7 = '515840233329477300', $8 = '0', $9 = '2025-09-17 13:15:59.238', $10 = '2025-09-17 13:15:59.097', $11 = '85.85', $12 = '85.86', $13 = '85.82', $14 = '85.82', $15 = '6', $16 = '0', $17 = '2025-09-17 13:15:59.239', $18 = '2025-09-17 13:15:59.097'
-
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: 2025-09-17 13:15:54 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-09-17 14:00:00', $2 = '0.47001', $3 = '0.47016', $4 = '0.46996', $5 = '0.47014', $6 = '316', $7 = '515840217506064300', $8 = '0', $9 = '2025-09-17 13:15:54.292', $10 = '2025-09-17 13:15:53.625', $11 = '0.47001', $12 = '0.47016', $13 = '0.46996', $14 = '0.47014', $15 = '316', $16 = '0', $17 = '2025-09-17 13:15:54.292', $18 = '2025-09-17 13:15:53.625'
11 485ms 36 9ms 20ms 13ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #11
Day Hour Count Duration Avg duration 13 36 485ms 13ms [ User: postgres - Total duration: 0ms - Times executed: 36 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 0ms - Times executed: 36 ]
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-09-17 13:50:50 Duration: 20ms 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: 2025-09-17 13:10:23 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-09-17 13:21:35 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'
12 440ms 116 0ms 33ms 3ms WITH pre_symbols AS ( /* find relevant symbols */ ;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 13 116 440ms 3ms [ User: postgres - Total duration: 2s27ms - Times executed: 116 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s27ms - Times executed: 116 ]
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-09-17 13:14:41 Duration: 33ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.164 parameters: $1 = '972', $2 = 'ICMARKETS-AU-MT5', $3 = 'AUDSGD', $4 = 'CHFSGD', $5 = 'EURDKK', $6 = 'EURHKD', $7 = 'EURNOK', $8 = 'EURPLN', $9 = 'EURSEK', $10 = 'EURSGD', $11 = 'EURTRY', $12 = 'EURZAR', $13 = 'GBPDKK', $14 = 'GBPNOK', $15 = 'GBPSEK', $16 = 'GBPSGD', $17 = 'NOKJPY', $18 = 'NOKSEK', $19 = 'SEKJPY', $20 = 'SGDJPY', $21 = 'USDCNH', $22 = 'USDCZK', $23 = 'USDDKK', $24 = 'USDHKD', $25 = 'USDHUF', $26 = 'USDMXN', $27 = 'USDNOK', $28 = 'USDPLN', $29 = 'USDRUB', $30 = 'USDSEK', $31 = 'USDTHB', $32 = 'USDTRY', $33 = 'USDZAR', $34 = 'AUDUSD', $35 = 'EURUSD', $36 = 'GBPUSD', $37 = 'USDCAD', $38 = 'USDCHF', $39 = 'USDJPY', $40 = 'AUDCAD', $41 = 'AUDCHF', $42 = 'AUDJPY', $43 = 'AUDNZD', $44 = 'CADCHF', $45 = 'CADJPY', $46 = 'CHFJPY', $47 = 'EURAUD', $48 = 'EURCAD', $49 = 'EURCHF', $50 = 'EURGBP', $51 = 'EURJPY', $52 = 'EURNZD', $53 = 'GBPAUD', $54 = 'GBPCAD', $55 = 'GBPCHF', $56 = 'GBPJPY', $57 = 'GBPNZD', $58 = 'NZDCAD', $59 = 'NZDCHF', $60 = 'NZDJPY', $61 = 'NZDUSD', $62 = 'USDSGD', $63 = 'AUS200', $64 = 'CHINA50', $65 = 'DE30', $66 = 'ES35', $67 = 'F40', $68 = 'HK50', $69 = 'IT40', $70 = 'JP225', $71 = 'STOXX50', $72 = 'UK100', $73 = 'US2000', $74 = 'US30', $75 = 'US500', $76 = 'USTEC', $77 = 'XAGEUR', $78 = 'XAGUSD', $79 = 'XAUEUR', $80 = 'XAUUSD', $81 = 'XPDUSD', $82 = 'XPTUSD', $83 = 'XBRUSD', $84 = 'XNGUSD', $85 = 'XTIUSD', $86 = 'BTCUSD', $87 = 'BRENT_F0', $88 = 'BRENT_F1', $89 = 'BRENT_F2', $90 = 'BRENT_F3', $91 = 'BRENT_F4', $92 = 'BRENT_F5', $93 = 'BRENT_F6', $94 = 'BRENT_F7', $95 = 'BRENT_F8', $96 = 'BRENT_F9', $97 = 'BRENT_G0', $98 = 'BRENT_G1', $99 = 'BRENT_G2', $100 = 'BRENT_G3', $101 = 'BRENT_G4', $102 = 'BRENT_G5', $103 = 'BRENT_G6', $104 = 'BRENT_G7', $105 = 'BRENT_G8', $106 = 'BRENT_G9', $107 = 'BRENT_H0', $108 = 'BRENT_H1', $109 = 'BRENT_H2', $110 = 'BRENT_H3', $111 = 'BRENT_H4', $112 = 'BRENT_H5', $113 = 'BRENT_H6', $114 = 'BRENT_H7', $115 = 'BRENT_H8', $116 = 'BRENT_H9', $117 = 'BRENT_J0', $118 = 'BRENT_J1', $119 = 'BRENT_J2', $120 = 'BRENT_J3', $121 = 'BRENT_J4', $122 = 'BRENT_J5', $123 = 'BRENT_J6', $124 = 'BRENT_J7', $125 = 'BRENT_J8', $126 = 'BRENT_J9', $127 = 'BRENT_K0', $128 = 'BRENT_K1', $129 = 'BRENT_K2', $130 = 'BRENT_K3', $131 = 'BRENT_K4', $132 = 'BRENT_K5', $133 = 'BRENT_K6', $134 = 'BRENT_K7', $135 = 'BRENT_K8', $136 = 'BRENT_K9', $137 = 'BRENT_M0', $138 = 'BRENT_M1', $139 = 'BRENT_M2', $140 = 'BRENT_M3', $141 = 'BRENT_M4', $142 = 'BRENT_M5', $143 = 'BRENT_M6', $144 = 'BRENT_M7', $145 = 'BRENT_M8', $146 = 'BRENT_M9', $147 = 'BRENT_N0', $148 = 'BRENT_N1', $149 = 'BRENT_N2', $150 = 'BRENT_N3', $151 = 'BRENT_N4', $152 = 'BRENT_N5', $153 = 'BRENT_N6', $154 = 'BRENT_N7', $155 = 'BRENT_N8', $156 = 'BRENT_N9', $157 = 'BRENT_Q0', $158 = 'BRENT_Q1', $159 = 'BRENT_Q2', $160 = 'BRENT_Q3', $161 = 'BRENT_Q4', $162 = 'BRENT_Q5', $163 = 'BRENT_Q6', $164 = 'BRENT_Q7', $165 = 'BRENT_Q8', $166 = 'BRENT_Q9', $167 = 'BRENT_U0', $168 = 'BRENT_U1', $169 = 'BRENT_U2', $170 = 'BRENT_U3', $171 = 'BRENT_U4', $172 = 'BRENT_U5', $173 = 'BRENT_U6', $174 = 'BRENT_U7', $175 = 'BRENT_U8', $176 = 'BRENT_U9', $177 = 'BRENT_V0', $178 = 'BRENT_V1', $179 = 'BRENT_V2', $180 = 'BRENT_V3', $181 = 'BRENT_V4', $182 = 'BRENT_V5', $183 = 'BRENT_V6', $184 = 'BRENT_V7', $185 = 'BRENT_V8', $186 = 'BRENT_V9', $187 = 'BRENT_X0', $188 = 'BRENT_X1', $189 = 'BRENT_X2', $190 = 'BRENT_X3', $191 = 'BRENT_X4', $192 = 'BRENT_X5', $193 = 'BRENT_X6', $194 = 'BRENT_X7', $195 = 'BRENT_X8', $196 = 'BRENT_X9', $197 = 'BRENT_Z0', $198 = 'BRENT_Z1', $199 = 'BRENT_Z2', $200 = 'BRENT_Z3', $201 = 'BRENT_Z4', $202 = 'BRENT_Z5', $203 = 'BRENT_Z6', $204 = 'BRENT_Z7', $205 = 'BRENT_Z8', $206 = 'BRENT_Z9', $207 = 'Coffee_F0', $208 = 'Coffee_F1', $209 = 'Coffee_F2', $210 = 'Coffee_F3', $211 = 'Coffee_F4', $212 = 'Coffee_F5', $213 = 'Coffee_F6', $214 = 'Coffee_F7', $215 = 'Coffee_F8', $216 = 'Coffee_F9', $217 = 'Coffee_G0', $218 = 'Coffee_G1', $219 = 'Coffee_G2', $220 = 'Coffee_G3', $221 = 'Coffee_G4', $222 = 'Coffee_G5', $223 = 'Coffee_G6', $224 = 'Coffee_G7', $225 = 'Coffee_G8', $226 = 'Coffee_G9', $227 = 'Coffee_H0', $228 = 'Coffee_H1', $229 = 'Coffee_H2', $230 = 'Coffee_H3', $231 = 'Coffee_H4', $232 = 'Coffee_H5', $233 = 'Coffee_H6', $234 = 'Coffee_H7', $235 = 'Coffee_H8', $236 = 'Coffee_H9', $237 = 'Coffee_J0', $238 = 'Coffee_J1', $239 = 'Coffee_J2', $240 = 'Coffee_J3', $241 = 'Coffee_J4', $242 = 'Coffee_J5', $243 = 'Coffee_J6', $244 = 'Coffee_J7', $245 = 'Coffee_J8', $246 = 'Coffee_J9', $247 = 'Coffee_K0', $248 = 'Coffee_K1', $249 = 'Coffee_K2', $250 = 'Coffee_K3', $251 = 'Coffee_K4', $252 = 'Coffee_K5', $253 = 'Coffee_K6', $254 = 'Coffee_K7', $255 = 'Coffee_K8', $256 = 'Coffee_K9', $257 = 'Coffee_M0', $258 = 'Coffee_M1', $259 = 'Coffee_M2', $260 = 'Coffee_M3', $261 = 'Coffee_M4', $262 = 'Coffee_M5', $263 = 'Coffee_M6', $264 = 'Coffee_M7', $265 = 'Coffee_M8', $266 = 'Coffee_M9', $267 = 'Coffee_N0', $268 = 'Coffee_N1', $269 = 'Coffee_N2', $270 = 'Coffee_N3', $271 = 'Coffee_N4', $272 = 'Coffee_N5', $273 = 'Coffee_N6', $274 = 'Coffee_N7', $275 = 'Coffee_N8', $276 = 'Coffee_N9', $277 = 'Coffee_Q0', $278 = 'Coffee_Q1', $279 = 'Coffee_Q2', $280 = 'Coffee_Q3', $281 = 'Coffee_Q4', $282 = 'Coffee_Q5', $283 = 'Coffee_Q6', $284 = 'Coffee_Q7', $285 = 'Coffee_Q8', $286 = 'Coffee_Q9', $287 = 'Coffee_U0', $288 = 'Coffee_U1', $289 = 'Coffee_U2', $290 = 'Coffee_U3', $291 = 'Coffee_U4', $292 = 'Coffee_U5', $293 = 'Coffee_U6', $294 = 'Coffee_U7', $295 = 'Coffee_U8', $296 = 'Coffee_U9', $297 = 'Coffee_V0', $298 = 'Coffee_V1', $299 = 'Coffee_V2', $300 = 'Coffee_V3', $301 = 'Coffee_V4', $302 = 'Coffee_V5', $303 = 'Coffee_V6', $304 = 'Coffee_V7', $305 = 'Coffee_V8', $306 = 'Coffee_V9', $307 = 'Coffee_X0', $308 = 'Coffee_X1', $309 = 'Coffee_X2', $310 = 'Coffee_X3', $311 = 'Coffee_X4', $312 = 'Coffee_X5', $313 = 'Coffee_X6', $314 = 'Coffee_X7', $315 = 'Coffee_X8', $316 = 'Coffee_X9', $317 = 'Coffee_Z0', $318 = 'Coffee_Z1', $319 = 'Coffee_Z2', $320 = 'Coffee_Z3', $321 = 'Coffee_Z4', $322 = 'Coffee_Z5', $323 = 'Coffee_Z6', $324 = 'Coffee_Z7', $325 = 'Coffee_Z8', $326 = 'Coffee_Z9', $327 = 'Corn_F0', $328 = 'Corn_F1', $329 = 'Corn_F2', $330 = 'Corn_F3', $331 = 'Corn_F4', $332 = 'Corn_F5', $333 = 'Corn_F6', $334 = 'Corn_F7', $335 = 'Corn_F8', $336 = 'Corn_F9', $337 = 'Corn_G0', $338 = 'Corn_G1', $339 = 'Corn_G2', $340 = 'Corn_G3', $341 = 'Corn_G4', $342 = 'Corn_G5', $343 = 'Corn_G6', $344 = 'Corn_G7', $345 = 'Corn_G8', $346 = 'Corn_G9', $347 = 'Corn_H0', $348 = 'Corn_H1', $349 = 'Corn_H2', $350 = 'Corn_H3', $351 = 'Corn_H4', $352 = 'Corn_H5', $353 = 'Corn_H6', $354 = 'Corn_H7', $355 = 'Corn_H8', $356 = 'Corn_H9', $357 = 'Corn_J0', $358 = 'Corn_J1', $359 = 'Corn_J2', $360 = 'Corn_J3', $361 = 'Corn_J4', $362 = 'Corn_J5', $363 = 'Corn_J6', $364 = 'Corn_J7', $365 = 'Corn_J8', $366 = 'Corn_J9', $367 = 'Corn_K0', $368 = 'Corn_K1', $369 = 'Corn_K2', $370 = 'Corn_K3', $371 = 'Corn_K4', $372 = 'Corn_K5', $373 = 'Corn_K6', $374 = 'Corn_K7', $375 = 'Corn_K8', $376 = 'Corn_K9', $377 = 'Corn_M0', $378 = 'Corn_M1', $379 = 'Corn_M2', $380 = 'Corn_M3', $381 = 'Corn_M4', $382 = 'Corn_M5', $383 = 'Corn_M6', $384 = 'Corn_M7', $385 = 'Corn_M8', $386 = 'Corn_M9', $387 = 'Corn_N0', $388 = 'Corn_N1', $389 = 'Corn_N2', $390 = 'Corn_N3', $391 = 'Corn_N4', $392 = 'Corn_N5', $393 = 'Corn_N6', $394 = 'Corn_N7', $395 = 'Corn_N8', $396 = 'Corn_N9', $397 = 'Corn_Q0', $398 = 'Corn_Q1', $399 = 'Corn_Q2', $400 = 'Corn_Q3', $401 = 'Corn_Q4', $402 = 'Corn_Q5', $403 = 'Corn_Q6', $404 = 'Corn_Q7', $405 = 'Corn_Q8', $406 = 'Corn_Q9', $407 = 'Corn_U0', $408 = 'Corn_U1', $409 = 'Corn_U2', $410 = 'Corn_U3', $411 = 'Corn_U4', $412 = 'Corn_U5', $413 = 'Corn_U6', $414 = 'Corn_U7', $415 = 'Corn_U8', $416 = 'Corn_U9', $417 = 'Corn_V0', $418 = 'Corn_V1', $419 = 'Corn_V2', $420 = 'Corn_V3', $421 = 'Corn_V4', $422 = 'Corn_V5', $423 = 'Corn_V6', $424 = 'Corn_V7', $425 = 'Corn_V8', $426 = 'Corn_V9', $427 = 'Corn_X0', $428 = 'Corn_X1', $429 = 'Corn_X2', $430 = 'Corn_X3', $431 = 'Corn_X4', $432 = 'Corn_X5', $433 = 'Corn_X6', $434 = 'Corn_X7', $435 = 'Corn_X8', $436 = 'Corn_X9', $437 = 'Corn_Z0', $438 = 'Corn_Z1', $439 = 'Corn_Z2', $440 = 'Corn_Z3', $441 = 'Corn_Z4', $442 = 'Corn_Z5', $443 = 'Corn_Z6', $444 = 'Corn_Z7', $445 = 'Corn_Z8', $446 = 'Corn_Z9', $447 = 'Soybean_F0', $448 = 'Soybean_F1', $449 = 'Soybean_F2', $450 = 'Soybean_F3', $451 = 'Soybean_F4', $452 = 'Soybean_F5', $453 = 'Soybean_F6', $454 = 'Soybean_F7', $455 = 'Soybean_F8', $456 = 'Soybean_F9', $457 = 'Soybean_G0', $458 = 'Soybean_G1', $459 = 'Soybean_G2', $460 = 'Soybean_G3', $461 = 'Soybean_G4', $462 = 'Soybean_G5', $463 = 'Soybean_G6', $464 = 'Soybean_G7', $465 = 'Soybean_G8', $466 = 'Soybean_G9', $467 = 'Soybean_H0', $468 = 'Soybean_H1', $469 = 'Soybean_H2', $470 = 'Soybean_H3', $471 = 'Soybean_H4', $472 = 'Soybean_H5', $473 = 'Soybean_H6', $474 = 'Soybean_H7', $475 = 'Soybean_H8', $476 = 'Soybean_H9', $477 = 'Soybean_J0', $478 = 'Soybean_J1', $479 = 'Soybean_J2', $480 = 'Soybean_J3', $481 = 'Soybean_J4', $482 = 'Soybean_J5', $483 = 'Soybean_J6', $484 = 'Soybean_J7', $485 = 'Soybean_J8', $486 = 'Soybean_J9', $487 = 'Soybean_K0', $488 = 'Soybean_K1', $489 = 'Soybean_K2', $490 = 'Soybean_K3', $491 = 'Soybean_K4', $492 = 'Soybean_K5', $493 = 'Soybean_K6', $494 = 'Soybean_K7', $495 = 'Soybean_K8', $496 = 'Soybean_K9', $497 = 'Soybean_M0', $498 = 'Soybean_M1', $499 = 'Soybean_M2', $500 = 'Soybean_M3', $501 = 'Soybean_M4', $502 = 'Soybean_M5', $503 = 'Soybean_M6', $504 = 'Soybean_M7', $505 = 'Soybean_M8', $506 = 'Soybean_M9', $507 = 'Soybean_N0', $508 = 'Soybean_N1', $509 = 'Soybean_N2', $510 = 'Soybean_N3', $511 = 'Soybean_N4', $512 = 'Soybean_N5', $513 = 'Soybean_N6', $514 = 'Soybean_N7', $515 = 'Soybean_N8', $516 = 'Soybean_N9', $517 = 'Soybean_Q0', $518 = 'Soybean_Q1', $519 = 'Soybean_Q2', $520 = 'Soybean_Q3', $521 = 'Soybean_Q4', $522 = 'Soybean_Q5', $523 = 'Soybean_Q6', $524 = 'Soybean_Q7', $525 = 'Soybean_Q8', $526 = 'Soybean_Q9', $527 = 'Soybean_U0', $528 = 'Soybean_U1', $529 = 'Soybean_U2', $530 = 'Soybean_U3', $531 = 'Soybean_U4', $532 = 'Soybean_U5', $533 = 'Soybean_U6', $534 = 'Soybean_U7', $535 = 'Soybean_U8', $536 = 'Soybean_U9', $537 = 'Soybean_V0', $538 = 'Soybean_V1', $539 = 'Soybean_V2', $540 = 'Soybean_V3', $541 = 'Soybean_V4', $542 = 'Soybean_V5', $543 = 'Soybean_V6', $544 = 'Soybean_V7', $545 = 'Soybean_V8', $546 = 'Soybean_V9', $547 = 'Soybean_X0', $548 = 'Soybean_X1', $549 = 'Soybean_X2', $550 = 'Soybean_X3', $551 = 'Soybean_X4', $552 = 'Soybean_X5', $553 = 'Soybean_X6', $554 = 'Soybean_X7', $555 = 'Soybean_X8', $556 = 'Soybean_X9', $557 = 'Soybean_Z0', $558 = 'Soybean_Z1', $559 = 'Soybean_Z2', $560 = 'Soybean_Z3', $561 = 'Soybean_Z4', $562 = 'Soybean_Z5', $563 = 'Soybean_Z6', $564 = 'Soybean_Z7', $565 = 'Soybean_Z8', $566 = 'Soybean_Z9', $567 = 'Sugar_F0', $568 = 'Sugar_F1', $569 = 'Sugar_F2', $570 = 'Sugar_F3', $571 = 'Sugar_F4', $572 = 'Sugar_F5', $573 = 'Sugar_F6', $574 = 'Sugar_F7', $575 = 'Sugar_F8', $576 = 'Sugar_F9', $577 = 'Sugar_G0', $578 = 'Sugar_G1', $579 = 'Sugar_G2', $580 = 'Sugar_G3', $581 = 'Sugar_G4', $582 = 'Sugar_G5', $583 = 'Sugar_G6', $584 = 'Sugar_G7', $585 = 'Sugar_G8', $586 = 'Sugar_G9', $587 = 'Sugar_H0', $588 = 'Sugar_H1', $589 = 'Sugar_H2', $590 = 'Sugar_H3', $591 = 'Sugar_H4', $592 = 'Sugar_H5', $593 = 'Sugar_H6', $594 = 'Sugar_H7', $595 = 'Sugar_H8', $596 = 'Sugar_H9', $597 = 'Sugar_J0', $598 = 'Sugar_J1', $599 = 'Sugar_J2', $600 = 'Sugar_J3', $601 = 'Sugar_J4', $602 = 'Sugar_J5', $603 = 'Sugar_J6', $604 = 'Sugar_J7', $605 = 'Sugar_J8', $606 = 'Sugar_J9', $607 = 'Sugar_K0', $608 = 'Sugar_K1', $609 = 'Sugar_K2', $610 = 'Sugar_K3', $611 = 'Sugar_K4', $612 = 'Sugar_K5', $613 = 'Sugar_K6', $614 = 'Sugar_K7', $615 = 'Sugar_K8', $616 = 'Sugar_K9', $617 = 'Sugar_M0', $618 = 'Sugar_M1', $619 = 'Sugar_M2', $620 = 'Sugar_M3', $621 = 'Sugar_M4', $622 = 'Sugar_M5', $623 = 'Sugar_M6', $624 = 'Sugar_M7', $625 = 'Sugar_M8', $626 = 'Sugar_M9', $627 = 'Sugar_N0', $628 = 'Sugar_N1', $629 = 'Sugar_N2', $630 = 'Sugar_N3', $631 = 'Sugar_N4', $632 = 'Sugar_N5', $633 = 'Sugar_N6', $634 = 'Sugar_N7', $635 = 'Sugar_N8', $636 = 'Sugar_N9', $637 = 'Sugar_Q0', $638 = 'Sugar_Q1', $639 = 'Sugar_Q2', $640 = 'Sugar_Q3', $641 = 'Sugar_Q4', $642 = 'Sugar_Q5', $643 = 'Sugar_Q6', $644 = 'Sugar_Q7', $645 = 'Sugar_Q8', $646 = 'Sugar_Q9', $647 = 'Sugar_U0', $648 = 'Sugar_U1', $649 = 'Sugar_U2', $650 = 'Sugar_U3', $651 = 'Sugar_U4', $652 = 'Sugar_U5', $653 = 'Sugar_U6', $654 = 'Sugar_U7', $655 = 'Sugar_U8', $656 = 'Sugar_U9', $657 = 'Sugar_V0', $658 = 'Sugar_V1', $659 = 'Sugar_V2', $660 = 'Sugar_V3', $661 = 'Sugar_V4', $662 = 'Sugar_V5', $663 = 'Sugar_V6', $664 = 'Sugar_V7', $665 = 'Sugar_V8', $666 = 'Sugar_V9', $667 = 'Sugar_X0', $668 = 'Sugar_X1', $669 = 'Sugar_X2', $670 = 'Sugar_X3', $671 = 'Sugar_X4', $672 = 'Sugar_X5', $673 = 'Sugar_X6', $674 = 'Sugar_X7', $675 = 'Sugar_X8', $676 = 'Sugar_X9', $677 = 'Sugar_Z0', $678 = 'Sugar_Z1', $679 = 'Sugar_Z2', $680 = 'Sugar_Z3', $681 = 'Sugar_Z4', $682 = 'Sugar_Z5', $683 = 'Sugar_Z6', $684 = 'Sugar_Z7', $685 = 'Sugar_Z8', $686 = 'Sugar_Z9', $687 = 'Wheat_F0', $688 = 'Wheat_F1', $689 = 'Wheat_F2', $690 = 'Wheat_F3', $691 = 'Wheat_F4', $692 = 'Wheat_F5', $693 = 'Wheat_F6', $694 = 'Wheat_F7', $695 = 'Wheat_F8', $696 = 'Wheat_F9', $697 = 'Wheat_G0', $698 = 'Wheat_G1', $699 = 'Wheat_G2', $700 = 'Wheat_G3', $701 = 'Wheat_G4', $702 = 'Wheat_G5', $703 = 'Wheat_G6', $704 = 'Wheat_G7', $705 = 'Wheat_G8', $706 = 'Wheat_G9', $707 = 'Wheat_H0', $708 = 'Wheat_H1', $709 = 'Wheat_H2', $710 = 'Wheat_H3', $711 = 'Wheat_H4', $712 = 'Wheat_H5', $713 = 'Wheat_H6', $714 = 'Wheat_H7', $715 = 'Wheat_H8', $716 = 'Wheat_H9', $717 = 'Wheat_J0', $718 = 'Wheat_J1', $719 = 'Wheat_J2', $720 = 'Wheat_J3', $721 = 'Wheat_J4', $722 = 'Wheat_J5', $723 = 'Wheat_J6', $724 = 'Wheat_J7', $725 = 'Wheat_J8', $726 = 'Wheat_J9', $727 = 'Wheat_K0', $728 = 'Wheat_K1', $729 = 'Wheat_K2', $730 = 'Wheat_K3', $731 = 'Wheat_K4', $732 = 'Wheat_K5', $733 = 'Wheat_K6', $734 = 'Wheat_K7', $735 = 'Wheat_K8', $736 = 'Wheat_K9', $737 = 'Wheat_M0', $738 = 'Wheat_M1', $739 = 'Wheat_M2', $740 = 'Wheat_M3', $741 = 'Wheat_M4', $742 = 'Wheat_M5', $743 = 'Wheat_M6', $744 = 'Wheat_M7', $745 = 'Wheat_M8', $746 = 'Wheat_M9', $747 = 'Wheat_N0', $748 = 'Wheat_N1', $749 = 'Wheat_N2', $750 = 'Wheat_N3', $751 = 'Wheat_N4', $752 = 'Wheat_N5', $753 = 'Wheat_N6', $754 = 'Wheat_N7', $755 = 'Wheat_N8', $756 = 'Wheat_N9', $757 = 'Wheat_Q0', $758 = 'Wheat_Q1', $759 = 'Wheat_Q2', $760 = 'Wheat_Q3', $761 = 'Wheat_Q4', $762 = 'Wheat_Q5', $763 = 'Wheat_Q6', $764 = 'Wheat_Q7', $765 = 'Wheat_Q8', $766 = 'Wheat_Q9', $767 = 'Wheat_U0', $768 = 'Wheat_U1', $769 = 'Wheat_U2', $770 = 'Wheat_U3', $771 = 'Wheat_U4', $772 = 'Wheat_U5', $773 = 'Wheat_U6', $774 = 'Wheat_U7', $775 = 'Wheat_U8', $776 = 'Wheat_U9', $777 = 'Wheat_V0', $778 = 'Wheat_V1', $779 = 'Wheat_V2', $780 = 'Wheat_V3', $781 = 'Wheat_V4', $782 = 'Wheat_V5', $783 = 'Wheat_V6', $784 = 'Wheat_V7', $785 = 'Wheat_V8', $786 = 'Wheat_V9', $787 = 'Wheat_X0', $788 = 'Wheat_X1', $789 = 'Wheat_X2', $790 = 'Wheat_X3', $791 = 'Wheat_X4', $792 = 'Wheat_X5', $793 = 'Wheat_X6', $794 = 'Wheat_X7', $795 = 'Wheat_X8', $796 = 'Wheat_X9', $797 = 'Wheat_Z0', $798 = 'Wheat_Z1', $799 = 'Wheat_Z2', $800 = 'Wheat_Z3', $801 = 'Wheat_Z4', $802 = 'Wheat_Z5', $803 = 'Wheat_Z6', $804 = 'Wheat_Z7', $805 = 'Wheat_Z8', $806 = 'Wheat_Z9', $807 = 'WTI_F0', $808 = 'WTI_F1', $809 = 'WTI_F2', $810 = 'WTI_F3', $811 = 'WTI_F4', $812 = 'WTI_F5', $813 = 'WTI_F6', $814 = 'WTI_F7', $815 = 'WTI_F8', $816 = 'WTI_F9', $817 = 'WTI_G0', $818 = 'WTI_G1', $819 = 'WTI_G2', $820 = 'WTI_G3', $821 = 'WTI_G4', $822 = 'WTI_G5', $823 = 'WTI_G6', $824 = 'WTI_G7', $825 = 'WTI_G8', $826 = 'WTI_G9', $827 = 'WTI_H0', $828 = 'WTI_H1', $829 = 'WTI_H2', $830 = 'WTI_H3', $831 = 'WTI_H4', $832 = 'WTI_H5', $833 = 'WTI_H6', $834 = 'WTI_H7', $835 = 'WTI_H8', $836 = 'WTI_H9', $837 = 'WTI_J0', $838 = 'WTI_J1', $839 = 'WTI_J2', $840 = 'WTI_J3', $841 = 'WTI_J4', $842 = 'WTI_J5', $843 = 'WTI_J6', $844 = 'WTI_J7', $845 = 'WTI_J8', $846 = 'WTI_J9', $847 = 'WTI_K0', $848 = 'WTI_K1', $849 = 'WTI_K2', $850 = 'WTI_K3', $851 = 'WTI_K4', $852 = 'WTI_K5', $853 = 'WTI_K6', $854 = 'WTI_K7', $855 = 'WTI_K8', $856 = 'WTI_K9', $857 = 'WTI_M0', $858 = 'WTI_M1', $859 = 'WTI_M2', $860 = 'WTI_M3', $861 = 'WTI_M4', $862 = 'WTI_M5', $863 = 'WTI_M6', $864 = 'WTI_M7', $865 = 'WTI_M8', $866 = 'WTI_M9', $867 = 'WTI_N0', $868 = 'WTI_N1', $869 = 'WTI_N2', $870 = 'WTI_N3', $871 = 'WTI_N4', $872 = 'WTI_N5', $873 = 'WTI_N6', $874 = 'WTI_N7', $875 = 'WTI_N8', $876 = 'WTI_N9', $877 = 'WTI_Q0', $878 = 'WTI_Q1', $879 = 'WTI_Q2', $880 = 'WTI_Q3', $881 = 'WTI_Q4', $882 = 'WTI_Q5', $883 = 'WTI_Q6', $884 = 'WTI_Q7', $885 = 'WTI_Q8', $886 = 'WTI_Q9', $887 = 'WTI_U0', $888 = 'WTI_U1', $889 = 'WTI_U2', $890 = 'WTI_U3', $891 = 'WTI_U4', $892 = 'WTI_U5', $893 = 'WTI_U6', $894 = 'WTI_U7', $895 = 'WTI_U8', $896 = 'WTI_U9', $897 = 'WTI_V0', $898 = 'WTI_V1', $899 = 'WTI_V2', $900 = 'WTI_V3', $901 = 'WTI_V4', $902 = 'WTI_V5', $903 = 'WTI_V6', $904 = 'WTI_V7', $905 = 'WTI_V8', $906 = 'WTI_V9', $907 = 'WTI_X0', $908 = 'WTI_X1', $909 = 'WTI_X2', $910 = 'WTI_X3', $911 = 'WTI_X4', $912 = 'WTI_X5', $913 = 'WTI_X6', $914 = 'WTI_X7', $915 = 'WTI_X8', $916 = 'WTI_X9', $917 = 'WTI_Z0', $918 = 'WTI_Z1', $919 = 'WTI_Z2', $920 = 'WTI_Z3', $921 = 'WTI_Z4', $922 = 'WTI_Z5', $923 = 'WTI_Z6', $924 = 'WTI_Z7', $925 = 'WTI_Z8', $926 = 'WTI_Z9', $927 = 'AUDSGD', $928 = 'CHFSGD', $929 = 'EURDKK', $930 = 'EURHKD', $931 = 'EURNOK', $932 = 'EURPLN', $933 = 'EURSEK', $934 = 'EURSGD', $935 = 'EURTRY', $936 = 'EURZAR', $937 = 'GBPDKK', $938 = 'GBPNOK', $939 = 'GBPSEK', $940 = 'GBPSGD', $941 = 'NOKJPY', $942 = 'NOKSEK', $943 = 'SEKJPY', $944 = 'SGDJPY', $945 = 'USDCNH', $946 = 'USDCZK', $947 = 'USDDKK', $948 = 'USDHKD', $949 = 'USDHUF', $950 = 'USDMXN', $951 = 'USDNOK', $952 = 'USDPLN', $953 = 'USDRUB', $954 = 'USDSEK', $955 = 'USDTHB', $956 = 'USDTRY', $957 = 'USDZAR', $958 = 'AUDUSD', $959 = 'EURUSD', $960 = 'GBPUSD', $961 = 'USDCAD', $962 = 'USDCHF', $963 = 'USDJPY', $964 = 'AUDCAD', $965 = 'AUDCHF', $966 = 'AUDJPY', $967 = 'AUDNZD', $968 = 'CADCHF', $969 = 'CADJPY', $970 = 'CHFJPY', $971 = 'EURAUD', $972 = 'EURCAD', $973 = 'EURCHF', $974 = 'EURGBP', $975 = 'EURJPY', $976 = 'EURNZD', $977 = 'GBPAUD', $978 = 'GBPCAD', $979 = 'GBPCHF', $980 = 'GBPJPY', $981 = 'GBPNZD', $982 = 'NZDCAD', $983 = 'NZDCHF', $984 = 'NZDJPY', $985 = 'NZDUSD', $986 = 'USDSGD', $987 = 'AUS200', $988 = 'CHINA50', $989 = 'DE30', $990 = 'ES35', $991 = 'F40', $992 = 'HK50', $993 = 'IT40', $994 = 'JP225', $995 = 'STOXX50', $996 = 'UK100', $997 = 'US2000', $998 = 'US30', $999 = 'US500', $1000 = 'USTEC', $1001 = 'XAGEUR', $1002 = 'XAGUSD', $1003 = 'XAUEUR', $1004 = 'XAUUSD', $1005 = 'XPDUSD', $1006 = 'XPTUSD', $1007 = 'XBRUSD', $1008 = 'XNGUSD', $1009 = 'XTIUSD', $1010 = 'BTCUSD', $1011 = 'BRENT_F0', $1012 = 'BRENT_F1', $1013 = 'BRENT_F2', $1014 = 'BRENT_F3', $1015 = 'BRENT_F4', $1016 = 'BRENT_F5', $1017 = 'BRENT_F6', $1018 = 'BRENT_F7', $1019 = 'BRENT_F8', $1020 = 'BRENT_F9', $1021 = 'BRENT_G0', $1022 = 'BRENT_G1', $1023 = 'BRENT_G2', $1024 = 'BRENT_G3', $1025 = 'BRENT_G4', $1026 = 'BRENT_G5', $1027 = 'BRENT_G6', $1028 = 'BRENT_G7', $1029 = 'BRENT_G8', $1030 = 'BRENT_G9', $1031 = 'BRENT_H0', $1032 = 'BRENT_H1', $1033 = 'BRENT_H2', $1034 = 'BRENT_H3', $1035 = 'BRENT_H4', $1036 = 'BRENT_H5', $1037 = 'BRENT_H6', $1038 = 'BRENT_H7', $1039 = 'BRENT_H8', $1040 = 'BRENT_H9', $1041 = 'BRENT_J0', $1042 = 'BRENT_J1', $1043 = 'BRENT_J2', $1044 = 'BRENT_J3', $1045 = 'BRENT_J4', $1046 = 'BRENT_J5', $1047 = 'BRENT_J6', $1048 = 'BRENT_J7', $1049 = 'BRENT_J8', $1050 = 'BRENT_J9', $1051 = 'BRENT_K0', $1052 = 'BRENT_K1', $1053 = 'BRENT_K2', $1054 = 'BRENT_K3', $1055 = 'BRENT_K4', $1056 = 'BRENT_K5', $1057 = 'BRENT_K6', $1058 = 'BRENT_K7', $1059 = 'BRENT_K8', $1060 = 'BRENT_K9', $1061 = 'BRENT_M0', $1062 = 'BRENT_M1', $1063 = 'BRENT_M2', $1064 = 'BRENT_M3', $1065 = 'BRENT_M4', $1066 = 'BRENT_M5', $1067 = 'BRENT_M6', $1068 = 'BRENT_M7', $1069 = 'BRENT_M8', $1070 = 'BRENT_M9', $1071 = 'BRENT_N0', $1072 = 'BRENT_N1', $1073 = 'BRENT_N2', $1074 = 'BRENT_N3', $1075 = 'BRENT_N4', $1076 = 'BRENT_N5', $1077 = 'BRENT_N6', $1078 = 'BRENT_N7', $1079 = 'BRENT_N8', $1080 = 'BRENT_N9', $1081 = 'BRENT_Q0', $1082 = 'BRENT_Q1', $1083 = 'BRENT_Q2', $1084 = 'BRENT_Q3', $1085 = 'BRENT_Q4', $1086 = 'BRENT_Q5', $1087 = 'BRENT_Q6', $1088 = 'BRENT_Q7', $1089 = 'BRENT_Q8', $1090 = 'BRENT_Q9', $1091 = 'BRENT_U0', $1092 = 'BRENT_U1', $1093 = 'BRENT_U2', $1094 = 'BRENT_U3', $1095 = 'BRENT_U4', $1096 = 'BRENT_U5', $1097 = 'BRENT_U6', $1098 = 'BRENT_U7', $1099 = 'BRENT_U8', $1100 = 'BRENT_U9', $1101 = 'BRENT_V0', $1102 = 'BRENT_V1', $1103 = 'BRENT_V2', $1104 = 'BRENT_V3', $1105 = 'BRENT_V4', $1106 = 'BRENT_V5', $1107 = 'BRENT_V6', $1108 = 'BRENT_V7', $1109 = 'BRENT_V8', $1110 = 'BRENT_V9', $1111 = 'BRENT_X0', $1112 = 'BRENT_X1', $1113 = 'BRENT_X2', $1114 = 'BRENT_X3', $1115 = 'BRENT_X4', $1116 = 'BRENT_X5', $1117 = 'BRENT_X6', $1118 = 'BRENT_X7', $1119 = 'BRENT_X8', $1120 = 'BRENT_X9', $1121 = 'BRENT_Z0', $1122 = 'BRENT_Z1', $1123 = 'BRENT_Z2', $1124 = 'BRENT_Z3', $1125 = 'BRENT_Z4', $1126 = 'BRENT_Z5', $1127 = 'BRENT_Z6', $1128 = 'BRENT_Z7', $1129 = 'BRENT_Z8', $1130 = 'BRENT_Z9', $1131 = 'Coffee_F0', $1132 = 'Coffee_F1', $1133 = 'Coffee_F2', $1134 = 'Coffee_F3', $1135 = 'Coffee_F4', $1136 = 'Coffee_F5', $1137 = 'Coffee_F6', $1138 = 'Coffee_F7', $1139 = 'Coffee_F8', $1140 = 'Coffee_F9', $1141 = 'Coffee_G0', $1142 = 'Coffee_G1', $1143 = 'Coffee_G2', $1144 = 'Coffee_G3', $1145 = 'Coffee_G4', $1146 = 'Coffee_G5', $1147 = 'Coffee_G6', $1148 = 'Coffee_G7', $1149 = 'Coffee_G8', $1150 = 'Coffee_G9', $1151 = 'Coffee_H0', $1152 = 'Coffee_H1', $1153 = 'Coffee_H2', $1154 = 'Coffee_H3', $1155 = 'Coffee_H4', $1156 = 'Coffee_H5', $1157 = 'Coffee_H6', $1158 = 'Coffee_H7', $1159 = 'Coffee_H8', $1160 = 'Coffee_H9', $1161 = 'Coffee_J0', $1162 = 'Coffee_J1', $1163 = 'Coffee_J2', $1164 = 'Coffee_J3', $1165 = 'Coffee_J4', $1166 = 'Coffee_J5', $1167 = 'Coffee_J6', $1168 = 'Coffee_J7', $1169 = 'Coffee_J8', $1170 = 'Coffee_J9', $1171 = 'Coffee_K0', $1172 = 'Coffee_K1', $1173 = 'Coffee_K2', $1174 = 'Coffee_K3', $1175 = 'Coffee_K4', $1176 = 'Coffee_K5', $1177 = 'Coffee_K6', $1178 = 'Coffee_K7', $1179 = 'Coffee_K8', $1180 = 'Coffee_K9', $1181 = 'Coffee_M0', $1182 = 'Coffee_M1', $1183 = 'Coffee_M2', $1184 = 'Coffee_M3', $1185 = 'Coffee_M4', $1186 = 'Coffee_M5', $1187 = 'Coffee_M6', $1188 = 'Coffee_M7', $1189 = 'Coffee_M8', $1190 = 'Coffee_M9', $1191 = 'Coffee_N0', $1192 = 'Coffee_N1', $1193 = 'Coffee_N2', $1194 = 'Coffee_N3', $1195 = 'Coffee_N4', $1196 = 'Coffee_N5', $1197 = 'Coffee_N6', $1198 = 'Coffee_N7', $1199 = 'Coffee_N8', $1200 = 'Coffee_N9', $1201 = 'Coffee_Q0', $1202 = 'Coffee_Q1', $1203 = 'Coffee_Q2', $1204 = 'Coffee_Q3', $1205 = 'Coffee_Q4', $1206 = 'Coffee_Q5', $1207 = 'Coffee_Q6', $1208 = 'Coffee_Q7', $1209 = 'Coffee_Q8', $1210 = 'Coffee_Q9', $1211 = 'Coffee_U0', $1212 = 'Coffee_U1', $1213 = 'Coffee_U2', $1214 = 'Coffee_U3', $1215 = 'Coffee_U4', $1216 = 'Coffee_U5', $1217 = 'Coffee_U6', $1218 = 'Coffee_U7', $1219 = 'Coffee_U8', $1220 = 'Coffee_U9', $1221 = 'Coffee_V0', $1222 = 'Coffee_V1', $1223 = 'Coffee_V2', $1224 = 'Coffee_V3', $1225 = 'Coffee_V4', $1226 = 'Coffee_V5', $1227 = 'Coffee_V6', $1228 = 'Coffee_V7', $1229 = 'Coffee_V8', $1230 = 'Coffee_V9', $1231 = 'Coffee_X0', $1232 = 'Coffee_X1', $1233 = 'Coffee_X2', $1234 = 'Coffee_X3', $1235 = 'Coffee_X4', $1236 = 'Coffee_X5', $1237 = 'Coffee_X6', $1238 = 'Coffee_X7', $1239 = 'Coffee_X8', $1240 = 'Coffee_X9', $1241 = 'Coffee_Z0', $1242 = 'Coffee_Z1', $1243 = 'Coffee_Z2', $1244 = 'Coffee_Z3', $1245 = 'Coffee_Z4', $1246 = 'Coffee_Z5', $1247 = 'Coffee_Z6', $1248 = 'Coffee_Z7', $1249 = 'Coffee_Z8', $1250 = 'Coffee_Z9', $1251 = 'Corn_F0', $1252 = 'Corn_F1', $1253 = 'Corn_F2', $1254 = 'Corn_F3', $1255 = 'Corn_F4', $1256 = 'Corn_F5', $1257 = 'Corn_F6', $1258 = 'Corn_F7', $1259 = 'Corn_F8', $1260 = 'Corn_F9', $1261 = 'Corn_G0', $1262 = 'Corn_G1', $1263 = 'Corn_G2', $1264 = 'Corn_G3', $1265 = 'Corn_G4', $1266 = 'Corn_G5', $1267 = 'Corn_G6', $1268 = 'Corn_G7', $1269 = 'Corn_G8', $1270 = 'Corn_G9', $1271 = 'Corn_H0', $1272 = 'Corn_H1', $1273 = 'Corn_H2', $1274 = 'Corn_H3', $1275 = 'Corn_H4', $1276 = 'Corn_H5', $1277 = 'Corn_H6', $1278 = 'Corn_H7', $1279 = 'Corn_H8', $1280 = 'Corn_H9', $1281 = 'Corn_J0', $1282 = 'Corn_J1', $1283 = 'Corn_J2', $1284 = 'Corn_J3', $1285 = 'Corn_J4', $1286 = 'Corn_J5', $1287 = 'Corn_J6', $1288 = 'Corn_J7', $1289 = 'Corn_J8', $1290 = 'Corn_J9', $1291 = 'Corn_K0', $1292 = 'Corn_K1', $1293 = 'Corn_K2', $1294 = 'Corn_K3', $1295 = 'Corn_K4', $1296 = 'Corn_K5', $1297 = 'Corn_K6', $1298 = 'Corn_K7', $1299 = 'Corn_K8', $1300 = 'Corn_K9', $1301 = 'Corn_M0', $1302 = 'Corn_M1', $1303 = 'Corn_M2', $1304 = 'Corn_M3', $1305 = 'Corn_M4', $1306 = 'Corn_M5', $1307 = 'Corn_M6', $1308 = 'Corn_M7', $1309 = 'Corn_M8', $1310 = 'Corn_M9', $1311 = 'Corn_N0', $1312 = 'Corn_N1', $1313 = 'Corn_N2', $1314 = 'Corn_N3', $1315 = 'Corn_N4', $1316 = 'Corn_N5', $1317 = 'Corn_N6', $1318 = 'Corn_N7', $1319 = 'Corn_N8', $1320 = 'Corn_N9', $1321 = 'Corn_Q0', $1322 = 'Corn_Q1', $1323 = 'Corn_Q2', $1324 = 'Corn_Q3', $1325 = 'Corn_Q4', $1326 = 'Corn_Q5', $1327 = 'Corn_Q6', $1328 = 'Corn_Q7', $1329 = 'Corn_Q8', $1330 = 'Corn_Q9', $1331 = 'Corn_U0', $1332 = 'Corn_U1', $1333 = 'Corn_U2', $1334 = 'Corn_U3', $1335 = 'Corn_U4', $1336 = 'Corn_U5', $1337 = 'Corn_U6', $1338 = 'Corn_U7', $1339 = 'Corn_U8', $1340 = 'Corn_U9', $1341 = 'Corn_V0', $1342 = 'Corn_V1', $1343 = 'Corn_V2', $1344 = 'Corn_V3', $1345 = 'Corn_V4', $1346 = 'Corn_V5', $1347 = 'Corn_V6', $1348 = 'Corn_V7', $1349 = 'Corn_V8', $1350 = 'Corn_V9', $1351 = 'Corn_X0', $1352 = 'Corn_X1', $1353 = 'Corn_X2', $1354 = 'Corn_X3', $1355 = 'Corn_X4', $1356 = 'Corn_X5', $1357 = 'Corn_X6', $1358 = 'Corn_X7', $1359 = 'Corn_X8', $1360 = 'Corn_X9', $1361 = 'Corn_Z0', $1362 = 'Corn_Z1', $1363 = 'Corn_Z2', $1364 = 'Corn_Z3', $1365 = 'Corn_Z4', $1366 = 'Corn_Z5', $1367 = 'Corn_Z6', $1368 = 'Corn_Z7', $1369 = 'Corn_Z8', $1370 = 'Corn_Z9', $1371 = 'Soybean_F0', $1372 = 'Soybean_F1', $1373 = 'Soybean_F2', $1374 = 'Soybean_F3', $1375 = 'Soybean_F4', $1376 = 'Soybean_F5', $1377 = 'Soybean_F6', $1378 = 'Soybean_F7', $1379 = 'Soybean_F8', $1380 = 'Soybean_F9', $1381 = 'Soybean_G0', $1382 = 'Soybean_G1', $1383 = 'Soybean_G2', $1384 = 'Soybean_G3', $1385 = 'Soybean_G4', $1386 = 'Soybean_G5', $1387 = 'Soybean_G6', $1388 = 'Soybean_G7', $1389 = 'Soybean_G8', $1390 = 'Soybean_G9', $1391 = 'Soybean_H0', $1392 = 'Soybean_H1', $1393 = 'Soybean_H2', $1394 = 'Soybean_H3', $1395 = 'Soybean_H4', $1396 = 'Soybean_H5', $1397 = 'Soybean_H6', $1398 = 'Soybean_H7', $1399 = 'Soybean_H8', $1400 = 'Soybean_H9', $1401 = 'Soybean_J0', $1402 = 'Soybean_J1', $1403 = 'Soybean_J2', $1404 = 'Soybean_J3', $1405 = 'Soybean_J4', $1406 = 'Soybean_J5', $1407 = 'Soybean_J6', $1408 = 'Soybean_J7', $1409 = 'Soybean_J8', $1410 = 'Soybean_J9', $1411 = 'Soybean_K0', $1412 = 'Soybean_K1', $1413 = 'Soybean_K2', $1414 = 'Soybean_K3', $1415 = 'Soybean_K4', $1416 = 'Soybean_K5', $1417 = 'Soybean_K6', $1418 = 'Soybean_K7', $1419 = 'Soybean_K8', $1420 = 'Soybean_K9', $1421 = 'Soybean_M0', $1422 = 'Soybean_M1', $1423 = 'Soybean_M2', $1424 = 'Soybean_M3', $1425 = 'Soybean_M4', $1426 = 'Soybean_M5', $1427 = 'Soybean_M6', $1428 = 'Soybean_M7', $1429 = 'Soybean_M8', $1430 = 'Soybean_M9', $1431 = 'Soybean_N0', $1432 = 'Soybean_N1', $1433 = 'Soybean_N2', $1434 = 'Soybean_N3', $1435 = 'Soybean_N4', $1436 = 'Soybean_N5', $1437 = 'Soybean_N6', $1438 = 'Soybean_N7', $1439 = 'Soybean_N8', $1440 = 'Soybean_N9', $1441 = 'Soybean_Q0', $1442 = 'Soybean_Q1', $1443 = 'Soybean_Q2', $1444 = 'Soybean_Q3', $1445 = 'Soybean_Q4', $1446 = 'Soybean_Q5', $1447 = 'Soybean_Q6', $1448 = 'Soybean_Q7', $1449 = 'Soybean_Q8', $1450 = 'Soybean_Q9', $1451 = 'Soybean_U0', $1452 = 'Soybean_U1', $1453 = 'Soybean_U2', $1454 = 'Soybean_U3', $1455 = 'Soybean_U4', $1456 = 'Soybean_U5', $1457 = 'Soybean_U6', $1458 = 'Soybean_U7', $1459 = 'Soybean_U8', $1460 = 'Soybean_U9', $1461 = 'Soybean_V0', $1462 = 'Soybean_V1', $1463 = 'Soybean_V2', $1464 = 'Soybean_V3', $1465 = 'Soybean_V4', $1466 = 'Soybean_V5', $1467 = 'Soybean_V6', $1468 = 'Soybean_V7', $1469 = 'Soybean_V8', $1470 = 'Soybean_V9', $1471 = 'Soybean_X0', $1472 = 'Soybean_X1', $1473 = 'Soybean_X2', $1474 = 'Soybean_X3', $1475 = 'Soybean_X4', $1476 = 'Soybean_X5', $1477 = 'Soybean_X6', $1478 = 'Soybean_X7', $1479 = 'Soybean_X8', $1480 = 'Soybean_X9', $1481 = 'Soybean_Z0', $1482 = 'Soybean_Z1', $1483 = 'Soybean_Z2', $1484 = 'Soybean_Z3', $1485 = 'Soybean_Z4', $1486 = 'Soybean_Z5', $1487 = 'Soybean_Z6', $1488 = 'Soybean_Z7', $1489 = 'Soybean_Z8', $1490 = 'Soybean_Z9', $1491 = 'Sugar_F0', $1492 = 'Sugar_F1', $1493 = 'Sugar_F2', $1494 = 'Sugar_F3', $1495 = 'Sugar_F4', $1496 = 'Sugar_F5', $1497 = 'Sugar_F6', $1498 = 'Sugar_F7', $1499 = 'Sugar_F8', $1500 = 'Sugar_F9', $1501 = 'Sugar_G0', $1502 = 'Sugar_G1', $1503 = 'Sugar_G2', $1504 = 'Sugar_G3', $1505 = 'Sugar_G4', $1506 = 'Sugar_G5', $1507 = 'Sugar_G6', $1508 = 'Sugar_G7', $1509 = 'Sugar_G8', $1510 = 'Sugar_G9', $1511 = 'Sugar_H0', $1512 = 'Sugar_H1', $1513 = 'Sugar_H2', $1514 = 'Sugar_H3', $1515 = 'Sugar_H4', $1516 = 'Sugar_H5', $1517 = 'Sugar_H6', $1518 = 'Sugar_H7', $1519 = 'Sugar_H8', $1520 = 'Sugar_H9', $1521 = 'Sugar_J0', $1522 = 'Sugar_J1', $1523 = 'Sugar_J2', $1524 = 'Sugar_J3', $1525 = 'Sugar_J4', $1526 = 'Sugar_J5', $1527 = 'Sugar_J6', $1528 = 'Sugar_J7', $1529 = 'Sugar_J8', $1530 = 'Sugar_J9', $1531 = 'Sugar_K0', $1532 = 'Sugar_K1', $1533 = 'Sugar_K2', $1534 = 'Sugar_K3', $1535 = 'Sugar_K4', $1536 = 'Sugar_K5', $1537 = 'Sugar_K6', $1538 = 'Sugar_K7', $1539 = 'Sugar_K8', $1540 = 'Sugar_K9', $1541 = 'Sugar_M0', $1542 = 'Sugar_M1', $1543 = 'Sugar_M2', $1544 = 'Sugar_M3', $1545 = 'Sugar_M4', $1546 = 'Sugar_M5', $1547 = 'Sugar_M6', $1548 = 'Sugar_M7', $1549 = 'Sugar_M8', $1550 = 'Sugar_M9', $1551 = 'Sugar_N0', $1552 = 'Sugar_N1', $1553 = 'Sugar_N2', $1554 = 'Sugar_N3', $1555 = 'Sugar_N4', $1556 = 'Sugar_N5', $1557 = 'Sugar_N6', $1558 = 'Sugar_N7', $1559 = 'Sugar_N8', $1560 = 'Sugar_N9', $1561 = 'Sugar_Q0', $1562 = 'Sugar_Q1', $1563 = 'Sugar_Q2', $1564 = 'Sugar_Q3', $1565 = 'Sugar_Q4', $1566 = 'Sugar_Q5', $1567 = 'Sugar_Q6', $1568 = 'Sugar_Q7', $1569 = 'Sugar_Q8', $1570 = 'Sugar_Q9', $1571 = 'Sugar_U0', $1572 = 'Sugar_U1', $1573 = 'Sugar_U2', $1574 = 'Sugar_U3', $1575 = 'Sugar_U4', $1576 = 'Sugar_U5', $1577 = 'Sugar_U6', $1578 = 'Sugar_U7', $1579 = 'Sugar_U8', $1580 = 'Sugar_U9', $1581 = 'Sugar_V0', $1582 = 'Sugar_V1', $1583 = 'Sugar_V2', $1584 = 'Sugar_V3', $1585 = 'Sugar_V4', $1586 = 'Sugar_V5', $1587 = 'Sugar_V6', $1588 = 'Sugar_V7', $1589 = 'Sugar_V8', $1590 = 'Sugar_V9', $1591 = 'Sugar_X0', $1592 = 'Sugar_X1', $1593 = 'Sugar_X2', $1594 = 'Sugar_X3', $1595 = 'Sugar_X4', $1596 = 'Sugar_X5', $1597 = 'Sugar_X6', $1598 = 'Sugar_X7', $1599 = 'Sugar_X8', $1600 = 'Sugar_X9', $1601 = 'Sugar_Z0', $1602 = 'Sugar_Z1', $1603 = 'Sugar_Z2', $1604 = 'Sugar_Z3', $1605 = 'Sugar_Z4', $1606 = 'Sugar_Z5', $1607 = 'Sugar_Z6', $1608 = 'Sugar_Z7', $1609 = 'Sugar_Z8', $1610 = 'Sugar_Z9', $1611 = 'Wheat_F0', $1612 = 'Wheat_F1', $1613 = 'Wheat_F2', $1614 = 'Wheat_F3', $1615 = 'Wheat_F4', $1616 = 'Wheat_F5', $1617 = 'Wheat_F6', $1618 = 'Wheat_F7', $1619 = 'Wheat_F8', $1620 = 'Wheat_F9', $1621 = 'Wheat_G0', $1622 = 'Wheat_G1', $1623 = 'Wheat_G2', $1624 = 'Wheat_G3', $1625 = 'Wheat_G4', $1626 = 'Wheat_G5', $1627 = 'Wheat_G6', $1628 = 'Wheat_G7', $1629 = 'Wheat_G8', $1630 = 'Wheat_G9', $1631 = 'Wheat_H0', $1632 = 'Wheat_H1', $1633 = 'Wheat_H2', $1634 = 'Wheat_H3', $1635 = 'Wheat_H4', $1636 = 'Wheat_H5', $1637 = 'Wheat_H6', $1638 = 'Wheat_H7', $1639 = 'Wheat_H8', $1640 = 'Wheat_H9', $1641 = 'Wheat_J0', $1642 = 'Wheat_J1', $1643 = 'Wheat_J2', $1644 = 'Wheat_J3', $1645 = 'Wheat_J4', $1646 = 'Wheat_J5', $1647 = 'Wheat_J6', $1648 = 'Wheat_J7', $1649 = 'Wheat_J8', $1650 = 'Wheat_J9', $1651 = 'Wheat_K0', $1652 = 'Wheat_K1', $1653 = 'Wheat_K2', $1654 = 'Wheat_K3', $1655 = 'Wheat_K4', $1656 = 'Wheat_K5', $1657 = 'Wheat_K6', $1658 = 'Wheat_K7', $1659 = 'Wheat_K8', $1660 = 'Wheat_K9', $1661 = 'Wheat_M0', $1662 = 'Wheat_M1', $1663 = 'Wheat_M2', $1664 = 'Wheat_M3', $1665 = 'Wheat_M4', $1666 = 'Wheat_M5', $1667 = 'Wheat_M6', $1668 = 'Wheat_M7', $1669 = 'Wheat_M8', $1670 = 'Wheat_M9', $1671 = 'Wheat_N0', $1672 = 'Wheat_N1', $1673 = 'Wheat_N2', $1674 = 'Wheat_N3', $1675 = 'Wheat_N4', $1676 = 'Wheat_N5', $1677 = 'Wheat_N6', $1678 = 'Wheat_N7', $1679 = 'Wheat_N8', $1680 = 'Wheat_N9', $1681 = 'Wheat_Q0', $1682 = 'Wheat_Q1', $1683 = 'Wheat_Q2', $1684 = 'Wheat_Q3', $1685 = 'Wheat_Q4', $1686 = 'Wheat_Q5', $1687 = 'Wheat_Q6', $1688 = 'Wheat_Q7', $1689 = 'Wheat_Q8', $1690 = 'Wheat_Q9', $1691 = 'Wheat_U0', $1692 = 'Wheat_U1', $1693 = 'Wheat_U2', $1694 = 'Wheat_U3', $1695 = 'Wheat_U4', $1696 = 'Wheat_U5', $1697 = 'Wheat_U6', $1698 = 'Wheat_U7', $1699 = 'Wheat_U8', $1700 = 'Wheat_U9', $1701 = 'Wheat_V0', $1702 = 'Wheat_V1', $1703 = 'Wheat_V2', $1704 = 'Wheat_V3', $1705 = 'Wheat_V4', $1706 = 'Wheat_V5', $1707 = 'Wheat_V6', $1708 = 'Wheat_V7', $1709 = 'Wheat_V8', $1710 = 'Wheat_V9', $1711 = 'Wheat_X0', $1712 = 'Wheat_X1', $1713 = 'Wheat_X2', $1714 = 'Wheat_X3', $1715 = 'Wheat_X4', $1716 = 'Wheat_X5', $1717 = 'Wheat_X6', $1718 = 'Wheat_X7', $1719 = 'Wheat_X8', $1720 = 'Wheat_X9', $1721 = 'Wheat_Z0', $1722 = 'Wheat_Z1', $1723 = 'Wheat_Z2', $1724 = 'Wheat_Z3', $1725 = 'Wheat_Z4', $1726 = 'Wheat_Z5', $1727 = 'Wheat_Z6', $1728 = 'Wheat_Z7', $1729 = 'Wheat_Z8', $1730 = 'Wheat_Z9', $1731 = 'WTI_F0', $1732 = 'WTI_F1', $1733 = 'WTI_F2', $1734 = 'WTI_F3', $1735 = 'WTI_F4', $1736 = 'WTI_F5', $1737 = 'WTI_F6', $1738 = 'WTI_F7', $1739 = 'WTI_F8', $1740 = 'WTI_F9', $1741 = 'WTI_G0', $1742 = 'WTI_G1', $1743 = 'WTI_G2', $1744 = 'WTI_G3', $1745 = 'WTI_G4', $1746 = 'WTI_G5', $1747 = 'WTI_G6', $1748 = 'WTI_G7', $1749 = 'WTI_G8', $1750 = 'WTI_G9', $1751 = 'WTI_H0', $1752 = 'WTI_H1', $1753 = 'WTI_H2', $1754 = 'WTI_H3', $1755 = 'WTI_H4', $1756 = 'WTI_H5', $1757 = 'WTI_H6', $1758 = 'WTI_H7', $1759 = 'WTI_H8', $1760 = 'WTI_H9', $1761 = 'WTI_J0', $1762 = 'WTI_J1', $1763 = 'WTI_J2', $1764 = 'WTI_J3', $1765 = 'WTI_J4', $1766 = 'WTI_J5', $1767 = 'WTI_J6', $1768 = 'WTI_J7', $1769 = 'WTI_J8', $1770 = 'WTI_J9', $1771 = 'WTI_K0', $1772 = 'WTI_K1', $1773 = 'WTI_K2', $1774 = 'WTI_K3', $1775 = 'WTI_K4', $1776 = 'WTI_K5', $1777 = 'WTI_K6', $1778 = 'WTI_K7', $1779 = 'WTI_K8', $1780 = 'WTI_K9', $1781 = 'WTI_M0', $1782 = 'WTI_M1', $1783 = 'WTI_M2', $1784 = 'WTI_M3', $1785 = 'WTI_M4', $1786 = 'WTI_M5', $1787 = 'WTI_M6', $1788 = 'WTI_M7', $1789 = 'WTI_M8', $1790 = 'WTI_M9', $1791 = 'WTI_N0', $1792 = 'WTI_N1', $1793 = 'WTI_N2', $1794 = 'WTI_N3', $1795 = 'WTI_N4', $1796 = 'WTI_N5', $1797 = 'WTI_N6', $1798 = 'WTI_N7', $1799 = 'WTI_N8', $1800 = 'WTI_N9', $1801 = 'WTI_Q0', $1802 = 'WTI_Q1', $1803 = 'WTI_Q2', $1804 = 'WTI_Q3', $1805 = 'WTI_Q4', $1806 = 'WTI_Q5', $1807 = 'WTI_Q6', $1808 = 'WTI_Q7', $1809 = 'WTI_Q8', $1810 = 'WTI_Q9', $1811 = 'WTI_U0', $1812 = 'WTI_U1', $1813 = 'WTI_U2', $1814 = 'WTI_U3', $1815 = 'WTI_U4', $1816 = 'WTI_U5', $1817 = 'WTI_U6', $1818 = 'WTI_U7', $1819 = 'WTI_U8', $1820 = 'WTI_U9', $1821 = 'WTI_V0', $1822 = 'WTI_V1', $1823 = 'WTI_V2', $1824 = 'WTI_V3', $1825 = 'WTI_V4', $1826 = 'WTI_V5', $1827 = 'WTI_V6', $1828 = 'WTI_V7', $1829 = 'WTI_V8', $1830 = 'WTI_V9', $1831 = 'WTI_X0', $1832 = 'WTI_X1', $1833 = 'WTI_X2', $1834 = 'WTI_X3', $1835 = 'WTI_X4', $1836 = 'WTI_X5', $1837 = 'WTI_X6', $1838 = 'WTI_X7', $1839 = 'WTI_X8', $1840 = 'WTI_X9', $1841 = 'WTI_Z0', $1842 = 'WTI_Z1', $1843 = 'WTI_Z2', $1844 = 'WTI_Z3', $1845 = 'WTI_Z4', $1846 = 'WTI_Z5', $1847 = 'WTI_Z6', $1848 = 'WTI_Z7', $1849 = 'WTI_Z8', $1850 = 'WTI_Z9', $1851 = '5'
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-09-17 13:14:42 Duration: 33ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.164 parameters: $1 = '974', $2 = 'ICMARKETS-AU-MT5', $3 = 'AUDCAD', $4 = 'AUDCHF', $5 = 'AUDJPY', $6 = 'AUDNZD', $7 = 'AUDSGD', $8 = 'AUDUSD', $9 = 'AUS200', $10 = 'BRENT_F0', $11 = 'BRENT_F1', $12 = 'BRENT_F2', $13 = 'BRENT_F3', $14 = 'BRENT_F4', $15 = 'BRENT_F5', $16 = 'BRENT_F6', $17 = 'BRENT_F7', $18 = 'BRENT_F8', $19 = 'BRENT_F9', $20 = 'BRENT_G0', $21 = 'BRENT_G1', $22 = 'BRENT_G2', $23 = 'BRENT_G3', $24 = 'BRENT_G4', $25 = 'BRENT_G5', $26 = 'BRENT_G6', $27 = 'BRENT_G7', $28 = 'BRENT_G8', $29 = 'BRENT_G9', $30 = 'BRENT_H0', $31 = 'BRENT_H1', $32 = 'BRENT_H2', $33 = 'BRENT_H3', $34 = 'BRENT_H4', $35 = 'BRENT_H5', $36 = 'BRENT_H6', $37 = 'BRENT_H7', $38 = 'BRENT_H8', $39 = 'BRENT_H9', $40 = 'BRENT_J0', $41 = 'BRENT_J1', $42 = 'BRENT_J2', $43 = 'BRENT_J3', $44 = 'BRENT_J4', $45 = 'BRENT_J5', $46 = 'BRENT_J6', $47 = 'BRENT_J7', $48 = 'BRENT_J8', $49 = 'BRENT_J9', $50 = 'BRENT_K0', $51 = 'BRENT_K1', $52 = 'BRENT_K2', $53 = 'BRENT_K3', $54 = 'BRENT_K4', $55 = 'BRENT_K5', $56 = 'BRENT_K6', $57 = 'BRENT_K7', $58 = 'BRENT_K8', $59 = 'BRENT_K9', $60 = 'BRENT_M0', $61 = 'BRENT_M1', $62 = 'BRENT_M2', $63 = 'BRENT_M3', $64 = 'BRENT_M4', $65 = 'BRENT_M5', $66 = 'BRENT_M6', $67 = 'BRENT_M7', $68 = 'BRENT_M8', $69 = 'BRENT_M9', $70 = 'BRENT_N0', $71 = 'BRENT_N1', $72 = 'BRENT_N2', $73 = 'BRENT_N3', $74 = 'BRENT_N4', $75 = 'BRENT_N5', $76 = 'BRENT_N6', $77 = 'BRENT_N7', $78 = 'BRENT_N8', $79 = 'BRENT_N9', $80 = 'BRENT_Q0', $81 = 'BRENT_Q1', $82 = 'BRENT_Q2', $83 = 'BRENT_Q3', $84 = 'BRENT_Q4', $85 = 'BRENT_Q5', $86 = 'BRENT_Q6', $87 = 'BRENT_Q7', $88 = 'BRENT_Q8', $89 = 'BRENT_Q9', $90 = 'BRENT_U0', $91 = 'BRENT_U1', $92 = 'BRENT_U2', $93 = 'BRENT_U3', $94 = 'BRENT_U4', $95 = 'BRENT_U5', $96 = 'BRENT_U6', $97 = 'BRENT_U7', $98 = 'BRENT_U8', $99 = 'BRENT_U9', $100 = 'BRENT_V0', $101 = 'BRENT_V1', $102 = 'BRENT_V2', $103 = 'BRENT_V3', $104 = 'BRENT_V4', $105 = 'BRENT_V5', $106 = 'BRENT_V6', $107 = 'BRENT_V7', $108 = 'BRENT_V8', $109 = 'BRENT_V9', $110 = 'BRENT_X0', $111 = 'BRENT_X1', $112 = 'BRENT_X2', $113 = 'BRENT_X3', $114 = 'BRENT_X4', $115 = 'BRENT_X5', $116 = 'BRENT_X6', $117 = 'BRENT_X7', $118 = 'BRENT_X8', $119 = 'BRENT_X9', $120 = 'BRENT_Z0', $121 = 'BRENT_Z1', $122 = 'BRENT_Z2', $123 = 'BRENT_Z3', $124 = 'BRENT_Z4', $125 = 'BRENT_Z5', $126 = 'BRENT_Z6', $127 = 'BRENT_Z7', $128 = 'BRENT_Z8', $129 = 'BRENT_Z9', $130 = 'BTCUSD', $131 = 'CADCHF', $132 = 'CADJPY', $133 = 'CHFJPY', $134 = 'CHFSGD', $135 = 'CHINA50', $136 = 'Coffee_F0', $137 = 'Coffee_F1', $138 = 'Coffee_F2', $139 = 'Coffee_F3', $140 = 'Coffee_F4', $141 = 'Coffee_F5', $142 = 'Coffee_F6', $143 = 'Coffee_F7', $144 = 'Coffee_F8', $145 = 'Coffee_F9', $146 = 'Coffee_G0', $147 = 'Coffee_G1', $148 = 'Coffee_G2', $149 = 'Coffee_G3', $150 = 'Coffee_G4', $151 = 'Coffee_G5', $152 = 'Coffee_G6', $153 = 'Coffee_G7', $154 = 'Coffee_G8', $155 = 'Coffee_G9', $156 = 'Coffee_H0', $157 = 'Coffee_H1', $158 = 'Coffee_H2', $159 = 'Coffee_H3', $160 = 'Coffee_H4', $161 = 'Coffee_H5', $162 = 'Coffee_H6', $163 = 'Coffee_H7', $164 = 'Coffee_H8', $165 = 'Coffee_H9', $166 = 'Coffee_J0', $167 = 'Coffee_J1', $168 = 'Coffee_J2', $169 = 'Coffee_J3', $170 = 'Coffee_J4', $171 = 'Coffee_J5', $172 = 'Coffee_J6', $173 = 'Coffee_J7', $174 = 'Coffee_J8', $175 = 'Coffee_J9', $176 = 'Coffee_K0', $177 = 'Coffee_K1', $178 = 'Coffee_K2', $179 = 'Coffee_K3', $180 = 'Coffee_K4', $181 = 'Coffee_K5', $182 = 'Coffee_K6', $183 = 'Coffee_K7', $184 = 'Coffee_K8', $185 = 'Coffee_K9', $186 = 'Coffee_M0', $187 = 'Coffee_M1', $188 = 'Coffee_M2', $189 = 'Coffee_M3', $190 = 'Coffee_M4', $191 = 'Coffee_M5', $192 = 'Coffee_M6', $193 = 'Coffee_M7', $194 = 'Coffee_M8', $195 = 'Coffee_M9', $196 = 'Coffee_N0', $197 = 'Coffee_N1', $198 = 'Coffee_N2', $199 = 'Coffee_N3', $200 = 'Coffee_N4', $201 = 'Coffee_N5', $202 = 'Coffee_N6', $203 = 'Coffee_N7', $204 = 'Coffee_N8', $205 = 'Coffee_N9', $206 = 'Coffee_Q0', $207 = 'Coffee_Q1', $208 = 'Coffee_Q2', $209 = 'Coffee_Q3', $210 = 'Coffee_Q4', $211 = 'Coffee_Q5', $212 = 'Coffee_Q6', $213 = 'Coffee_Q7', $214 = 'Coffee_Q8', $215 = 'Coffee_Q9', $216 = 'Coffee_U0', $217 = 'Coffee_U1', $218 = 'Coffee_U2', $219 = 'Coffee_U3', $220 = 'Coffee_U4', $221 = 'Coffee_U5', $222 = 'Coffee_U6', $223 = 'Coffee_U7', $224 = 'Coffee_U8', $225 = 'Coffee_U9', $226 = 'Coffee_V0', $227 = 'Coffee_V1', $228 = 'Coffee_V2', $229 = 'Coffee_V3', $230 = 'Coffee_V4', $231 = 'Coffee_V5', $232 = 'Coffee_V6', $233 = 'Coffee_V7', $234 = 'Coffee_V8', $235 = 'Coffee_V9', $236 = 'Coffee_X0', $237 = 'Coffee_X1', $238 = 'Coffee_X2', $239 = 'Coffee_X3', $240 = 'Coffee_X4', $241 = 'Coffee_X5', $242 = 'Coffee_X6', $243 = 'Coffee_X7', $244 = 'Coffee_X8', $245 = 'Coffee_X9', $246 = 'Coffee_Z0', $247 = 'Coffee_Z1', $248 = 'Coffee_Z2', $249 = 'Coffee_Z3', $250 = 'Coffee_Z4', $251 = 'Coffee_Z5', $252 = 'Coffee_Z6', $253 = 'Coffee_Z7', $254 = 'Coffee_Z8', $255 = 'Coffee_Z9', $256 = 'Corn_F0', $257 = 'Corn_F1', $258 = 'Corn_F2', $259 = 'Corn_F3', $260 = 'Corn_F4', $261 = 'Corn_F5', $262 = 'Corn_F6', $263 = 'Corn_F7', $264 = 'Corn_F8', $265 = 'Corn_F9', $266 = 'Corn_G0', $267 = 'Corn_G1', $268 = 'Corn_G2', $269 = 'Corn_G3', $270 = 'Corn_G4', $271 = 'Corn_G5', $272 = 'Corn_G6', $273 = 'Corn_G7', $274 = 'Corn_G8', $275 = 'Corn_G9', $276 = 'Corn_H0', $277 = 'Corn_H1', $278 = 'Corn_H2', $279 = 'Corn_H3', $280 = 'Corn_H4', $281 = 'Corn_H5', $282 = 'Corn_H6', $283 = 'Corn_H7', $284 = 'Corn_H8', $285 = 'Corn_H9', $286 = 'Corn_J0', $287 = 'Corn_J1', $288 = 'Corn_J2', $289 = 'Corn_J3', $290 = 'Corn_J4', $291 = 'Corn_J5', $292 = 'Corn_J6', $293 = 'Corn_J7', $294 = 'Corn_J8', $295 = 'Corn_J9', $296 = 'Corn_K0', $297 = 'Corn_K1', $298 = 'Corn_K2', $299 = 'Corn_K3', $300 = 'Corn_K4', $301 = 'Corn_K5', $302 = 'Corn_K6', $303 = 'Corn_K7', $304 = 'Corn_K8', $305 = 'Corn_K9', $306 = 'Corn_M0', $307 = 'Corn_M1', $308 = 'Corn_M2', $309 = 'Corn_M3', $310 = 'Corn_M4', $311 = 'Corn_M5', $312 = 'Corn_M6', $313 = 'Corn_M7', $314 = 'Corn_M8', $315 = 'Corn_M9', $316 = 'Corn_N0', $317 = 'Corn_N1', $318 = 'Corn_N2', $319 = 'Corn_N3', $320 = 'Corn_N4', $321 = 'Corn_N5', $322 = 'Corn_N6', $323 = 'Corn_N7', $324 = 'Corn_N8', $325 = 'Corn_N9', $326 = 'Corn_Q0', $327 = 'Corn_Q1', $328 = 'Corn_Q2', $329 = 'Corn_Q3', $330 = 'Corn_Q4', $331 = 'Corn_Q5', $332 = 'Corn_Q6', $333 = 'Corn_Q7', $334 = 'Corn_Q8', $335 = 'Corn_Q9', $336 = 'Corn_U0', $337 = 'Corn_U1', $338 = 'Corn_U2', $339 = 'Corn_U3', $340 = 'Corn_U4', $341 = 'Corn_U5', $342 = 'Corn_U6', $343 = 'Corn_U7', $344 = 'Corn_U8', $345 = 'Corn_U9', $346 = 'Corn_V0', $347 = 'Corn_V1', $348 = 'Corn_V2', $349 = 'Corn_V3', $350 = 'Corn_V4', $351 = 'Corn_V5', $352 = 'Corn_V6', $353 = 'Corn_V7', $354 = 'Corn_V8', $355 = 'Corn_V9', $356 = 'Corn_X0', $357 = 'Corn_X1', $358 = 'Corn_X2', $359 = 'Corn_X3', $360 = 'Corn_X4', $361 = 'Corn_X5', $362 = 'Corn_X6', $363 = 'Corn_X7', $364 = 'Corn_X8', $365 = 'Corn_X9', $366 = 'Corn_Z0', $367 = 'Corn_Z1', $368 = 'Corn_Z2', $369 = 'Corn_Z3', $370 = 'Corn_Z4', $371 = 'Corn_Z5', $372 = 'Corn_Z6', $373 = 'Corn_Z7', $374 = 'Corn_Z8', $375 = 'Corn_Z9', $376 = 'DE30', $377 = 'ES35', $378 = 'EURAUD', $379 = 'EURCAD', $380 = 'EURCHF', $381 = 'EURDKK', $382 = 'EURGBP', $383 = 'EURHKD', $384 = 'EURJPY', $385 = 'EURNOK', $386 = 'EURNZD', $387 = 'EURPLN', $388 = 'EURSEK', $389 = 'EURSGD', $390 = 'EURTRY', $391 = 'EURUSD', $392 = 'EURZAR', $393 = 'F40', $394 = 'GBPAUD', $395 = 'GBPCAD', $396 = 'GBPCHF', $397 = 'GBPDKK', $398 = 'GBPJPY', $399 = 'GBPNOK', $400 = 'GBPNZD', $401 = 'GBPSEK', $402 = 'GBPSGD', $403 = 'GBPUSD', $404 = 'HK50', $405 = 'IT40', $406 = 'JP225', $407 = 'NOKJPY', $408 = 'NOKSEK', $409 = 'NZDCAD', $410 = 'NZDCHF', $411 = 'NZDJPY', $412 = 'NZDUSD', $413 = 'SEKJPY', $414 = 'SGDJPY', $415 = 'STOXX50', $416 = 'Soybean_F0', $417 = 'Soybean_F1', $418 = 'Soybean_F2', $419 = 'Soybean_F3', $420 = 'Soybean_F4', $421 = 'Soybean_F5', $422 = 'Soybean_F6', $423 = 'Soybean_F7', $424 = 'Soybean_F8', $425 = 'Soybean_F9', $426 = 'Soybean_G0', $427 = 'Soybean_G1', $428 = 'Soybean_G2', $429 = 'Soybean_G3', $430 = 'Soybean_G4', $431 = 'Soybean_G5', $432 = 'Soybean_G6', $433 = 'Soybean_G7', $434 = 'Soybean_G8', $435 = 'Soybean_G9', $436 = 'Soybean_H0', $437 = 'Soybean_H1', $438 = 'Soybean_H2', $439 = 'Soybean_H3', $440 = 'Soybean_H4', $441 = 'Soybean_H5', $442 = 'Soybean_H6', $443 = 'Soybean_H7', $444 = 'Soybean_H8', $445 = 'Soybean_H9', $446 = 'Soybean_J0', $447 = 'Soybean_J1', $448 = 'Soybean_J2', $449 = 'Soybean_J3', $450 = 'Soybean_J4', $451 = 'Soybean_J5', $452 = 'Soybean_J6', $453 = 'Soybean_J7', $454 = 'Soybean_J8', $455 = 'Soybean_J9', $456 = 'Soybean_K0', $457 = 'Soybean_K1', $458 = 'Soybean_K2', $459 = 'Soybean_K3', $460 = 'Soybean_K4', $461 = 'Soybean_K5', $462 = 'Soybean_K6', $463 = 'Soybean_K7', $464 = 'Soybean_K8', $465 = 'Soybean_K9', $466 = 'Soybean_M0', $467 = 'Soybean_M1', $468 = 'Soybean_M2', $469 = 'Soybean_M3', $470 = 'Soybean_M4', $471 = 'Soybean_M5', $472 = 'Soybean_M6', $473 = 'Soybean_M7', $474 = 'Soybean_M8', $475 = 'Soybean_M9', $476 = 'Soybean_N0', $477 = 'Soybean_N1', $478 = 'Soybean_N2', $479 = 'Soybean_N3', $480 = 'Soybean_N4', $481 = 'Soybean_N5', $482 = 'Soybean_N6', $483 = 'Soybean_N7', $484 = 'Soybean_N8', $485 = 'Soybean_N9', $486 = 'Soybean_Q0', $487 = 'Soybean_Q1', $488 = 'Soybean_Q2', $489 = 'Soybean_Q3', $490 = 'Soybean_Q4', $491 = 'Soybean_Q5', $492 = 'Soybean_Q6', $493 = 'Soybean_Q7', $494 = 'Soybean_Q8', $495 = 'Soybean_Q9', $496 = 'Soybean_U0', $497 = 'Soybean_U1', $498 = 'Soybean_U2', $499 = 'Soybean_U3', $500 = 'Soybean_U4', $501 = 'Soybean_U5', $502 = 'Soybean_U6', $503 = 'Soybean_U7', $504 = 'Soybean_U8', $505 = 'Soybean_U9', $506 = 'Soybean_V0', $507 = 'Soybean_V1', $508 = 'Soybean_V2', $509 = 'Soybean_V3', $510 = 'Soybean_V4', $511 = 'Soybean_V5', $512 = 'Soybean_V6', $513 = 'Soybean_V7', $514 = 'Soybean_V8', $515 = 'Soybean_V9', $516 = 'Soybean_X0', $517 = 'Soybean_X1', $518 = 'Soybean_X2', $519 = 'Soybean_X3', $520 = 'Soybean_X4', $521 = 'Soybean_X5', $522 = 'Soybean_X6', $523 = 'Soybean_X7', $524 = 'Soybean_X8', $525 = 'Soybean_X9', $526 = 'Soybean_Z0', $527 = 'Soybean_Z1', $528 = 'Soybean_Z2', $529 = 'Soybean_Z3', $530 = 'Soybean_Z4', $531 = 'Soybean_Z5', $532 = 'Soybean_Z6', $533 = 'Soybean_Z7', $534 = 'Soybean_Z8', $535 = 'Soybean_Z9', $536 = 'Sugar_F0', $537 = 'Sugar_F1', $538 = 'Sugar_F2', $539 = 'Sugar_F3', $540 = 'Sugar_F4', $541 = 'Sugar_F5', $542 = 'Sugar_F6', $543 = 'Sugar_F7', $544 = 'Sugar_F8', $545 = 'Sugar_F9', $546 = 'Sugar_G0', $547 = 'Sugar_G1', $548 = 'Sugar_G2', $549 = 'Sugar_G3', $550 = 'Sugar_G4', $551 = 'Sugar_G5', $552 = 'Sugar_G6', $553 = 'Sugar_G7', $554 = 'Sugar_G8', $555 = 'Sugar_G9', $556 = 'Sugar_H0', $557 = 'Sugar_H1', $558 = 'Sugar_H2', $559 = 'Sugar_H3', $560 = 'Sugar_H4', $561 = 'Sugar_H5', $562 = 'Sugar_H6', $563 = 'Sugar_H7', $564 = 'Sugar_H8', $565 = 'Sugar_H9', $566 = 'Sugar_J0', $567 = 'Sugar_J1', $568 = 'Sugar_J2', $569 = 'Sugar_J3', $570 = 'Sugar_J4', $571 = 'Sugar_J5', $572 = 'Sugar_J6', $573 = 'Sugar_J7', $574 = 'Sugar_J8', $575 = 'Sugar_J9', $576 = 'Sugar_K0', $577 = 'Sugar_K1', $578 = 'Sugar_K2', $579 = 'Sugar_K3', $580 = 'Sugar_K4', $581 = 'Sugar_K5', $582 = 'Sugar_K6', $583 = 'Sugar_K7', $584 = 'Sugar_K8', $585 = 'Sugar_K9', $586 = 'Sugar_M0', $587 = 'Sugar_M1', $588 = 'Sugar_M2', $589 = 'Sugar_M3', $590 = 'Sugar_M4', $591 = 'Sugar_M5', $592 = 'Sugar_M6', $593 = 'Sugar_M7', $594 = 'Sugar_M8', $595 = 'Sugar_M9', $596 = 'Sugar_N0', $597 = 'Sugar_N1', $598 = 'Sugar_N2', $599 = 'Sugar_N3', $600 = 'Sugar_N4', $601 = 'Sugar_N5', $602 = 'Sugar_N6', $603 = 'Sugar_N7', $604 = 'Sugar_N8', $605 = 'Sugar_N9', $606 = 'Sugar_Q0', $607 = 'Sugar_Q1', $608 = 'Sugar_Q2', $609 = 'Sugar_Q3', $610 = 'Sugar_Q4', $611 = 'Sugar_Q5', $612 = 'Sugar_Q6', $613 = 'Sugar_Q7', $614 = 'Sugar_Q8', $615 = 'Sugar_Q9', $616 = 'Sugar_U0', $617 = 'Sugar_U1', $618 = 'Sugar_U2', $619 = 'Sugar_U3', $620 = 'Sugar_U4', $621 = 'Sugar_U5', $622 = 'Sugar_U6', $623 = 'Sugar_U7', $624 = 'Sugar_U8', $625 = 'Sugar_U9', $626 = 'Sugar_V0', $627 = 'Sugar_V1', $628 = 'Sugar_V2', $629 = 'Sugar_V3', $630 = 'Sugar_V4', $631 = 'Sugar_V5', $632 = 'Sugar_V6', $633 = 'Sugar_V7', $634 = 'Sugar_V8', $635 = 'Sugar_V9', $636 = 'Sugar_X0', $637 = 'Sugar_X1', $638 = 'Sugar_X2', $639 = 'Sugar_X3', $640 = 'Sugar_X4', $641 = 'Sugar_X5', $642 = 'Sugar_X6', $643 = 'Sugar_X7', $644 = 'Sugar_X8', $645 = 'Sugar_X9', $646 = 'Sugar_Z0', $647 = 'Sugar_Z1', $648 = 'Sugar_Z2', $649 = 'Sugar_Z3', $650 = 'Sugar_Z4', $651 = 'Sugar_Z5', $652 = 'Sugar_Z6', $653 = 'Sugar_Z7', $654 = 'Sugar_Z8', $655 = 'Sugar_Z9', $656 = 'UK100', $657 = 'US2000', $658 = 'US30', $659 = 'US500', $660 = 'USDCAD', $661 = 'USDCHF', $662 = 'USDCNH', $663 = 'USDCZK', $664 = 'USDDKK', $665 = 'USDHKD', $666 = 'USDHUF', $667 = 'USDJPY', $668 = 'USDMXN', $669 = 'USDNOK', $670 = 'USDPLN', $671 = 'USDRUB', $672 = 'USDSEK', $673 = 'USDSGD', $674 = 'USDTHB', $675 = 'USDTRY', $676 = 'USDZAR', $677 = 'USTEC', $678 = 'WTI_F0', $679 = 'WTI_F1', $680 = 'WTI_F2', $681 = 'WTI_F3', $682 = 'WTI_F4', $683 = 'WTI_F5', $684 = 'WTI_F6', $685 = 'WTI_F7', $686 = 'WTI_F8', $687 = 'WTI_F9', $688 = 'WTI_G0', $689 = 'WTI_G1', $690 = 'WTI_G2', $691 = 'WTI_G3', $692 = 'WTI_G4', $693 = 'WTI_G5', $694 = 'WTI_G6', $695 = 'WTI_G7', $696 = 'WTI_G8', $697 = 'WTI_G9', $698 = 'WTI_H0', $699 = 'WTI_H1', $700 = 'WTI_H2', $701 = 'WTI_H3', $702 = 'WTI_H4', $703 = 'WTI_H5', $704 = 'WTI_H6', $705 = 'WTI_H7', $706 = 'WTI_H8', $707 = 'WTI_H9', $708 = 'WTI_J0', $709 = 'WTI_J1', $710 = 'WTI_J2', $711 = 'WTI_J3', $712 = 'WTI_J4', $713 = 'WTI_J5', $714 = 'WTI_J6', $715 = 'WTI_J7', $716 = 'WTI_J8', $717 = 'WTI_J9', $718 = 'WTI_K0', $719 = 'WTI_K1', $720 = 'WTI_K2', $721 = 'WTI_K3', $722 = 'WTI_K4', $723 = 'WTI_K5', $724 = 'WTI_K6', $725 = 'WTI_K7', $726 = 'WTI_K8', $727 = 'WTI_K9', $728 = 'WTI_M0', $729 = 'WTI_M1', $730 = 'WTI_M2', $731 = 'WTI_M3', $732 = 'WTI_M4', $733 = 'WTI_M5', $734 = 'WTI_M6', $735 = 'WTI_M7', $736 = 'WTI_M8', $737 = 'WTI_M9', $738 = 'WTI_N0', $739 = 'WTI_N1', $740 = 'WTI_N2', $741 = 'WTI_N3', $742 = 'WTI_N4', $743 = 'WTI_N5', $744 = 'WTI_N6', $745 = 'WTI_N7', $746 = 'WTI_N8', $747 = 'WTI_N9', $748 = 'WTI_Q0', $749 = 'WTI_Q1', $750 = 'WTI_Q2', $751 = 'WTI_Q3', $752 = 'WTI_Q4', $753 = 'WTI_Q5', $754 = 'WTI_Q6', $755 = 'WTI_Q7', $756 = 'WTI_Q8', $757 = 'WTI_Q9', $758 = 'WTI_U0', $759 = 'WTI_U1', $760 = 'WTI_U2', $761 = 'WTI_U3', $762 = 'WTI_U4', $763 = 'WTI_U5', $764 = 'WTI_U6', $765 = 'WTI_U7', $766 = 'WTI_U8', $767 = 'WTI_U9', $768 = 'WTI_V0', $769 = 'WTI_V1', $770 = 'WTI_V2', $771 = 'WTI_V3', $772 = 'WTI_V4', $773 = 'WTI_V5', $774 = 'WTI_V6', $775 = 'WTI_V7', $776 = 'WTI_V8', $777 = 'WTI_V9', $778 = 'WTI_X0', $779 = 'WTI_X1', $780 = 'WTI_X2', $781 = 'WTI_X3', $782 = 'WTI_X4', $783 = 'WTI_X5', $784 = 'WTI_X6', $785 = 'WTI_X7', $786 = 'WTI_X8', $787 = 'WTI_X9', $788 = 'WTI_Z0', $789 = 'WTI_Z1', $790 = 'WTI_Z2', $791 = 'WTI_Z3', $792 = 'WTI_Z4', $793 = 'WTI_Z5', $794 = 'WTI_Z6', $795 = 'WTI_Z7', $796 = 'WTI_Z8', $797 = 'WTI_Z9', $798 = 'Wheat_F0', $799 = 'Wheat_F1', $800 = 'Wheat_F2', $801 = 'Wheat_F3', $802 = 'Wheat_F4', $803 = 'Wheat_F5', $804 = 'Wheat_F6', $805 = 'Wheat_F7', $806 = 'Wheat_F8', $807 = 'Wheat_F9', $808 = 'Wheat_G0', $809 = 'Wheat_G1', $810 = 'Wheat_G2', $811 = 'Wheat_G3', $812 = 'Wheat_G4', $813 = 'Wheat_G5', $814 = 'Wheat_G6', $815 = 'Wheat_G7', $816 = 'Wheat_G8', $817 = 'Wheat_G9', $818 = 'Wheat_H0', $819 = 'Wheat_H1', $820 = 'Wheat_H2', $821 = 'Wheat_H3', $822 = 'Wheat_H4', $823 = 'Wheat_H5', $824 = 'Wheat_H6', $825 = 'Wheat_H7', $826 = 'Wheat_H8', $827 = 'Wheat_H9', $828 = 'Wheat_J0', $829 = 'Wheat_J1', $830 = 'Wheat_J2', $831 = 'Wheat_J3', $832 = 'Wheat_J4', $833 = 'Wheat_J5', $834 = 'Wheat_J6', $835 = 'Wheat_J7', $836 = 'Wheat_J8', $837 = 'Wheat_J9', $838 = 'Wheat_K0', $839 = 'Wheat_K1', $840 = 'Wheat_K2', $841 = 'Wheat_K3', $842 = 'Wheat_K4', $843 = 'Wheat_K5', $844 = 'Wheat_K6', $845 = 'Wheat_K7', $846 = 'Wheat_K8', $847 = 'Wheat_K9', $848 = 'Wheat_M0', $849 = 'Wheat_M1', $850 = 'Wheat_M2', $851 = 'Wheat_M3', $852 = 'Wheat_M4', $853 = 'Wheat_M5', $854 = 'Wheat_M6', $855 = 'Wheat_M7', $856 = 'Wheat_M8', $857 = 'Wheat_M9', $858 = 'Wheat_N0', $859 = 'Wheat_N1', $860 = 'Wheat_N2', $861 = 'Wheat_N3', $862 = 'Wheat_N4', $863 = 'Wheat_N5', $864 = 'Wheat_N6', $865 = 'Wheat_N7', $866 = 'Wheat_N8', $867 = 'Wheat_N9', $868 = 'Wheat_Q0', $869 = 'Wheat_Q1', $870 = 'Wheat_Q2', $871 = 'Wheat_Q3', $872 = 'Wheat_Q4', $873 = 'Wheat_Q5', $874 = 'Wheat_Q6', $875 = 'Wheat_Q7', $876 = 'Wheat_Q8', $877 = 'Wheat_Q9', $878 = 'Wheat_U0', $879 = 'Wheat_U1', $880 = 'Wheat_U2', $881 = 'Wheat_U3', $882 = 'Wheat_U4', $883 = 'Wheat_U5', $884 = 'Wheat_U6', $885 = 'Wheat_U7', $886 = 'Wheat_U8', $887 = 'Wheat_U9', $888 = 'Wheat_V0', $889 = 'Wheat_V1', $890 = 'Wheat_V2', $891 = 'Wheat_V3', $892 = 'Wheat_V4', $893 = 'Wheat_V5', $894 = 'Wheat_V6', $895 = 'Wheat_V7', $896 = 'Wheat_V8', $897 = 'Wheat_V9', $898 = 'Wheat_X0', $899 = 'Wheat_X1', $900 = 'Wheat_X2', $901 = 'Wheat_X3', $902 = 'Wheat_X4', $903 = 'Wheat_X5', $904 = 'Wheat_X6', $905 = 'Wheat_X7', $906 = 'Wheat_X8', $907 = 'Wheat_X9', $908 = 'Wheat_Z0', $909 = 'Wheat_Z1', $910 = 'Wheat_Z2', $911 = 'Wheat_Z3', $912 = 'Wheat_Z4', $913 = 'Wheat_Z5', $914 = 'Wheat_Z6', $915 = 'Wheat_Z7', $916 = 'Wheat_Z8', $917 = 'Wheat_Z9', $918 = 'XAGEUR', $919 = 'XAGUSD', $920 = 'XAUEUR', $921 = 'XAUUSD', $922 = 'XBRUSD', $923 = 'XNGUSD', $924 = 'XPDUSD', $925 = 'XPTUSD', $926 = 'XTIUSD', $927 = 'AUDCAD', $928 = 'AUDCHF', $929 = 'AUDJPY', $930 = 'AUDNZD', $931 = 'AUDSGD', $932 = 'AUDUSD', $933 = 'AUS200', $934 = 'BRENT_F0', $935 = 'BRENT_F1', $936 = 'BRENT_F2', $937 = 'BRENT_F3', $938 = 'BRENT_F4', $939 = 'BRENT_F5', $940 = 'BRENT_F6', $941 = 'BRENT_F7', $942 = 'BRENT_F8', $943 = 'BRENT_F9', $944 = 'BRENT_G0', $945 = 'BRENT_G1', $946 = 'BRENT_G2', $947 = 'BRENT_G3', $948 = 'BRENT_G4', $949 = 'BRENT_G5', $950 = 'BRENT_G6', $951 = 'BRENT_G7', $952 = 'BRENT_G8', $953 = 'BRENT_G9', $954 = 'BRENT_H0', $955 = 'BRENT_H1', $956 = 'BRENT_H2', $957 = 'BRENT_H3', $958 = 'BRENT_H4', $959 = 'BRENT_H5', $960 = 'BRENT_H6', $961 = 'BRENT_H7', $962 = 'BRENT_H8', $963 = 'BRENT_H9', $964 = 'BRENT_J0', $965 = 'BRENT_J1', $966 = 'BRENT_J2', $967 = 'BRENT_J3', $968 = 'BRENT_J4', $969 = 'BRENT_J5', $970 = 'BRENT_J6', $971 = 'BRENT_J7', $972 = 'BRENT_J8', $973 = 'BRENT_J9', $974 = 'BRENT_K0', $975 = 'BRENT_K1', $976 = 'BRENT_K2', $977 = 'BRENT_K3', $978 = 'BRENT_K4', $979 = 'BRENT_K5', $980 = 'BRENT_K6', $981 = 'BRENT_K7', $982 = 'BRENT_K8', $983 = 'BRENT_K9', $984 = 'BRENT_M0', $985 = 'BRENT_M1', $986 = 'BRENT_M2', $987 = 'BRENT_M3', $988 = 'BRENT_M4', $989 = 'BRENT_M5', $990 = 'BRENT_M6', $991 = 'BRENT_M7', $992 = 'BRENT_M8', $993 = 'BRENT_M9', $994 = 'BRENT_N0', $995 = 'BRENT_N1', $996 = 'BRENT_N2', $997 = 'BRENT_N3', $998 = 'BRENT_N4', $999 = 'BRENT_N5', $1000 = 'BRENT_N6', $1001 = 'BRENT_N7', $1002 = 'BRENT_N8', $1003 = 'BRENT_N9', $1004 = 'BRENT_Q0', $1005 = 'BRENT_Q1', $1006 = 'BRENT_Q2', $1007 = 'BRENT_Q3', $1008 = 'BRENT_Q4', $1009 = 'BRENT_Q5', $1010 = 'BRENT_Q6', $1011 = 'BRENT_Q7', $1012 = 'BRENT_Q8', $1013 = 'BRENT_Q9', $1014 = 'BRENT_U0', $1015 = 'BRENT_U1', $1016 = 'BRENT_U2', $1017 = 'BRENT_U3', $1018 = 'BRENT_U4', $1019 = 'BRENT_U5', $1020 = 'BRENT_U6', $1021 = 'BRENT_U7', $1022 = 'BRENT_U8', $1023 = 'BRENT_U9', $1024 = 'BRENT_V0', $1025 = 'BRENT_V1', $1026 = 'BRENT_V2', $1027 = 'BRENT_V3', $1028 = 'BRENT_V4', $1029 = 'BRENT_V5', $1030 = 'BRENT_V6', $1031 = 'BRENT_V7', $1032 = 'BRENT_V8', $1033 = 'BRENT_V9', $1034 = 'BRENT_X0', $1035 = 'BRENT_X1', $1036 = 'BRENT_X2', $1037 = 'BRENT_X3', $1038 = 'BRENT_X4', $1039 = 'BRENT_X5', $1040 = 'BRENT_X6', $1041 = 'BRENT_X7', $1042 = 'BRENT_X8', $1043 = 'BRENT_X9', $1044 = 'BRENT_Z0', $1045 = 'BRENT_Z1', $1046 = 'BRENT_Z2', $1047 = 'BRENT_Z3', $1048 = 'BRENT_Z4', $1049 = 'BRENT_Z5', $1050 = 'BRENT_Z6', $1051 = 'BRENT_Z7', $1052 = 'BRENT_Z8', $1053 = 'BRENT_Z9', $1054 = 'BTCUSD', $1055 = 'CADCHF', $1056 = 'CADJPY', $1057 = 'CHFJPY', $1058 = 'CHFSGD', $1059 = 'CHINA50', $1060 = 'Coffee_F0', $1061 = 'Coffee_F1', $1062 = 'Coffee_F2', $1063 = 'Coffee_F3', $1064 = 'Coffee_F4', $1065 = 'Coffee_F5', $1066 = 'Coffee_F6', $1067 = 'Coffee_F7', $1068 = 'Coffee_F8', $1069 = 'Coffee_F9', $1070 = 'Coffee_G0', $1071 = 'Coffee_G1', $1072 = 'Coffee_G2', $1073 = 'Coffee_G3', $1074 = 'Coffee_G4', $1075 = 'Coffee_G5', $1076 = 'Coffee_G6', $1077 = 'Coffee_G7', $1078 = 'Coffee_G8', $1079 = 'Coffee_G9', $1080 = 'Coffee_H0', $1081 = 'Coffee_H1', $1082 = 'Coffee_H2', $1083 = 'Coffee_H3', $1084 = 'Coffee_H4', $1085 = 'Coffee_H5', $1086 = 'Coffee_H6', $1087 = 'Coffee_H7', $1088 = 'Coffee_H8', $1089 = 'Coffee_H9', $1090 = 'Coffee_J0', $1091 = 'Coffee_J1', $1092 = 'Coffee_J2', $1093 = 'Coffee_J3', $1094 = 'Coffee_J4', $1095 = 'Coffee_J5', $1096 = 'Coffee_J6', $1097 = 'Coffee_J7', $1098 = 'Coffee_J8', $1099 = 'Coffee_J9', $1100 = 'Coffee_K0', $1101 = 'Coffee_K1', $1102 = 'Coffee_K2', $1103 = 'Coffee_K3', $1104 = 'Coffee_K4', $1105 = 'Coffee_K5', $1106 = 'Coffee_K6', $1107 = 'Coffee_K7', $1108 = 'Coffee_K8', $1109 = 'Coffee_K9', $1110 = 'Coffee_M0', $1111 = 'Coffee_M1', $1112 = 'Coffee_M2', $1113 = 'Coffee_M3', $1114 = 'Coffee_M4', $1115 = 'Coffee_M5', $1116 = 'Coffee_M6', $1117 = 'Coffee_M7', $1118 = 'Coffee_M8', $1119 = 'Coffee_M9', $1120 = 'Coffee_N0', $1121 = 'Coffee_N1', $1122 = 'Coffee_N2', $1123 = 'Coffee_N3', $1124 = 'Coffee_N4', $1125 = 'Coffee_N5', $1126 = 'Coffee_N6', $1127 = 'Coffee_N7', $1128 = 'Coffee_N8', $1129 = 'Coffee_N9', $1130 = 'Coffee_Q0', $1131 = 'Coffee_Q1', $1132 = 'Coffee_Q2', $1133 = 'Coffee_Q3', $1134 = 'Coffee_Q4', $1135 = 'Coffee_Q5', $1136 = 'Coffee_Q6', $1137 = 'Coffee_Q7', $1138 = 'Coffee_Q8', $1139 = 'Coffee_Q9', $1140 = 'Coffee_U0', $1141 = 'Coffee_U1', $1142 = 'Coffee_U2', $1143 = 'Coffee_U3', $1144 = 'Coffee_U4', $1145 = 'Coffee_U5', $1146 = 'Coffee_U6', $1147 = 'Coffee_U7', $1148 = 'Coffee_U8', $1149 = 'Coffee_U9', $1150 = 'Coffee_V0', $1151 = 'Coffee_V1', $1152 = 'Coffee_V2', $1153 = 'Coffee_V3', $1154 = 'Coffee_V4', $1155 = 'Coffee_V5', $1156 = 'Coffee_V6', $1157 = 'Coffee_V7', $1158 = 'Coffee_V8', $1159 = 'Coffee_V9', $1160 = 'Coffee_X0', $1161 = 'Coffee_X1', $1162 = 'Coffee_X2', $1163 = 'Coffee_X3', $1164 = 'Coffee_X4', $1165 = 'Coffee_X5', $1166 = 'Coffee_X6', $1167 = 'Coffee_X7', $1168 = 'Coffee_X8', $1169 = 'Coffee_X9', $1170 = 'Coffee_Z0', $1171 = 'Coffee_Z1', $1172 = 'Coffee_Z2', $1173 = 'Coffee_Z3', $1174 = 'Coffee_Z4', $1175 = 'Coffee_Z5', $1176 = 'Coffee_Z6', $1177 = 'Coffee_Z7', $1178 = 'Coffee_Z8', $1179 = 'Coffee_Z9', $1180 = 'Corn_F0', $1181 = 'Corn_F1', $1182 = 'Corn_F2', $1183 = 'Corn_F3', $1184 = 'Corn_F4', $1185 = 'Corn_F5', $1186 = 'Corn_F6', $1187 = 'Corn_F7', $1188 = 'Corn_F8', $1189 = 'Corn_F9', $1190 = 'Corn_G0', $1191 = 'Corn_G1', $1192 = 'Corn_G2', $1193 = 'Corn_G3', $1194 = 'Corn_G4', $1195 = 'Corn_G5', $1196 = 'Corn_G6', $1197 = 'Corn_G7', $1198 = 'Corn_G8', $1199 = 'Corn_G9', $1200 = 'Corn_H0', $1201 = 'Corn_H1', $1202 = 'Corn_H2', $1203 = 'Corn_H3', $1204 = 'Corn_H4', $1205 = 'Corn_H5', $1206 = 'Corn_H6', $1207 = 'Corn_H7', $1208 = 'Corn_H8', $1209 = 'Corn_H9', $1210 = 'Corn_J0', $1211 = 'Corn_J1', $1212 = 'Corn_J2', $1213 = 'Corn_J3', $1214 = 'Corn_J4', $1215 = 'Corn_J5', $1216 = 'Corn_J6', $1217 = 'Corn_J7', $1218 = 'Corn_J8', $1219 = 'Corn_J9', $1220 = 'Corn_K0', $1221 = 'Corn_K1', $1222 = 'Corn_K2', $1223 = 'Corn_K3', $1224 = 'Corn_K4', $1225 = 'Corn_K5', $1226 = 'Corn_K6', $1227 = 'Corn_K7', $1228 = 'Corn_K8', $1229 = 'Corn_K9', $1230 = 'Corn_M0', $1231 = 'Corn_M1', $1232 = 'Corn_M2', $1233 = 'Corn_M3', $1234 = 'Corn_M4', $1235 = 'Corn_M5', $1236 = 'Corn_M6', $1237 = 'Corn_M7', $1238 = 'Corn_M8', $1239 = 'Corn_M9', $1240 = 'Corn_N0', $1241 = 'Corn_N1', $1242 = 'Corn_N2', $1243 = 'Corn_N3', $1244 = 'Corn_N4', $1245 = 'Corn_N5', $1246 = 'Corn_N6', $1247 = 'Corn_N7', $1248 = 'Corn_N8', $1249 = 'Corn_N9', $1250 = 'Corn_Q0', $1251 = 'Corn_Q1', $1252 = 'Corn_Q2', $1253 = 'Corn_Q3', $1254 = 'Corn_Q4', $1255 = 'Corn_Q5', $1256 = 'Corn_Q6', $1257 = 'Corn_Q7', $1258 = 'Corn_Q8', $1259 = 'Corn_Q9', $1260 = 'Corn_U0', $1261 = 'Corn_U1', $1262 = 'Corn_U2', $1263 = 'Corn_U3', $1264 = 'Corn_U4', $1265 = 'Corn_U5', $1266 = 'Corn_U6', $1267 = 'Corn_U7', $1268 = 'Corn_U8', $1269 = 'Corn_U9', $1270 = 'Corn_V0', $1271 = 'Corn_V1', $1272 = 'Corn_V2', $1273 = 'Corn_V3', $1274 = 'Corn_V4', $1275 = 'Corn_V5', $1276 = 'Corn_V6', $1277 = 'Corn_V7', $1278 = 'Corn_V8', $1279 = 'Corn_V9', $1280 = 'Corn_X0', $1281 = 'Corn_X1', $1282 = 'Corn_X2', $1283 = 'Corn_X3', $1284 = 'Corn_X4', $1285 = 'Corn_X5', $1286 = 'Corn_X6', $1287 = 'Corn_X7', $1288 = 'Corn_X8', $1289 = 'Corn_X9', $1290 = 'Corn_Z0', $1291 = 'Corn_Z1', $1292 = 'Corn_Z2', $1293 = 'Corn_Z3', $1294 = 'Corn_Z4', $1295 = 'Corn_Z5', $1296 = 'Corn_Z6', $1297 = 'Corn_Z7', $1298 = 'Corn_Z8', $1299 = 'Corn_Z9', $1300 = 'DE30', $1301 = 'ES35', $1302 = 'EURAUD', $1303 = 'EURCAD', $1304 = 'EURCHF', $1305 = 'EURDKK', $1306 = 'EURGBP', $1307 = 'EURHKD', $1308 = 'EURJPY', $1309 = 'EURNOK', $1310 = 'EURNZD', $1311 = 'EURPLN', $1312 = 'EURSEK', $1313 = 'EURSGD', $1314 = 'EURTRY', $1315 = 'EURUSD', $1316 = 'EURZAR', $1317 = 'F40', $1318 = 'GBPAUD', $1319 = 'GBPCAD', $1320 = 'GBPCHF', $1321 = 'GBPDKK', $1322 = 'GBPJPY', $1323 = 'GBPNOK', $1324 = 'GBPNZD', $1325 = 'GBPSEK', $1326 = 'GBPSGD', $1327 = 'GBPUSD', $1328 = 'HK50', $1329 = 'IT40', $1330 = 'JP225', $1331 = 'NOKJPY', $1332 = 'NOKSEK', $1333 = 'NZDCAD', $1334 = 'NZDCHF', $1335 = 'NZDJPY', $1336 = 'NZDUSD', $1337 = 'SEKJPY', $1338 = 'SGDJPY', $1339 = 'STOXX50', $1340 = 'Soybean_F0', $1341 = 'Soybean_F1', $1342 = 'Soybean_F2', $1343 = 'Soybean_F3', $1344 = 'Soybean_F4', $1345 = 'Soybean_F5', $1346 = 'Soybean_F6', $1347 = 'Soybean_F7', $1348 = 'Soybean_F8', $1349 = 'Soybean_F9', $1350 = 'Soybean_G0', $1351 = 'Soybean_G1', $1352 = 'Soybean_G2', $1353 = 'Soybean_G3', $1354 = 'Soybean_G4', $1355 = 'Soybean_G5', $1356 = 'Soybean_G6', $1357 = 'Soybean_G7', $1358 = 'Soybean_G8', $1359 = 'Soybean_G9', $1360 = 'Soybean_H0', $1361 = 'Soybean_H1', $1362 = 'Soybean_H2', $1363 = 'Soybean_H3', $1364 = 'Soybean_H4', $1365 = 'Soybean_H5', $1366 = 'Soybean_H6', $1367 = 'Soybean_H7', $1368 = 'Soybean_H8', $1369 = 'Soybean_H9', $1370 = 'Soybean_J0', $1371 = 'Soybean_J1', $1372 = 'Soybean_J2', $1373 = 'Soybean_J3', $1374 = 'Soybean_J4', $1375 = 'Soybean_J5', $1376 = 'Soybean_J6', $1377 = 'Soybean_J7', $1378 = 'Soybean_J8', $1379 = 'Soybean_J9', $1380 = 'Soybean_K0', $1381 = 'Soybean_K1', $1382 = 'Soybean_K2', $1383 = 'Soybean_K3', $1384 = 'Soybean_K4', $1385 = 'Soybean_K5', $1386 = 'Soybean_K6', $1387 = 'Soybean_K7', $1388 = 'Soybean_K8', $1389 = 'Soybean_K9', $1390 = 'Soybean_M0', $1391 = 'Soybean_M1', $1392 = 'Soybean_M2', $1393 = 'Soybean_M3', $1394 = 'Soybean_M4', $1395 = 'Soybean_M5', $1396 = 'Soybean_M6', $1397 = 'Soybean_M7', $1398 = 'Soybean_M8', $1399 = 'Soybean_M9', $1400 = 'Soybean_N0', $1401 = 'Soybean_N1', $1402 = 'Soybean_N2', $1403 = 'Soybean_N3', $1404 = 'Soybean_N4', $1405 = 'Soybean_N5', $1406 = 'Soybean_N6', $1407 = 'Soybean_N7', $1408 = 'Soybean_N8', $1409 = 'Soybean_N9', $1410 = 'Soybean_Q0', $1411 = 'Soybean_Q1', $1412 = 'Soybean_Q2', $1413 = 'Soybean_Q3', $1414 = 'Soybean_Q4', $1415 = 'Soybean_Q5', $1416 = 'Soybean_Q6', $1417 = 'Soybean_Q7', $1418 = 'Soybean_Q8', $1419 = 'Soybean_Q9', $1420 = 'Soybean_U0', $1421 = 'Soybean_U1', $1422 = 'Soybean_U2', $1423 = 'Soybean_U3', $1424 = 'Soybean_U4', $1425 = 'Soybean_U5', $1426 = 'Soybean_U6', $1427 = 'Soybean_U7', $1428 = 'Soybean_U8', $1429 = 'Soybean_U9', $1430 = 'Soybean_V0', $1431 = 'Soybean_V1', $1432 = 'Soybean_V2', $1433 = 'Soybean_V3', $1434 = 'Soybean_V4', $1435 = 'Soybean_V5', $1436 = 'Soybean_V6', $1437 = 'Soybean_V7', $1438 = 'Soybean_V8', $1439 = 'Soybean_V9', $1440 = 'Soybean_X0', $1441 = 'Soybean_X1', $1442 = 'Soybean_X2', $1443 = 'Soybean_X3', $1444 = 'Soybean_X4', $1445 = 'Soybean_X5', $1446 = 'Soybean_X6', $1447 = 'Soybean_X7', $1448 = 'Soybean_X8', $1449 = 'Soybean_X9', $1450 = 'Soybean_Z0', $1451 = 'Soybean_Z1', $1452 = 'Soybean_Z2', $1453 = 'Soybean_Z3', $1454 = 'Soybean_Z4', $1455 = 'Soybean_Z5', $1456 = 'Soybean_Z6', $1457 = 'Soybean_Z7', $1458 = 'Soybean_Z8', $1459 = 'Soybean_Z9', $1460 = 'Sugar_F0', $1461 = 'Sugar_F1', $1462 = 'Sugar_F2', $1463 = 'Sugar_F3', $1464 = 'Sugar_F4', $1465 = 'Sugar_F5', $1466 = 'Sugar_F6', $1467 = 'Sugar_F7', $1468 = 'Sugar_F8', $1469 = 'Sugar_F9', $1470 = 'Sugar_G0', $1471 = 'Sugar_G1', $1472 = 'Sugar_G2', $1473 = 'Sugar_G3', $1474 = 'Sugar_G4', $1475 = 'Sugar_G5', $1476 = 'Sugar_G6', $1477 = 'Sugar_G7', $1478 = 'Sugar_G8', $1479 = 'Sugar_G9', $1480 = 'Sugar_H0', $1481 = 'Sugar_H1', $1482 = 'Sugar_H2', $1483 = 'Sugar_H3', $1484 = 'Sugar_H4', $1485 = 'Sugar_H5', $1486 = 'Sugar_H6', $1487 = 'Sugar_H7', $1488 = 'Sugar_H8', $1489 = 'Sugar_H9', $1490 = 'Sugar_J0', $1491 = 'Sugar_J1', $1492 = 'Sugar_J2', $1493 = 'Sugar_J3', $1494 = 'Sugar_J4', $1495 = 'Sugar_J5', $1496 = 'Sugar_J6', $1497 = 'Sugar_J7', $1498 = 'Sugar_J8', $1499 = 'Sugar_J9', $1500 = 'Sugar_K0', $1501 = 'Sugar_K1', $1502 = 'Sugar_K2', $1503 = 'Sugar_K3', $1504 = 'Sugar_K4', $1505 = 'Sugar_K5', $1506 = 'Sugar_K6', $1507 = 'Sugar_K7', $1508 = 'Sugar_K8', $1509 = 'Sugar_K9', $1510 = 'Sugar_M0', $1511 = 'Sugar_M1', $1512 = 'Sugar_M2', $1513 = 'Sugar_M3', $1514 = 'Sugar_M4', $1515 = 'Sugar_M5', $1516 = 'Sugar_M6', $1517 = 'Sugar_M7', $1518 = 'Sugar_M8', $1519 = 'Sugar_M9', $1520 = 'Sugar_N0', $1521 = 'Sugar_N1', $1522 = 'Sugar_N2', $1523 = 'Sugar_N3', $1524 = 'Sugar_N4', $1525 = 'Sugar_N5', $1526 = 'Sugar_N6', $1527 = 'Sugar_N7', $1528 = 'Sugar_N8', $1529 = 'Sugar_N9', $1530 = 'Sugar_Q0', $1531 = 'Sugar_Q1', $1532 = 'Sugar_Q2', $1533 = 'Sugar_Q3', $1534 = 'Sugar_Q4', $1535 = 'Sugar_Q5', $1536 = 'Sugar_Q6', $1537 = 'Sugar_Q7', $1538 = 'Sugar_Q8', $1539 = 'Sugar_Q9', $1540 = 'Sugar_U0', $1541 = 'Sugar_U1', $1542 = 'Sugar_U2', $1543 = 'Sugar_U3', $1544 = 'Sugar_U4', $1545 = 'Sugar_U5', $1546 = 'Sugar_U6', $1547 = 'Sugar_U7', $1548 = 'Sugar_U8', $1549 = 'Sugar_U9', $1550 = 'Sugar_V0', $1551 = 'Sugar_V1', $1552 = 'Sugar_V2', $1553 = 'Sugar_V3', $1554 = 'Sugar_V4', $1555 = 'Sugar_V5', $1556 = 'Sugar_V6', $1557 = 'Sugar_V7', $1558 = 'Sugar_V8', $1559 = 'Sugar_V9', $1560 = 'Sugar_X0', $1561 = 'Sugar_X1', $1562 = 'Sugar_X2', $1563 = 'Sugar_X3', $1564 = 'Sugar_X4', $1565 = 'Sugar_X5', $1566 = 'Sugar_X6', $1567 = 'Sugar_X7', $1568 = 'Sugar_X8', $1569 = 'Sugar_X9', $1570 = 'Sugar_Z0', $1571 = 'Sugar_Z1', $1572 = 'Sugar_Z2', $1573 = 'Sugar_Z3', $1574 = 'Sugar_Z4', $1575 = 'Sugar_Z5', $1576 = 'Sugar_Z6', $1577 = 'Sugar_Z7', $1578 = 'Sugar_Z8', $1579 = 'Sugar_Z9', $1580 = 'UK100', $1581 = 'US2000', $1582 = 'US30', $1583 = 'US500', $1584 = 'USDCAD', $1585 = 'USDCHF', $1586 = 'USDCNH', $1587 = 'USDCZK', $1588 = 'USDDKK', $1589 = 'USDHKD', $1590 = 'USDHUF', $1591 = 'USDJPY', $1592 = 'USDMXN', $1593 = 'USDNOK', $1594 = 'USDPLN', $1595 = 'USDRUB', $1596 = 'USDSEK', $1597 = 'USDSGD', $1598 = 'USDTHB', $1599 = 'USDTRY', $1600 = 'USDZAR', $1601 = 'USTEC', $1602 = 'WTI_F0', $1603 = 'WTI_F1', $1604 = 'WTI_F2', $1605 = 'WTI_F3', $1606 = 'WTI_F4', $1607 = 'WTI_F5', $1608 = 'WTI_F6', $1609 = 'WTI_F7', $1610 = 'WTI_F8', $1611 = 'WTI_F9', $1612 = 'WTI_G0', $1613 = 'WTI_G1', $1614 = 'WTI_G2', $1615 = 'WTI_G3', $1616 = 'WTI_G4', $1617 = 'WTI_G5', $1618 = 'WTI_G6', $1619 = 'WTI_G7', $1620 = 'WTI_G8', $1621 = 'WTI_G9', $1622 = 'WTI_H0', $1623 = 'WTI_H1', $1624 = 'WTI_H2', $1625 = 'WTI_H3', $1626 = 'WTI_H4', $1627 = 'WTI_H5', $1628 = 'WTI_H6', $1629 = 'WTI_H7', $1630 = 'WTI_H8', $1631 = 'WTI_H9', $1632 = 'WTI_J0', $1633 = 'WTI_J1', $1634 = 'WTI_J2', $1635 = 'WTI_J3', $1636 = 'WTI_J4', $1637 = 'WTI_J5', $1638 = 'WTI_J6', $1639 = 'WTI_J7', $1640 = 'WTI_J8', $1641 = 'WTI_J9', $1642 = 'WTI_K0', $1643 = 'WTI_K1', $1644 = 'WTI_K2', $1645 = 'WTI_K3', $1646 = 'WTI_K4', $1647 = 'WTI_K5', $1648 = 'WTI_K6', $1649 = 'WTI_K7', $1650 = 'WTI_K8', $1651 = 'WTI_K9', $1652 = 'WTI_M0', $1653 = 'WTI_M1', $1654 = 'WTI_M2', $1655 = 'WTI_M3', $1656 = 'WTI_M4', $1657 = 'WTI_M5', $1658 = 'WTI_M6', $1659 = 'WTI_M7', $1660 = 'WTI_M8', $1661 = 'WTI_M9', $1662 = 'WTI_N0', $1663 = 'WTI_N1', $1664 = 'WTI_N2', $1665 = 'WTI_N3', $1666 = 'WTI_N4', $1667 = 'WTI_N5', $1668 = 'WTI_N6', $1669 = 'WTI_N7', $1670 = 'WTI_N8', $1671 = 'WTI_N9', $1672 = 'WTI_Q0', $1673 = 'WTI_Q1', $1674 = 'WTI_Q2', $1675 = 'WTI_Q3', $1676 = 'WTI_Q4', $1677 = 'WTI_Q5', $1678 = 'WTI_Q6', $1679 = 'WTI_Q7', $1680 = 'WTI_Q8', $1681 = 'WTI_Q9', $1682 = 'WTI_U0', $1683 = 'WTI_U1', $1684 = 'WTI_U2', $1685 = 'WTI_U3', $1686 = 'WTI_U4', $1687 = 'WTI_U5', $1688 = 'WTI_U6', $1689 = 'WTI_U7', $1690 = 'WTI_U8', $1691 = 'WTI_U9', $1692 = 'WTI_V0', $1693 = 'WTI_V1', $1694 = 'WTI_V2', $1695 = 'WTI_V3', $1696 = 'WTI_V4', $1697 = 'WTI_V5', $1698 = 'WTI_V6', $1699 = 'WTI_V7', $1700 = 'WTI_V8', $1701 = 'WTI_V9', $1702 = 'WTI_X0', $1703 = 'WTI_X1', $1704 = 'WTI_X2', $1705 = 'WTI_X3', $1706 = 'WTI_X4', $1707 = 'WTI_X5', $1708 = 'WTI_X6', $1709 = 'WTI_X7', $1710 = 'WTI_X8', $1711 = 'WTI_X9', $1712 = 'WTI_Z0', $1713 = 'WTI_Z1', $1714 = 'WTI_Z2', $1715 = 'WTI_Z3', $1716 = 'WTI_Z4', $1717 = 'WTI_Z5', $1718 = 'WTI_Z6', $1719 = 'WTI_Z7', $1720 = 'WTI_Z8', $1721 = 'WTI_Z9', $1722 = 'Wheat_F0', $1723 = 'Wheat_F1', $1724 = 'Wheat_F2', $1725 = 'Wheat_F3', $1726 = 'Wheat_F4', $1727 = 'Wheat_F5', $1728 = 'Wheat_F6', $1729 = 'Wheat_F7', $1730 = 'Wheat_F8', $1731 = 'Wheat_F9', $1732 = 'Wheat_G0', $1733 = 'Wheat_G1', $1734 = 'Wheat_G2', $1735 = 'Wheat_G3', $1736 = 'Wheat_G4', $1737 = 'Wheat_G5', $1738 = 'Wheat_G6', $1739 = 'Wheat_G7', $1740 = 'Wheat_G8', $1741 = 'Wheat_G9', $1742 = 'Wheat_H0', $1743 = 'Wheat_H1', $1744 = 'Wheat_H2', $1745 = 'Wheat_H3', $1746 = 'Wheat_H4', $1747 = 'Wheat_H5', $1748 = 'Wheat_H6', $1749 = 'Wheat_H7', $1750 = 'Wheat_H8', $1751 = 'Wheat_H9', $1752 = 'Wheat_J0', $1753 = 'Wheat_J1', $1754 = 'Wheat_J2', $1755 = 'Wheat_J3', $1756 = 'Wheat_J4', $1757 = 'Wheat_J5', $1758 = 'Wheat_J6', $1759 = 'Wheat_J7', $1760 = 'Wheat_J8', $1761 = 'Wheat_J9', $1762 = 'Wheat_K0', $1763 = 'Wheat_K1', $1764 = 'Wheat_K2', $1765 = 'Wheat_K3', $1766 = 'Wheat_K4', $1767 = 'Wheat_K5', $1768 = 'Wheat_K6', $1769 = 'Wheat_K7', $1770 = 'Wheat_K8', $1771 = 'Wheat_K9', $1772 = 'Wheat_M0', $1773 = 'Wheat_M1', $1774 = 'Wheat_M2', $1775 = 'Wheat_M3', $1776 = 'Wheat_M4', $1777 = 'Wheat_M5', $1778 = 'Wheat_M6', $1779 = 'Wheat_M7', $1780 = 'Wheat_M8', $1781 = 'Wheat_M9', $1782 = 'Wheat_N0', $1783 = 'Wheat_N1', $1784 = 'Wheat_N2', $1785 = 'Wheat_N3', $1786 = 'Wheat_N4', $1787 = 'Wheat_N5', $1788 = 'Wheat_N6', $1789 = 'Wheat_N7', $1790 = 'Wheat_N8', $1791 = 'Wheat_N9', $1792 = 'Wheat_Q0', $1793 = 'Wheat_Q1', $1794 = 'Wheat_Q2', $1795 = 'Wheat_Q3', $1796 = 'Wheat_Q4', $1797 = 'Wheat_Q5', $1798 = 'Wheat_Q6', $1799 = 'Wheat_Q7', $1800 = 'Wheat_Q8', $1801 = 'Wheat_Q9', $1802 = 'Wheat_U0', $1803 = 'Wheat_U1', $1804 = 'Wheat_U2', $1805 = 'Wheat_U3', $1806 = 'Wheat_U4', $1807 = 'Wheat_U5', $1808 = 'Wheat_U6', $1809 = 'Wheat_U7', $1810 = 'Wheat_U8', $1811 = 'Wheat_U9', $1812 = 'Wheat_V0', $1813 = 'Wheat_V1', $1814 = 'Wheat_V2', $1815 = 'Wheat_V3', $1816 = 'Wheat_V4', $1817 = 'Wheat_V5', $1818 = 'Wheat_V6', $1819 = 'Wheat_V7', $1820 = 'Wheat_V8', $1821 = 'Wheat_V9', $1822 = 'Wheat_X0', $1823 = 'Wheat_X1', $1824 = 'Wheat_X2', $1825 = 'Wheat_X3', $1826 = 'Wheat_X4', $1827 = 'Wheat_X5', $1828 = 'Wheat_X6', $1829 = 'Wheat_X7', $1830 = 'Wheat_X8', $1831 = 'Wheat_X9', $1832 = 'Wheat_Z0', $1833 = 'Wheat_Z1', $1834 = 'Wheat_Z2', $1835 = 'Wheat_Z3', $1836 = 'Wheat_Z4', $1837 = 'Wheat_Z5', $1838 = 'Wheat_Z6', $1839 = 'Wheat_Z7', $1840 = 'Wheat_Z8', $1841 = 'Wheat_Z9', $1842 = 'XAGEUR', $1843 = 'XAGUSD', $1844 = 'XAUEUR', $1845 = 'XAUUSD', $1846 = 'XBRUSD', $1847 = 'XNGUSD', $1848 = 'XPDUSD', $1849 = 'XPTUSD', $1850 = 'XTIUSD'
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-09-17 13:14:42 Duration: 33ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.164 parameters: $1 = '974', $2 = 'ICMARKETS-AU-MT5', $3 = 'AUDCAD', $4 = 'AUDCHF', $5 = 'AUDJPY', $6 = 'AUDNZD', $7 = 'AUDSGD', $8 = 'AUDUSD', $9 = 'AUS200', $10 = 'BRENT_F0', $11 = 'BRENT_F1', $12 = 'BRENT_F2', $13 = 'BRENT_F3', $14 = 'BRENT_F4', $15 = 'BRENT_F5', $16 = 'BRENT_F6', $17 = 'BRENT_F7', $18 = 'BRENT_F8', $19 = 'BRENT_F9', $20 = 'BRENT_G0', $21 = 'BRENT_G1', $22 = 'BRENT_G2', $23 = 'BRENT_G3', $24 = 'BRENT_G4', $25 = 'BRENT_G5', $26 = 'BRENT_G6', $27 = 'BRENT_G7', $28 = 'BRENT_G8', $29 = 'BRENT_G9', $30 = 'BRENT_H0', $31 = 'BRENT_H1', $32 = 'BRENT_H2', $33 = 'BRENT_H3', $34 = 'BRENT_H4', $35 = 'BRENT_H5', $36 = 'BRENT_H6', $37 = 'BRENT_H7', $38 = 'BRENT_H8', $39 = 'BRENT_H9', $40 = 'BRENT_J0', $41 = 'BRENT_J1', $42 = 'BRENT_J2', $43 = 'BRENT_J3', $44 = 'BRENT_J4', $45 = 'BRENT_J5', $46 = 'BRENT_J6', $47 = 'BRENT_J7', $48 = 'BRENT_J8', $49 = 'BRENT_J9', $50 = 'BRENT_K0', $51 = 'BRENT_K1', $52 = 'BRENT_K2', $53 = 'BRENT_K3', $54 = 'BRENT_K4', $55 = 'BRENT_K5', $56 = 'BRENT_K6', $57 = 'BRENT_K7', $58 = 'BRENT_K8', $59 = 'BRENT_K9', $60 = 'BRENT_M0', $61 = 'BRENT_M1', $62 = 'BRENT_M2', $63 = 'BRENT_M3', $64 = 'BRENT_M4', $65 = 'BRENT_M5', $66 = 'BRENT_M6', $67 = 'BRENT_M7', $68 = 'BRENT_M8', $69 = 'BRENT_M9', $70 = 'BRENT_N0', $71 = 'BRENT_N1', $72 = 'BRENT_N2', $73 = 'BRENT_N3', $74 = 'BRENT_N4', $75 = 'BRENT_N5', $76 = 'BRENT_N6', $77 = 'BRENT_N7', $78 = 'BRENT_N8', $79 = 'BRENT_N9', $80 = 'BRENT_Q0', $81 = 'BRENT_Q1', $82 = 'BRENT_Q2', $83 = 'BRENT_Q3', $84 = 'BRENT_Q4', $85 = 'BRENT_Q5', $86 = 'BRENT_Q6', $87 = 'BRENT_Q7', $88 = 'BRENT_Q8', $89 = 'BRENT_Q9', $90 = 'BRENT_U0', $91 = 'BRENT_U1', $92 = 'BRENT_U2', $93 = 'BRENT_U3', $94 = 'BRENT_U4', $95 = 'BRENT_U5', $96 = 'BRENT_U6', $97 = 'BRENT_U7', $98 = 'BRENT_U8', $99 = 'BRENT_U9', $100 = 'BRENT_V0', $101 = 'BRENT_V1', $102 = 'BRENT_V2', $103 = 'BRENT_V3', $104 = 'BRENT_V4', $105 = 'BRENT_V5', $106 = 'BRENT_V6', $107 = 'BRENT_V7', $108 = 'BRENT_V8', $109 = 'BRENT_V9', $110 = 'BRENT_X0', $111 = 'BRENT_X1', $112 = 'BRENT_X2', $113 = 'BRENT_X3', $114 = 'BRENT_X4', $115 = 'BRENT_X5', $116 = 'BRENT_X6', $117 = 'BRENT_X7', $118 = 'BRENT_X8', $119 = 'BRENT_X9', $120 = 'BRENT_Z0', $121 = 'BRENT_Z1', $122 = 'BRENT_Z2', $123 = 'BRENT_Z3', $124 = 'BRENT_Z4', $125 = 'BRENT_Z5', $126 = 'BRENT_Z6', $127 = 'BRENT_Z7', $128 = 'BRENT_Z8', $129 = 'BRENT_Z9', $130 = 'BTCUSD', $131 = 'CADCHF', $132 = 'CADJPY', $133 = 'CHFJPY', $134 = 'CHFSGD', $135 = 'CHINA50', $136 = 'Coffee_F0', $137 = 'Coffee_F1', $138 = 'Coffee_F2', $139 = 'Coffee_F3', $140 = 'Coffee_F4', $141 = 'Coffee_F5', $142 = 'Coffee_F6', $143 = 'Coffee_F7', $144 = 'Coffee_F8', $145 = 'Coffee_F9', $146 = 'Coffee_G0', $147 = 'Coffee_G1', $148 = 'Coffee_G2', $149 = 'Coffee_G3', $150 = 'Coffee_G4', $151 = 'Coffee_G5', $152 = 'Coffee_G6', $153 = 'Coffee_G7', $154 = 'Coffee_G8', $155 = 'Coffee_G9', $156 = 'Coffee_H0', $157 = 'Coffee_H1', $158 = 'Coffee_H2', $159 = 'Coffee_H3', $160 = 'Coffee_H4', $161 = 'Coffee_H5', $162 = 'Coffee_H6', $163 = 'Coffee_H7', $164 = 'Coffee_H8', $165 = 'Coffee_H9', $166 = 'Coffee_J0', $167 = 'Coffee_J1', $168 = 'Coffee_J2', $169 = 'Coffee_J3', $170 = 'Coffee_J4', $171 = 'Coffee_J5', $172 = 'Coffee_J6', $173 = 'Coffee_J7', $174 = 'Coffee_J8', $175 = 'Coffee_J9', $176 = 'Coffee_K0', $177 = 'Coffee_K1', $178 = 'Coffee_K2', $179 = 'Coffee_K3', $180 = 'Coffee_K4', $181 = 'Coffee_K5', $182 = 'Coffee_K6', $183 = 'Coffee_K7', $184 = 'Coffee_K8', $185 = 'Coffee_K9', $186 = 'Coffee_M0', $187 = 'Coffee_M1', $188 = 'Coffee_M2', $189 = 'Coffee_M3', $190 = 'Coffee_M4', $191 = 'Coffee_M5', $192 = 'Coffee_M6', $193 = 'Coffee_M7', $194 = 'Coffee_M8', $195 = 'Coffee_M9', $196 = 'Coffee_N0', $197 = 'Coffee_N1', $198 = 'Coffee_N2', $199 = 'Coffee_N3', $200 = 'Coffee_N4', $201 = 'Coffee_N5', $202 = 'Coffee_N6', $203 = 'Coffee_N7', $204 = 'Coffee_N8', $205 = 'Coffee_N9', $206 = 'Coffee_Q0', $207 = 'Coffee_Q1', $208 = 'Coffee_Q2', $209 = 'Coffee_Q3', $210 = 'Coffee_Q4', $211 = 'Coffee_Q5', $212 = 'Coffee_Q6', $213 = 'Coffee_Q7', $214 = 'Coffee_Q8', $215 = 'Coffee_Q9', $216 = 'Coffee_U0', $217 = 'Coffee_U1', $218 = 'Coffee_U2', $219 = 'Coffee_U3', $220 = 'Coffee_U4', $221 = 'Coffee_U5', $222 = 'Coffee_U6', $223 = 'Coffee_U7', $224 = 'Coffee_U8', $225 = 'Coffee_U9', $226 = 'Coffee_V0', $227 = 'Coffee_V1', $228 = 'Coffee_V2', $229 = 'Coffee_V3', $230 = 'Coffee_V4', $231 = 'Coffee_V5', $232 = 'Coffee_V6', $233 = 'Coffee_V7', $234 = 'Coffee_V8', $235 = 'Coffee_V9', $236 = 'Coffee_X0', $237 = 'Coffee_X1', $238 = 'Coffee_X2', $239 = 'Coffee_X3', $240 = 'Coffee_X4', $241 = 'Coffee_X5', $242 = 'Coffee_X6', $243 = 'Coffee_X7', $244 = 'Coffee_X8', $245 = 'Coffee_X9', $246 = 'Coffee_Z0', $247 = 'Coffee_Z1', $248 = 'Coffee_Z2', $249 = 'Coffee_Z3', $250 = 'Coffee_Z4', $251 = 'Coffee_Z5', $252 = 'Coffee_Z6', $253 = 'Coffee_Z7', $254 = 'Coffee_Z8', $255 = 'Coffee_Z9', $256 = 'Corn_F0', $257 = 'Corn_F1', $258 = 'Corn_F2', $259 = 'Corn_F3', $260 = 'Corn_F4', $261 = 'Corn_F5', $262 = 'Corn_F6', $263 = 'Corn_F7', $264 = 'Corn_F8', $265 = 'Corn_F9', $266 = 'Corn_G0', $267 = 'Corn_G1', $268 = 'Corn_G2', $269 = 'Corn_G3', $270 = 'Corn_G4', $271 = 'Corn_G5', $272 = 'Corn_G6', $273 = 'Corn_G7', $274 = 'Corn_G8', $275 = 'Corn_G9', $276 = 'Corn_H0', $277 = 'Corn_H1', $278 = 'Corn_H2', $279 = 'Corn_H3', $280 = 'Corn_H4', $281 = 'Corn_H5', $282 = 'Corn_H6', $283 = 'Corn_H7', $284 = 'Corn_H8', $285 = 'Corn_H9', $286 = 'Corn_J0', $287 = 'Corn_J1', $288 = 'Corn_J2', $289 = 'Corn_J3', $290 = 'Corn_J4', $291 = 'Corn_J5', $292 = 'Corn_J6', $293 = 'Corn_J7', $294 = 'Corn_J8', $295 = 'Corn_J9', $296 = 'Corn_K0', $297 = 'Corn_K1', $298 = 'Corn_K2', $299 = 'Corn_K3', $300 = 'Corn_K4', $301 = 'Corn_K5', $302 = 'Corn_K6', $303 = 'Corn_K7', $304 = 'Corn_K8', $305 = 'Corn_K9', $306 = 'Corn_M0', $307 = 'Corn_M1', $308 = 'Corn_M2', $309 = 'Corn_M3', $310 = 'Corn_M4', $311 = 'Corn_M5', $312 = 'Corn_M6', $313 = 'Corn_M7', $314 = 'Corn_M8', $315 = 'Corn_M9', $316 = 'Corn_N0', $317 = 'Corn_N1', $318 = 'Corn_N2', $319 = 'Corn_N3', $320 = 'Corn_N4', $321 = 'Corn_N5', $322 = 'Corn_N6', $323 = 'Corn_N7', $324 = 'Corn_N8', $325 = 'Corn_N9', $326 = 'Corn_Q0', $327 = 'Corn_Q1', $328 = 'Corn_Q2', $329 = 'Corn_Q3', $330 = 'Corn_Q4', $331 = 'Corn_Q5', $332 = 'Corn_Q6', $333 = 'Corn_Q7', $334 = 'Corn_Q8', $335 = 'Corn_Q9', $336 = 'Corn_U0', $337 = 'Corn_U1', $338 = 'Corn_U2', $339 = 'Corn_U3', $340 = 'Corn_U4', $341 = 'Corn_U5', $342 = 'Corn_U6', $343 = 'Corn_U7', $344 = 'Corn_U8', $345 = 'Corn_U9', $346 = 'Corn_V0', $347 = 'Corn_V1', $348 = 'Corn_V2', $349 = 'Corn_V3', $350 = 'Corn_V4', $351 = 'Corn_V5', $352 = 'Corn_V6', $353 = 'Corn_V7', $354 = 'Corn_V8', $355 = 'Corn_V9', $356 = 'Corn_X0', $357 = 'Corn_X1', $358 = 'Corn_X2', $359 = 'Corn_X3', $360 = 'Corn_X4', $361 = 'Corn_X5', $362 = 'Corn_X6', $363 = 'Corn_X7', $364 = 'Corn_X8', $365 = 'Corn_X9', $366 = 'Corn_Z0', $367 = 'Corn_Z1', $368 = 'Corn_Z2', $369 = 'Corn_Z3', $370 = 'Corn_Z4', $371 = 'Corn_Z5', $372 = 'Corn_Z6', $373 = 'Corn_Z7', $374 = 'Corn_Z8', $375 = 'Corn_Z9', $376 = 'DE30', $377 = 'ES35', $378 = 'EURAUD', $379 = 'EURCAD', $380 = 'EURCHF', $381 = 'EURDKK', $382 = 'EURGBP', $383 = 'EURHKD', $384 = 'EURJPY', $385 = 'EURNOK', $386 = 'EURNZD', $387 = 'EURPLN', $388 = 'EURSEK', $389 = 'EURSGD', $390 = 'EURTRY', $391 = 'EURUSD', $392 = 'EURZAR', $393 = 'F40', $394 = 'GBPAUD', $395 = 'GBPCAD', $396 = 'GBPCHF', $397 = 'GBPDKK', $398 = 'GBPJPY', $399 = 'GBPNOK', $400 = 'GBPNZD', $401 = 'GBPSEK', $402 = 'GBPSGD', $403 = 'GBPUSD', $404 = 'HK50', $405 = 'IT40', $406 = 'JP225', $407 = 'NOKJPY', $408 = 'NOKSEK', $409 = 'NZDCAD', $410 = 'NZDCHF', $411 = 'NZDJPY', $412 = 'NZDUSD', $413 = 'SEKJPY', $414 = 'SGDJPY', $415 = 'STOXX50', $416 = 'Soybean_F0', $417 = 'Soybean_F1', $418 = 'Soybean_F2', $419 = 'Soybean_F3', $420 = 'Soybean_F4', $421 = 'Soybean_F5', $422 = 'Soybean_F6', $423 = 'Soybean_F7', $424 = 'Soybean_F8', $425 = 'Soybean_F9', $426 = 'Soybean_G0', $427 = 'Soybean_G1', $428 = 'Soybean_G2', $429 = 'Soybean_G3', $430 = 'Soybean_G4', $431 = 'Soybean_G5', $432 = 'Soybean_G6', $433 = 'Soybean_G7', $434 = 'Soybean_G8', $435 = 'Soybean_G9', $436 = 'Soybean_H0', $437 = 'Soybean_H1', $438 = 'Soybean_H2', $439 = 'Soybean_H3', $440 = 'Soybean_H4', $441 = 'Soybean_H5', $442 = 'Soybean_H6', $443 = 'Soybean_H7', $444 = 'Soybean_H8', $445 = 'Soybean_H9', $446 = 'Soybean_J0', $447 = 'Soybean_J1', $448 = 'Soybean_J2', $449 = 'Soybean_J3', $450 = 'Soybean_J4', $451 = 'Soybean_J5', $452 = 'Soybean_J6', $453 = 'Soybean_J7', $454 = 'Soybean_J8', $455 = 'Soybean_J9', $456 = 'Soybean_K0', $457 = 'Soybean_K1', $458 = 'Soybean_K2', $459 = 'Soybean_K3', $460 = 'Soybean_K4', $461 = 'Soybean_K5', $462 = 'Soybean_K6', $463 = 'Soybean_K7', $464 = 'Soybean_K8', $465 = 'Soybean_K9', $466 = 'Soybean_M0', $467 = 'Soybean_M1', $468 = 'Soybean_M2', $469 = 'Soybean_M3', $470 = 'Soybean_M4', $471 = 'Soybean_M5', $472 = 'Soybean_M6', $473 = 'Soybean_M7', $474 = 'Soybean_M8', $475 = 'Soybean_M9', $476 = 'Soybean_N0', $477 = 'Soybean_N1', $478 = 'Soybean_N2', $479 = 'Soybean_N3', $480 = 'Soybean_N4', $481 = 'Soybean_N5', $482 = 'Soybean_N6', $483 = 'Soybean_N7', $484 = 'Soybean_N8', $485 = 'Soybean_N9', $486 = 'Soybean_Q0', $487 = 'Soybean_Q1', $488 = 'Soybean_Q2', $489 = 'Soybean_Q3', $490 = 'Soybean_Q4', $491 = 'Soybean_Q5', $492 = 'Soybean_Q6', $493 = 'Soybean_Q7', $494 = 'Soybean_Q8', $495 = 'Soybean_Q9', $496 = 'Soybean_U0', $497 = 'Soybean_U1', $498 = 'Soybean_U2', $499 = 'Soybean_U3', $500 = 'Soybean_U4', $501 = 'Soybean_U5', $502 = 'Soybean_U6', $503 = 'Soybean_U7', $504 = 'Soybean_U8', $505 = 'Soybean_U9', $506 = 'Soybean_V0', $507 = 'Soybean_V1', $508 = 'Soybean_V2', $509 = 'Soybean_V3', $510 = 'Soybean_V4', $511 = 'Soybean_V5', $512 = 'Soybean_V6', $513 = 'Soybean_V7', $514 = 'Soybean_V8', $515 = 'Soybean_V9', $516 = 'Soybean_X0', $517 = 'Soybean_X1', $518 = 'Soybean_X2', $519 = 'Soybean_X3', $520 = 'Soybean_X4', $521 = 'Soybean_X5', $522 = 'Soybean_X6', $523 = 'Soybean_X7', $524 = 'Soybean_X8', $525 = 'Soybean_X9', $526 = 'Soybean_Z0', $527 = 'Soybean_Z1', $528 = 'Soybean_Z2', $529 = 'Soybean_Z3', $530 = 'Soybean_Z4', $531 = 'Soybean_Z5', $532 = 'Soybean_Z6', $533 = 'Soybean_Z7', $534 = 'Soybean_Z8', $535 = 'Soybean_Z9', $536 = 'Sugar_F0', $537 = 'Sugar_F1', $538 = 'Sugar_F2', $539 = 'Sugar_F3', $540 = 'Sugar_F4', $541 = 'Sugar_F5', $542 = 'Sugar_F6', $543 = 'Sugar_F7', $544 = 'Sugar_F8', $545 = 'Sugar_F9', $546 = 'Sugar_G0', $547 = 'Sugar_G1', $548 = 'Sugar_G2', $549 = 'Sugar_G3', $550 = 'Sugar_G4', $551 = 'Sugar_G5', $552 = 'Sugar_G6', $553 = 'Sugar_G7', $554 = 'Sugar_G8', $555 = 'Sugar_G9', $556 = 'Sugar_H0', $557 = 'Sugar_H1', $558 = 'Sugar_H2', $559 = 'Sugar_H3', $560 = 'Sugar_H4', $561 = 'Sugar_H5', $562 = 'Sugar_H6', $563 = 'Sugar_H7', $564 = 'Sugar_H8', $565 = 'Sugar_H9', $566 = 'Sugar_J0', $567 = 'Sugar_J1', $568 = 'Sugar_J2', $569 = 'Sugar_J3', $570 = 'Sugar_J4', $571 = 'Sugar_J5', $572 = 'Sugar_J6', $573 = 'Sugar_J7', $574 = 'Sugar_J8', $575 = 'Sugar_J9', $576 = 'Sugar_K0', $577 = 'Sugar_K1', $578 = 'Sugar_K2', $579 = 'Sugar_K3', $580 = 'Sugar_K4', $581 = 'Sugar_K5', $582 = 'Sugar_K6', $583 = 'Sugar_K7', $584 = 'Sugar_K8', $585 = 'Sugar_K9', $586 = 'Sugar_M0', $587 = 'Sugar_M1', $588 = 'Sugar_M2', $589 = 'Sugar_M3', $590 = 'Sugar_M4', $591 = 'Sugar_M5', $592 = 'Sugar_M6', $593 = 'Sugar_M7', $594 = 'Sugar_M8', $595 = 'Sugar_M9', $596 = 'Sugar_N0', $597 = 'Sugar_N1', $598 = 'Sugar_N2', $599 = 'Sugar_N3', $600 = 'Sugar_N4', $601 = 'Sugar_N5', $602 = 'Sugar_N6', $603 = 'Sugar_N7', $604 = 'Sugar_N8', $605 = 'Sugar_N9', $606 = 'Sugar_Q0', $607 = 'Sugar_Q1', $608 = 'Sugar_Q2', $609 = 'Sugar_Q3', $610 = 'Sugar_Q4', $611 = 'Sugar_Q5', $612 = 'Sugar_Q6', $613 = 'Sugar_Q7', $614 = 'Sugar_Q8', $615 = 'Sugar_Q9', $616 = 'Sugar_U0', $617 = 'Sugar_U1', $618 = 'Sugar_U2', $619 = 'Sugar_U3', $620 = 'Sugar_U4', $621 = 'Sugar_U5', $622 = 'Sugar_U6', $623 = 'Sugar_U7', $624 = 'Sugar_U8', $625 = 'Sugar_U9', $626 = 'Sugar_V0', $627 = 'Sugar_V1', $628 = 'Sugar_V2', $629 = 'Sugar_V3', $630 = 'Sugar_V4', $631 = 'Sugar_V5', $632 = 'Sugar_V6', $633 = 'Sugar_V7', $634 = 'Sugar_V8', $635 = 'Sugar_V9', $636 = 'Sugar_X0', $637 = 'Sugar_X1', $638 = 'Sugar_X2', $639 = 'Sugar_X3', $640 = 'Sugar_X4', $641 = 'Sugar_X5', $642 = 'Sugar_X6', $643 = 'Sugar_X7', $644 = 'Sugar_X8', $645 = 'Sugar_X9', $646 = 'Sugar_Z0', $647 = 'Sugar_Z1', $648 = 'Sugar_Z2', $649 = 'Sugar_Z3', $650 = 'Sugar_Z4', $651 = 'Sugar_Z5', $652 = 'Sugar_Z6', $653 = 'Sugar_Z7', $654 = 'Sugar_Z8', $655 = 'Sugar_Z9', $656 = 'UK100', $657 = 'US2000', $658 = 'US30', $659 = 'US500', $660 = 'USDCAD', $661 = 'USDCHF', $662 = 'USDCNH', $663 = 'USDCZK', $664 = 'USDDKK', $665 = 'USDHKD', $666 = 'USDHUF', $667 = 'USDJPY', $668 = 'USDMXN', $669 = 'USDNOK', $670 = 'USDPLN', $671 = 'USDRUB', $672 = 'USDSEK', $673 = 'USDSGD', $674 = 'USDTHB', $675 = 'USDTRY', $676 = 'USDZAR', $677 = 'USTEC', $678 = 'WTI_F0', $679 = 'WTI_F1', $680 = 'WTI_F2', $681 = 'WTI_F3', $682 = 'WTI_F4', $683 = 'WTI_F5', $684 = 'WTI_F6', $685 = 'WTI_F7', $686 = 'WTI_F8', $687 = 'WTI_F9', $688 = 'WTI_G0', $689 = 'WTI_G1', $690 = 'WTI_G2', $691 = 'WTI_G3', $692 = 'WTI_G4', $693 = 'WTI_G5', $694 = 'WTI_G6', $695 = 'WTI_G7', $696 = 'WTI_G8', $697 = 'WTI_G9', $698 = 'WTI_H0', $699 = 'WTI_H1', $700 = 'WTI_H2', $701 = 'WTI_H3', $702 = 'WTI_H4', $703 = 'WTI_H5', $704 = 'WTI_H6', $705 = 'WTI_H7', $706 = 'WTI_H8', $707 = 'WTI_H9', $708 = 'WTI_J0', $709 = 'WTI_J1', $710 = 'WTI_J2', $711 = 'WTI_J3', $712 = 'WTI_J4', $713 = 'WTI_J5', $714 = 'WTI_J6', $715 = 'WTI_J7', $716 = 'WTI_J8', $717 = 'WTI_J9', $718 = 'WTI_K0', $719 = 'WTI_K1', $720 = 'WTI_K2', $721 = 'WTI_K3', $722 = 'WTI_K4', $723 = 'WTI_K5', $724 = 'WTI_K6', $725 = 'WTI_K7', $726 = 'WTI_K8', $727 = 'WTI_K9', $728 = 'WTI_M0', $729 = 'WTI_M1', $730 = 'WTI_M2', $731 = 'WTI_M3', $732 = 'WTI_M4', $733 = 'WTI_M5', $734 = 'WTI_M6', $735 = 'WTI_M7', $736 = 'WTI_M8', $737 = 'WTI_M9', $738 = 'WTI_N0', $739 = 'WTI_N1', $740 = 'WTI_N2', $741 = 'WTI_N3', $742 = 'WTI_N4', $743 = 'WTI_N5', $744 = 'WTI_N6', $745 = 'WTI_N7', $746 = 'WTI_N8', $747 = 'WTI_N9', $748 = 'WTI_Q0', $749 = 'WTI_Q1', $750 = 'WTI_Q2', $751 = 'WTI_Q3', $752 = 'WTI_Q4', $753 = 'WTI_Q5', $754 = 'WTI_Q6', $755 = 'WTI_Q7', $756 = 'WTI_Q8', $757 = 'WTI_Q9', $758 = 'WTI_U0', $759 = 'WTI_U1', $760 = 'WTI_U2', $761 = 'WTI_U3', $762 = 'WTI_U4', $763 = 'WTI_U5', $764 = 'WTI_U6', $765 = 'WTI_U7', $766 = 'WTI_U8', $767 = 'WTI_U9', $768 = 'WTI_V0', $769 = 'WTI_V1', $770 = 'WTI_V2', $771 = 'WTI_V3', $772 = 'WTI_V4', $773 = 'WTI_V5', $774 = 'WTI_V6', $775 = 'WTI_V7', $776 = 'WTI_V8', $777 = 'WTI_V9', $778 = 'WTI_X0', $779 = 'WTI_X1', $780 = 'WTI_X2', $781 = 'WTI_X3', $782 = 'WTI_X4', $783 = 'WTI_X5', $784 = 'WTI_X6', $785 = 'WTI_X7', $786 = 'WTI_X8', $787 = 'WTI_X9', $788 = 'WTI_Z0', $789 = 'WTI_Z1', $790 = 'WTI_Z2', $791 = 'WTI_Z3', $792 = 'WTI_Z4', $793 = 'WTI_Z5', $794 = 'WTI_Z6', $795 = 'WTI_Z7', $796 = 'WTI_Z8', $797 = 'WTI_Z9', $798 = 'Wheat_F0', $799 = 'Wheat_F1', $800 = 'Wheat_F2', $801 = 'Wheat_F3', $802 = 'Wheat_F4', $803 = 'Wheat_F5', $804 = 'Wheat_F6', $805 = 'Wheat_F7', $806 = 'Wheat_F8', $807 = 'Wheat_F9', $808 = 'Wheat_G0', $809 = 'Wheat_G1', $810 = 'Wheat_G2', $811 = 'Wheat_G3', $812 = 'Wheat_G4', $813 = 'Wheat_G5', $814 = 'Wheat_G6', $815 = 'Wheat_G7', $816 = 'Wheat_G8', $817 = 'Wheat_G9', $818 = 'Wheat_H0', $819 = 'Wheat_H1', $820 = 'Wheat_H2', $821 = 'Wheat_H3', $822 = 'Wheat_H4', $823 = 'Wheat_H5', $824 = 'Wheat_H6', $825 = 'Wheat_H7', $826 = 'Wheat_H8', $827 = 'Wheat_H9', $828 = 'Wheat_J0', $829 = 'Wheat_J1', $830 = 'Wheat_J2', $831 = 'Wheat_J3', $832 = 'Wheat_J4', $833 = 'Wheat_J5', $834 = 'Wheat_J6', $835 = 'Wheat_J7', $836 = 'Wheat_J8', $837 = 'Wheat_J9', $838 = 'Wheat_K0', $839 = 'Wheat_K1', $840 = 'Wheat_K2', $841 = 'Wheat_K3', $842 = 'Wheat_K4', $843 = 'Wheat_K5', $844 = 'Wheat_K6', $845 = 'Wheat_K7', $846 = 'Wheat_K8', $847 = 'Wheat_K9', $848 = 'Wheat_M0', $849 = 'Wheat_M1', $850 = 'Wheat_M2', $851 = 'Wheat_M3', $852 = 'Wheat_M4', $853 = 'Wheat_M5', $854 = 'Wheat_M6', $855 = 'Wheat_M7', $856 = 'Wheat_M8', $857 = 'Wheat_M9', $858 = 'Wheat_N0', $859 = 'Wheat_N1', $860 = 'Wheat_N2', $861 = 'Wheat_N3', $862 = 'Wheat_N4', $863 = 'Wheat_N5', $864 = 'Wheat_N6', $865 = 'Wheat_N7', $866 = 'Wheat_N8', $867 = 'Wheat_N9', $868 = 'Wheat_Q0', $869 = 'Wheat_Q1', $870 = 'Wheat_Q2', $871 = 'Wheat_Q3', $872 = 'Wheat_Q4', $873 = 'Wheat_Q5', $874 = 'Wheat_Q6', $875 = 'Wheat_Q7', $876 = 'Wheat_Q8', $877 = 'Wheat_Q9', $878 = 'Wheat_U0', $879 = 'Wheat_U1', $880 = 'Wheat_U2', $881 = 'Wheat_U3', $882 = 'Wheat_U4', $883 = 'Wheat_U5', $884 = 'Wheat_U6', $885 = 'Wheat_U7', $886 = 'Wheat_U8', $887 = 'Wheat_U9', $888 = 'Wheat_V0', $889 = 'Wheat_V1', $890 = 'Wheat_V2', $891 = 'Wheat_V3', $892 = 'Wheat_V4', $893 = 'Wheat_V5', $894 = 'Wheat_V6', $895 = 'Wheat_V7', $896 = 'Wheat_V8', $897 = 'Wheat_V9', $898 = 'Wheat_X0', $899 = 'Wheat_X1', $900 = 'Wheat_X2', $901 = 'Wheat_X3', $902 = 'Wheat_X4', $903 = 'Wheat_X5', $904 = 'Wheat_X6', $905 = 'Wheat_X7', $906 = 'Wheat_X8', $907 = 'Wheat_X9', $908 = 'Wheat_Z0', $909 = 'Wheat_Z1', $910 = 'Wheat_Z2', $911 = 'Wheat_Z3', $912 = 'Wheat_Z4', $913 = 'Wheat_Z5', $914 = 'Wheat_Z6', $915 = 'Wheat_Z7', $916 = 'Wheat_Z8', $917 = 'Wheat_Z9', $918 = 'XAGEUR', $919 = 'XAGUSD', $920 = 'XAUEUR', $921 = 'XAUUSD', $922 = 'XBRUSD', $923 = 'XNGUSD', $924 = 'XPDUSD', $925 = 'XPTUSD', $926 = 'XTIUSD', $927 = 'AUDCAD', $928 = 'AUDCHF', $929 = 'AUDJPY', $930 = 'AUDNZD', $931 = 'AUDSGD', $932 = 'AUDUSD', $933 = 'AUS200', $934 = 'BRENT_F0', $935 = 'BRENT_F1', $936 = 'BRENT_F2', $937 = 'BRENT_F3', $938 = 'BRENT_F4', $939 = 'BRENT_F5', $940 = 'BRENT_F6', $941 = 'BRENT_F7', $942 = 'BRENT_F8', $943 = 'BRENT_F9', $944 = 'BRENT_G0', $945 = 'BRENT_G1', $946 = 'BRENT_G2', $947 = 'BRENT_G3', $948 = 'BRENT_G4', $949 = 'BRENT_G5', $950 = 'BRENT_G6', $951 = 'BRENT_G7', $952 = 'BRENT_G8', $953 = 'BRENT_G9', $954 = 'BRENT_H0', $955 = 'BRENT_H1', $956 = 'BRENT_H2', $957 = 'BRENT_H3', $958 = 'BRENT_H4', $959 = 'BRENT_H5', $960 = 'BRENT_H6', $961 = 'BRENT_H7', $962 = 'BRENT_H8', $963 = 'BRENT_H9', $964 = 'BRENT_J0', $965 = 'BRENT_J1', $966 = 'BRENT_J2', $967 = 'BRENT_J3', $968 = 'BRENT_J4', $969 = 'BRENT_J5', $970 = 'BRENT_J6', $971 = 'BRENT_J7', $972 = 'BRENT_J8', $973 = 'BRENT_J9', $974 = 'BRENT_K0', $975 = 'BRENT_K1', $976 = 'BRENT_K2', $977 = 'BRENT_K3', $978 = 'BRENT_K4', $979 = 'BRENT_K5', $980 = 'BRENT_K6', $981 = 'BRENT_K7', $982 = 'BRENT_K8', $983 = 'BRENT_K9', $984 = 'BRENT_M0', $985 = 'BRENT_M1', $986 = 'BRENT_M2', $987 = 'BRENT_M3', $988 = 'BRENT_M4', $989 = 'BRENT_M5', $990 = 'BRENT_M6', $991 = 'BRENT_M7', $992 = 'BRENT_M8', $993 = 'BRENT_M9', $994 = 'BRENT_N0', $995 = 'BRENT_N1', $996 = 'BRENT_N2', $997 = 'BRENT_N3', $998 = 'BRENT_N4', $999 = 'BRENT_N5', $1000 = 'BRENT_N6', $1001 = 'BRENT_N7', $1002 = 'BRENT_N8', $1003 = 'BRENT_N9', $1004 = 'BRENT_Q0', $1005 = 'BRENT_Q1', $1006 = 'BRENT_Q2', $1007 = 'BRENT_Q3', $1008 = 'BRENT_Q4', $1009 = 'BRENT_Q5', $1010 = 'BRENT_Q6', $1011 = 'BRENT_Q7', $1012 = 'BRENT_Q8', $1013 = 'BRENT_Q9', $1014 = 'BRENT_U0', $1015 = 'BRENT_U1', $1016 = 'BRENT_U2', $1017 = 'BRENT_U3', $1018 = 'BRENT_U4', $1019 = 'BRENT_U5', $1020 = 'BRENT_U6', $1021 = 'BRENT_U7', $1022 = 'BRENT_U8', $1023 = 'BRENT_U9', $1024 = 'BRENT_V0', $1025 = 'BRENT_V1', $1026 = 'BRENT_V2', $1027 = 'BRENT_V3', $1028 = 'BRENT_V4', $1029 = 'BRENT_V5', $1030 = 'BRENT_V6', $1031 = 'BRENT_V7', $1032 = 'BRENT_V8', $1033 = 'BRENT_V9', $1034 = 'BRENT_X0', $1035 = 'BRENT_X1', $1036 = 'BRENT_X2', $1037 = 'BRENT_X3', $1038 = 'BRENT_X4', $1039 = 'BRENT_X5', $1040 = 'BRENT_X6', $1041 = 'BRENT_X7', $1042 = 'BRENT_X8', $1043 = 'BRENT_X9', $1044 = 'BRENT_Z0', $1045 = 'BRENT_Z1', $1046 = 'BRENT_Z2', $1047 = 'BRENT_Z3', $1048 = 'BRENT_Z4', $1049 = 'BRENT_Z5', $1050 = 'BRENT_Z6', $1051 = 'BRENT_Z7', $1052 = 'BRENT_Z8', $1053 = 'BRENT_Z9', $1054 = 'BTCUSD', $1055 = 'CADCHF', $1056 = 'CADJPY', $1057 = 'CHFJPY', $1058 = 'CHFSGD', $1059 = 'CHINA50', $1060 = 'Coffee_F0', $1061 = 'Coffee_F1', $1062 = 'Coffee_F2', $1063 = 'Coffee_F3', $1064 = 'Coffee_F4', $1065 = 'Coffee_F5', $1066 = 'Coffee_F6', $1067 = 'Coffee_F7', $1068 = 'Coffee_F8', $1069 = 'Coffee_F9', $1070 = 'Coffee_G0', $1071 = 'Coffee_G1', $1072 = 'Coffee_G2', $1073 = 'Coffee_G3', $1074 = 'Coffee_G4', $1075 = 'Coffee_G5', $1076 = 'Coffee_G6', $1077 = 'Coffee_G7', $1078 = 'Coffee_G8', $1079 = 'Coffee_G9', $1080 = 'Coffee_H0', $1081 = 'Coffee_H1', $1082 = 'Coffee_H2', $1083 = 'Coffee_H3', $1084 = 'Coffee_H4', $1085 = 'Coffee_H5', $1086 = 'Coffee_H6', $1087 = 'Coffee_H7', $1088 = 'Coffee_H8', $1089 = 'Coffee_H9', $1090 = 'Coffee_J0', $1091 = 'Coffee_J1', $1092 = 'Coffee_J2', $1093 = 'Coffee_J3', $1094 = 'Coffee_J4', $1095 = 'Coffee_J5', $1096 = 'Coffee_J6', $1097 = 'Coffee_J7', $1098 = 'Coffee_J8', $1099 = 'Coffee_J9', $1100 = 'Coffee_K0', $1101 = 'Coffee_K1', $1102 = 'Coffee_K2', $1103 = 'Coffee_K3', $1104 = 'Coffee_K4', $1105 = 'Coffee_K5', $1106 = 'Coffee_K6', $1107 = 'Coffee_K7', $1108 = 'Coffee_K8', $1109 = 'Coffee_K9', $1110 = 'Coffee_M0', $1111 = 'Coffee_M1', $1112 = 'Coffee_M2', $1113 = 'Coffee_M3', $1114 = 'Coffee_M4', $1115 = 'Coffee_M5', $1116 = 'Coffee_M6', $1117 = 'Coffee_M7', $1118 = 'Coffee_M8', $1119 = 'Coffee_M9', $1120 = 'Coffee_N0', $1121 = 'Coffee_N1', $1122 = 'Coffee_N2', $1123 = 'Coffee_N3', $1124 = 'Coffee_N4', $1125 = 'Coffee_N5', $1126 = 'Coffee_N6', $1127 = 'Coffee_N7', $1128 = 'Coffee_N8', $1129 = 'Coffee_N9', $1130 = 'Coffee_Q0', $1131 = 'Coffee_Q1', $1132 = 'Coffee_Q2', $1133 = 'Coffee_Q3', $1134 = 'Coffee_Q4', $1135 = 'Coffee_Q5', $1136 = 'Coffee_Q6', $1137 = 'Coffee_Q7', $1138 = 'Coffee_Q8', $1139 = 'Coffee_Q9', $1140 = 'Coffee_U0', $1141 = 'Coffee_U1', $1142 = 'Coffee_U2', $1143 = 'Coffee_U3', $1144 = 'Coffee_U4', $1145 = 'Coffee_U5', $1146 = 'Coffee_U6', $1147 = 'Coffee_U7', $1148 = 'Coffee_U8', $1149 = 'Coffee_U9', $1150 = 'Coffee_V0', $1151 = 'Coffee_V1', $1152 = 'Coffee_V2', $1153 = 'Coffee_V3', $1154 = 'Coffee_V4', $1155 = 'Coffee_V5', $1156 = 'Coffee_V6', $1157 = 'Coffee_V7', $1158 = 'Coffee_V8', $1159 = 'Coffee_V9', $1160 = 'Coffee_X0', $1161 = 'Coffee_X1', $1162 = 'Coffee_X2', $1163 = 'Coffee_X3', $1164 = 'Coffee_X4', $1165 = 'Coffee_X5', $1166 = 'Coffee_X6', $1167 = 'Coffee_X7', $1168 = 'Coffee_X8', $1169 = 'Coffee_X9', $1170 = 'Coffee_Z0', $1171 = 'Coffee_Z1', $1172 = 'Coffee_Z2', $1173 = 'Coffee_Z3', $1174 = 'Coffee_Z4', $1175 = 'Coffee_Z5', $1176 = 'Coffee_Z6', $1177 = 'Coffee_Z7', $1178 = 'Coffee_Z8', $1179 = 'Coffee_Z9', $1180 = 'Corn_F0', $1181 = 'Corn_F1', $1182 = 'Corn_F2', $1183 = 'Corn_F3', $1184 = 'Corn_F4', $1185 = 'Corn_F5', $1186 = 'Corn_F6', $1187 = 'Corn_F7', $1188 = 'Corn_F8', $1189 = 'Corn_F9', $1190 = 'Corn_G0', $1191 = 'Corn_G1', $1192 = 'Corn_G2', $1193 = 'Corn_G3', $1194 = 'Corn_G4', $1195 = 'Corn_G5', $1196 = 'Corn_G6', $1197 = 'Corn_G7', $1198 = 'Corn_G8', $1199 = 'Corn_G9', $1200 = 'Corn_H0', $1201 = 'Corn_H1', $1202 = 'Corn_H2', $1203 = 'Corn_H3', $1204 = 'Corn_H4', $1205 = 'Corn_H5', $1206 = 'Corn_H6', $1207 = 'Corn_H7', $1208 = 'Corn_H8', $1209 = 'Corn_H9', $1210 = 'Corn_J0', $1211 = 'Corn_J1', $1212 = 'Corn_J2', $1213 = 'Corn_J3', $1214 = 'Corn_J4', $1215 = 'Corn_J5', $1216 = 'Corn_J6', $1217 = 'Corn_J7', $1218 = 'Corn_J8', $1219 = 'Corn_J9', $1220 = 'Corn_K0', $1221 = 'Corn_K1', $1222 = 'Corn_K2', $1223 = 'Corn_K3', $1224 = 'Corn_K4', $1225 = 'Corn_K5', $1226 = 'Corn_K6', $1227 = 'Corn_K7', $1228 = 'Corn_K8', $1229 = 'Corn_K9', $1230 = 'Corn_M0', $1231 = 'Corn_M1', $1232 = 'Corn_M2', $1233 = 'Corn_M3', $1234 = 'Corn_M4', $1235 = 'Corn_M5', $1236 = 'Corn_M6', $1237 = 'Corn_M7', $1238 = 'Corn_M8', $1239 = 'Corn_M9', $1240 = 'Corn_N0', $1241 = 'Corn_N1', $1242 = 'Corn_N2', $1243 = 'Corn_N3', $1244 = 'Corn_N4', $1245 = 'Corn_N5', $1246 = 'Corn_N6', $1247 = 'Corn_N7', $1248 = 'Corn_N8', $1249 = 'Corn_N9', $1250 = 'Corn_Q0', $1251 = 'Corn_Q1', $1252 = 'Corn_Q2', $1253 = 'Corn_Q3', $1254 = 'Corn_Q4', $1255 = 'Corn_Q5', $1256 = 'Corn_Q6', $1257 = 'Corn_Q7', $1258 = 'Corn_Q8', $1259 = 'Corn_Q9', $1260 = 'Corn_U0', $1261 = 'Corn_U1', $1262 = 'Corn_U2', $1263 = 'Corn_U3', $1264 = 'Corn_U4', $1265 = 'Corn_U5', $1266 = 'Corn_U6', $1267 = 'Corn_U7', $1268 = 'Corn_U8', $1269 = 'Corn_U9', $1270 = 'Corn_V0', $1271 = 'Corn_V1', $1272 = 'Corn_V2', $1273 = 'Corn_V3', $1274 = 'Corn_V4', $1275 = 'Corn_V5', $1276 = 'Corn_V6', $1277 = 'Corn_V7', $1278 = 'Corn_V8', $1279 = 'Corn_V9', $1280 = 'Corn_X0', $1281 = 'Corn_X1', $1282 = 'Corn_X2', $1283 = 'Corn_X3', $1284 = 'Corn_X4', $1285 = 'Corn_X5', $1286 = 'Corn_X6', $1287 = 'Corn_X7', $1288 = 'Corn_X8', $1289 = 'Corn_X9', $1290 = 'Corn_Z0', $1291 = 'Corn_Z1', $1292 = 'Corn_Z2', $1293 = 'Corn_Z3', $1294 = 'Corn_Z4', $1295 = 'Corn_Z5', $1296 = 'Corn_Z6', $1297 = 'Corn_Z7', $1298 = 'Corn_Z8', $1299 = 'Corn_Z9', $1300 = 'DE30', $1301 = 'ES35', $1302 = 'EURAUD', $1303 = 'EURCAD', $1304 = 'EURCHF', $1305 = 'EURDKK', $1306 = 'EURGBP', $1307 = 'EURHKD', $1308 = 'EURJPY', $1309 = 'EURNOK', $1310 = 'EURNZD', $1311 = 'EURPLN', $1312 = 'EURSEK', $1313 = 'EURSGD', $1314 = 'EURTRY', $1315 = 'EURUSD', $1316 = 'EURZAR', $1317 = 'F40', $1318 = 'GBPAUD', $1319 = 'GBPCAD', $1320 = 'GBPCHF', $1321 = 'GBPDKK', $1322 = 'GBPJPY', $1323 = 'GBPNOK', $1324 = 'GBPNZD', $1325 = 'GBPSEK', $1326 = 'GBPSGD', $1327 = 'GBPUSD', $1328 = 'HK50', $1329 = 'IT40', $1330 = 'JP225', $1331 = 'NOKJPY', $1332 = 'NOKSEK', $1333 = 'NZDCAD', $1334 = 'NZDCHF', $1335 = 'NZDJPY', $1336 = 'NZDUSD', $1337 = 'SEKJPY', $1338 = 'SGDJPY', $1339 = 'STOXX50', $1340 = 'Soybean_F0', $1341 = 'Soybean_F1', $1342 = 'Soybean_F2', $1343 = 'Soybean_F3', $1344 = 'Soybean_F4', $1345 = 'Soybean_F5', $1346 = 'Soybean_F6', $1347 = 'Soybean_F7', $1348 = 'Soybean_F8', $1349 = 'Soybean_F9', $1350 = 'Soybean_G0', $1351 = 'Soybean_G1', $1352 = 'Soybean_G2', $1353 = 'Soybean_G3', $1354 = 'Soybean_G4', $1355 = 'Soybean_G5', $1356 = 'Soybean_G6', $1357 = 'Soybean_G7', $1358 = 'Soybean_G8', $1359 = 'Soybean_G9', $1360 = 'Soybean_H0', $1361 = 'Soybean_H1', $1362 = 'Soybean_H2', $1363 = 'Soybean_H3', $1364 = 'Soybean_H4', $1365 = 'Soybean_H5', $1366 = 'Soybean_H6', $1367 = 'Soybean_H7', $1368 = 'Soybean_H8', $1369 = 'Soybean_H9', $1370 = 'Soybean_J0', $1371 = 'Soybean_J1', $1372 = 'Soybean_J2', $1373 = 'Soybean_J3', $1374 = 'Soybean_J4', $1375 = 'Soybean_J5', $1376 = 'Soybean_J6', $1377 = 'Soybean_J7', $1378 = 'Soybean_J8', $1379 = 'Soybean_J9', $1380 = 'Soybean_K0', $1381 = 'Soybean_K1', $1382 = 'Soybean_K2', $1383 = 'Soybean_K3', $1384 = 'Soybean_K4', $1385 = 'Soybean_K5', $1386 = 'Soybean_K6', $1387 = 'Soybean_K7', $1388 = 'Soybean_K8', $1389 = 'Soybean_K9', $1390 = 'Soybean_M0', $1391 = 'Soybean_M1', $1392 = 'Soybean_M2', $1393 = 'Soybean_M3', $1394 = 'Soybean_M4', $1395 = 'Soybean_M5', $1396 = 'Soybean_M6', $1397 = 'Soybean_M7', $1398 = 'Soybean_M8', $1399 = 'Soybean_M9', $1400 = 'Soybean_N0', $1401 = 'Soybean_N1', $1402 = 'Soybean_N2', $1403 = 'Soybean_N3', $1404 = 'Soybean_N4', $1405 = 'Soybean_N5', $1406 = 'Soybean_N6', $1407 = 'Soybean_N7', $1408 = 'Soybean_N8', $1409 = 'Soybean_N9', $1410 = 'Soybean_Q0', $1411 = 'Soybean_Q1', $1412 = 'Soybean_Q2', $1413 = 'Soybean_Q3', $1414 = 'Soybean_Q4', $1415 = 'Soybean_Q5', $1416 = 'Soybean_Q6', $1417 = 'Soybean_Q7', $1418 = 'Soybean_Q8', $1419 = 'Soybean_Q9', $1420 = 'Soybean_U0', $1421 = 'Soybean_U1', $1422 = 'Soybean_U2', $1423 = 'Soybean_U3', $1424 = 'Soybean_U4', $1425 = 'Soybean_U5', $1426 = 'Soybean_U6', $1427 = 'Soybean_U7', $1428 = 'Soybean_U8', $1429 = 'Soybean_U9', $1430 = 'Soybean_V0', $1431 = 'Soybean_V1', $1432 = 'Soybean_V2', $1433 = 'Soybean_V3', $1434 = 'Soybean_V4', $1435 = 'Soybean_V5', $1436 = 'Soybean_V6', $1437 = 'Soybean_V7', $1438 = 'Soybean_V8', $1439 = 'Soybean_V9', $1440 = 'Soybean_X0', $1441 = 'Soybean_X1', $1442 = 'Soybean_X2', $1443 = 'Soybean_X3', $1444 = 'Soybean_X4', $1445 = 'Soybean_X5', $1446 = 'Soybean_X6', $1447 = 'Soybean_X7', $1448 = 'Soybean_X8', $1449 = 'Soybean_X9', $1450 = 'Soybean_Z0', $1451 = 'Soybean_Z1', $1452 = 'Soybean_Z2', $1453 = 'Soybean_Z3', $1454 = 'Soybean_Z4', $1455 = 'Soybean_Z5', $1456 = 'Soybean_Z6', $1457 = 'Soybean_Z7', $1458 = 'Soybean_Z8', $1459 = 'Soybean_Z9', $1460 = 'Sugar_F0', $1461 = 'Sugar_F1', $1462 = 'Sugar_F2', $1463 = 'Sugar_F3', $1464 = 'Sugar_F4', $1465 = 'Sugar_F5', $1466 = 'Sugar_F6', $1467 = 'Sugar_F7', $1468 = 'Sugar_F8', $1469 = 'Sugar_F9', $1470 = 'Sugar_G0', $1471 = 'Sugar_G1', $1472 = 'Sugar_G2', $1473 = 'Sugar_G3', $1474 = 'Sugar_G4', $1475 = 'Sugar_G5', $1476 = 'Sugar_G6', $1477 = 'Sugar_G7', $1478 = 'Sugar_G8', $1479 = 'Sugar_G9', $1480 = 'Sugar_H0', $1481 = 'Sugar_H1', $1482 = 'Sugar_H2', $1483 = 'Sugar_H3', $1484 = 'Sugar_H4', $1485 = 'Sugar_H5', $1486 = 'Sugar_H6', $1487 = 'Sugar_H7', $1488 = 'Sugar_H8', $1489 = 'Sugar_H9', $1490 = 'Sugar_J0', $1491 = 'Sugar_J1', $1492 = 'Sugar_J2', $1493 = 'Sugar_J3', $1494 = 'Sugar_J4', $1495 = 'Sugar_J5', $1496 = 'Sugar_J6', $1497 = 'Sugar_J7', $1498 = 'Sugar_J8', $1499 = 'Sugar_J9', $1500 = 'Sugar_K0', $1501 = 'Sugar_K1', $1502 = 'Sugar_K2', $1503 = 'Sugar_K3', $1504 = 'Sugar_K4', $1505 = 'Sugar_K5', $1506 = 'Sugar_K6', $1507 = 'Sugar_K7', $1508 = 'Sugar_K8', $1509 = 'Sugar_K9', $1510 = 'Sugar_M0', $1511 = 'Sugar_M1', $1512 = 'Sugar_M2', $1513 = 'Sugar_M3', $1514 = 'Sugar_M4', $1515 = 'Sugar_M5', $1516 = 'Sugar_M6', $1517 = 'Sugar_M7', $1518 = 'Sugar_M8', $1519 = 'Sugar_M9', $1520 = 'Sugar_N0', $1521 = 'Sugar_N1', $1522 = 'Sugar_N2', $1523 = 'Sugar_N3', $1524 = 'Sugar_N4', $1525 = 'Sugar_N5', $1526 = 'Sugar_N6', $1527 = 'Sugar_N7', $1528 = 'Sugar_N8', $1529 = 'Sugar_N9', $1530 = 'Sugar_Q0', $1531 = 'Sugar_Q1', $1532 = 'Sugar_Q2', $1533 = 'Sugar_Q3', $1534 = 'Sugar_Q4', $1535 = 'Sugar_Q5', $1536 = 'Sugar_Q6', $1537 = 'Sugar_Q7', $1538 = 'Sugar_Q8', $1539 = 'Sugar_Q9', $1540 = 'Sugar_U0', $1541 = 'Sugar_U1', $1542 = 'Sugar_U2', $1543 = 'Sugar_U3', $1544 = 'Sugar_U4', $1545 = 'Sugar_U5', $1546 = 'Sugar_U6', $1547 = 'Sugar_U7', $1548 = 'Sugar_U8', $1549 = 'Sugar_U9', $1550 = 'Sugar_V0', $1551 = 'Sugar_V1', $1552 = 'Sugar_V2', $1553 = 'Sugar_V3', $1554 = 'Sugar_V4', $1555 = 'Sugar_V5', $1556 = 'Sugar_V6', $1557 = 'Sugar_V7', $1558 = 'Sugar_V8', $1559 = 'Sugar_V9', $1560 = 'Sugar_X0', $1561 = 'Sugar_X1', $1562 = 'Sugar_X2', $1563 = 'Sugar_X3', $1564 = 'Sugar_X4', $1565 = 'Sugar_X5', $1566 = 'Sugar_X6', $1567 = 'Sugar_X7', $1568 = 'Sugar_X8', $1569 = 'Sugar_X9', $1570 = 'Sugar_Z0', $1571 = 'Sugar_Z1', $1572 = 'Sugar_Z2', $1573 = 'Sugar_Z3', $1574 = 'Sugar_Z4', $1575 = 'Sugar_Z5', $1576 = 'Sugar_Z6', $1577 = 'Sugar_Z7', $1578 = 'Sugar_Z8', $1579 = 'Sugar_Z9', $1580 = 'UK100', $1581 = 'US2000', $1582 = 'US30', $1583 = 'US500', $1584 = 'USDCAD', $1585 = 'USDCHF', $1586 = 'USDCNH', $1587 = 'USDCZK', $1588 = 'USDDKK', $1589 = 'USDHKD', $1590 = 'USDHUF', $1591 = 'USDJPY', $1592 = 'USDMXN', $1593 = 'USDNOK', $1594 = 'USDPLN', $1595 = 'USDRUB', $1596 = 'USDSEK', $1597 = 'USDSGD', $1598 = 'USDTHB', $1599 = 'USDTRY', $1600 = 'USDZAR', $1601 = 'USTEC', $1602 = 'WTI_F0', $1603 = 'WTI_F1', $1604 = 'WTI_F2', $1605 = 'WTI_F3', $1606 = 'WTI_F4', $1607 = 'WTI_F5', $1608 = 'WTI_F6', $1609 = 'WTI_F7', $1610 = 'WTI_F8', $1611 = 'WTI_F9', $1612 = 'WTI_G0', $1613 = 'WTI_G1', $1614 = 'WTI_G2', $1615 = 'WTI_G3', $1616 = 'WTI_G4', $1617 = 'WTI_G5', $1618 = 'WTI_G6', $1619 = 'WTI_G7', $1620 = 'WTI_G8', $1621 = 'WTI_G9', $1622 = 'WTI_H0', $1623 = 'WTI_H1', $1624 = 'WTI_H2', $1625 = 'WTI_H3', $1626 = 'WTI_H4', $1627 = 'WTI_H5', $1628 = 'WTI_H6', $1629 = 'WTI_H7', $1630 = 'WTI_H8', $1631 = 'WTI_H9', $1632 = 'WTI_J0', $1633 = 'WTI_J1', $1634 = 'WTI_J2', $1635 = 'WTI_J3', $1636 = 'WTI_J4', $1637 = 'WTI_J5', $1638 = 'WTI_J6', $1639 = 'WTI_J7', $1640 = 'WTI_J8', $1641 = 'WTI_J9', $1642 = 'WTI_K0', $1643 = 'WTI_K1', $1644 = 'WTI_K2', $1645 = 'WTI_K3', $1646 = 'WTI_K4', $1647 = 'WTI_K5', $1648 = 'WTI_K6', $1649 = 'WTI_K7', $1650 = 'WTI_K8', $1651 = 'WTI_K9', $1652 = 'WTI_M0', $1653 = 'WTI_M1', $1654 = 'WTI_M2', $1655 = 'WTI_M3', $1656 = 'WTI_M4', $1657 = 'WTI_M5', $1658 = 'WTI_M6', $1659 = 'WTI_M7', $1660 = 'WTI_M8', $1661 = 'WTI_M9', $1662 = 'WTI_N0', $1663 = 'WTI_N1', $1664 = 'WTI_N2', $1665 = 'WTI_N3', $1666 = 'WTI_N4', $1667 = 'WTI_N5', $1668 = 'WTI_N6', $1669 = 'WTI_N7', $1670 = 'WTI_N8', $1671 = 'WTI_N9', $1672 = 'WTI_Q0', $1673 = 'WTI_Q1', $1674 = 'WTI_Q2', $1675 = 'WTI_Q3', $1676 = 'WTI_Q4', $1677 = 'WTI_Q5', $1678 = 'WTI_Q6', $1679 = 'WTI_Q7', $1680 = 'WTI_Q8', $1681 = 'WTI_Q9', $1682 = 'WTI_U0', $1683 = 'WTI_U1', $1684 = 'WTI_U2', $1685 = 'WTI_U3', $1686 = 'WTI_U4', $1687 = 'WTI_U5', $1688 = 'WTI_U6', $1689 = 'WTI_U7', $1690 = 'WTI_U8', $1691 = 'WTI_U9', $1692 = 'WTI_V0', $1693 = 'WTI_V1', $1694 = 'WTI_V2', $1695 = 'WTI_V3', $1696 = 'WTI_V4', $1697 = 'WTI_V5', $1698 = 'WTI_V6', $1699 = 'WTI_V7', $1700 = 'WTI_V8', $1701 = 'WTI_V9', $1702 = 'WTI_X0', $1703 = 'WTI_X1', $1704 = 'WTI_X2', $1705 = 'WTI_X3', $1706 = 'WTI_X4', $1707 = 'WTI_X5', $1708 = 'WTI_X6', $1709 = 'WTI_X7', $1710 = 'WTI_X8', $1711 = 'WTI_X9', $1712 = 'WTI_Z0', $1713 = 'WTI_Z1', $1714 = 'WTI_Z2', $1715 = 'WTI_Z3', $1716 = 'WTI_Z4', $1717 = 'WTI_Z5', $1718 = 'WTI_Z6', $1719 = 'WTI_Z7', $1720 = 'WTI_Z8', $1721 = 'WTI_Z9', $1722 = 'Wheat_F0', $1723 = 'Wheat_F1', $1724 = 'Wheat_F2', $1725 = 'Wheat_F3', $1726 = 'Wheat_F4', $1727 = 'Wheat_F5', $1728 = 'Wheat_F6', $1729 = 'Wheat_F7', $1730 = 'Wheat_F8', $1731 = 'Wheat_F9', $1732 = 'Wheat_G0', $1733 = 'Wheat_G1', $1734 = 'Wheat_G2', $1735 = 'Wheat_G3', $1736 = 'Wheat_G4', $1737 = 'Wheat_G5', $1738 = 'Wheat_G6', $1739 = 'Wheat_G7', $1740 = 'Wheat_G8', $1741 = 'Wheat_G9', $1742 = 'Wheat_H0', $1743 = 'Wheat_H1', $1744 = 'Wheat_H2', $1745 = 'Wheat_H3', $1746 = 'Wheat_H4', $1747 = 'Wheat_H5', $1748 = 'Wheat_H6', $1749 = 'Wheat_H7', $1750 = 'Wheat_H8', $1751 = 'Wheat_H9', $1752 = 'Wheat_J0', $1753 = 'Wheat_J1', $1754 = 'Wheat_J2', $1755 = 'Wheat_J3', $1756 = 'Wheat_J4', $1757 = 'Wheat_J5', $1758 = 'Wheat_J6', $1759 = 'Wheat_J7', $1760 = 'Wheat_J8', $1761 = 'Wheat_J9', $1762 = 'Wheat_K0', $1763 = 'Wheat_K1', $1764 = 'Wheat_K2', $1765 = 'Wheat_K3', $1766 = 'Wheat_K4', $1767 = 'Wheat_K5', $1768 = 'Wheat_K6', $1769 = 'Wheat_K7', $1770 = 'Wheat_K8', $1771 = 'Wheat_K9', $1772 = 'Wheat_M0', $1773 = 'Wheat_M1', $1774 = 'Wheat_M2', $1775 = 'Wheat_M3', $1776 = 'Wheat_M4', $1777 = 'Wheat_M5', $1778 = 'Wheat_M6', $1779 = 'Wheat_M7', $1780 = 'Wheat_M8', $1781 = 'Wheat_M9', $1782 = 'Wheat_N0', $1783 = 'Wheat_N1', $1784 = 'Wheat_N2', $1785 = 'Wheat_N3', $1786 = 'Wheat_N4', $1787 = 'Wheat_N5', $1788 = 'Wheat_N6', $1789 = 'Wheat_N7', $1790 = 'Wheat_N8', $1791 = 'Wheat_N9', $1792 = 'Wheat_Q0', $1793 = 'Wheat_Q1', $1794 = 'Wheat_Q2', $1795 = 'Wheat_Q3', $1796 = 'Wheat_Q4', $1797 = 'Wheat_Q5', $1798 = 'Wheat_Q6', $1799 = 'Wheat_Q7', $1800 = 'Wheat_Q8', $1801 = 'Wheat_Q9', $1802 = 'Wheat_U0', $1803 = 'Wheat_U1', $1804 = 'Wheat_U2', $1805 = 'Wheat_U3', $1806 = 'Wheat_U4', $1807 = 'Wheat_U5', $1808 = 'Wheat_U6', $1809 = 'Wheat_U7', $1810 = 'Wheat_U8', $1811 = 'Wheat_U9', $1812 = 'Wheat_V0', $1813 = 'Wheat_V1', $1814 = 'Wheat_V2', $1815 = 'Wheat_V3', $1816 = 'Wheat_V4', $1817 = 'Wheat_V5', $1818 = 'Wheat_V6', $1819 = 'Wheat_V7', $1820 = 'Wheat_V8', $1821 = 'Wheat_V9', $1822 = 'Wheat_X0', $1823 = 'Wheat_X1', $1824 = 'Wheat_X2', $1825 = 'Wheat_X3', $1826 = 'Wheat_X4', $1827 = 'Wheat_X5', $1828 = 'Wheat_X6', $1829 = 'Wheat_X7', $1830 = 'Wheat_X8', $1831 = 'Wheat_X9', $1832 = 'Wheat_Z0', $1833 = 'Wheat_Z1', $1834 = 'Wheat_Z2', $1835 = 'Wheat_Z3', $1836 = 'Wheat_Z4', $1837 = 'Wheat_Z5', $1838 = 'Wheat_Z6', $1839 = 'Wheat_Z7', $1840 = 'Wheat_Z8', $1841 = 'Wheat_Z9', $1842 = 'XAGEUR', $1843 = 'XAGUSD', $1844 = 'XAUEUR', $1845 = 'XAUUSD', $1846 = 'XBRUSD', $1847 = 'XNGUSD', $1848 = 'XPDUSD', $1849 = 'XPTUSD', $1850 = 'XTIUSD'
13 368ms 6,080 0ms 1ms 0ms select category, ;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 13 6,080 368ms 0ms [ User: postgres - Total duration: 373ms - Times executed: 6080 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 373ms - Times executed: 6080 ]
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select category, ;
Date: 2025-09-17 13:52:30 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.54 parameters: $1 = '601729875344536307', $2 = 'symbol', $3 = 'USDMXN', $4 = 'USDSEK', $5 = 'XAGEUR', $6 = 'CADJPY', $7 = 'AUDJPY', $8 = 'USDZAR', $9 = 'NZDJPY', $10 = 'EURJPY', $11 = 'XAGUSD', $12 = 'CHFJPY', $13 = 'GBPJPY', $14 = 'XAUUSD', $15 = 'USDJPY', $16 = 'ZARJPY', $17 = 'USDHUF', $18 = 'GBPZAR', $19 = 'USDCZK', $20 = 'XAUEUR', $21 = 'USDPLN', $22 = 'USDCNH', $23 = 'USDNOK', $24 = 'EURHUF', $25 = 'USDDKK', $26 = 'GBPNZD', $27 = 'EURNOK', $28 = 'EURPLN', $29 = 'EURHUF', $30 = 'GBPAUD', $31 = 'USDTRY', $32 = 'EURNZD', $33 = 'ZARJPY', $34 = 'EURAUD', $35 = 'GBPCAD', $36 = 'XAGEUR', $37 = 'EURGBP', $38 = 'GBPUSD', $39 = 'EURCHF', $40 = 'EURCAD', $41 = 'USDMXN', $42 = 'CADCHF', $43 = 'USDHUF', $44 = 'XAUEUR', $45 = 'USDSGD', $46 = 'GBPCHF', $47 = 'EURPLN', $48 = 'XAGUSD', $49 = 'USDCAD', $50 = 'USDPLN', $51 = 'EURCAD', $52 = 'USDSEK', $53 = '601729875344536307', $54 = 'symbol', $55 = 'USDMXN', $56 = 'USDSEK', $57 = 'XAGEUR', $58 = 'CADJPY', $59 = 'AUDJPY', $60 = 'USDZAR', $61 = 'NZDJPY', $62 = 'EURJPY', $63 = 'XAGUSD', $64 = 'CHFJPY', $65 = 'GBPJPY', $66 = 'XAUUSD', $67 = 'USDJPY', $68 = 'ZARJPY', $69 = 'USDHUF', $70 = 'GBPZAR', $71 = 'USDCZK', $72 = 'XAUEUR', $73 = 'USDPLN', $74 = 'USDCNH', $75 = 'USDNOK', $76 = 'EURHUF', $77 = 'USDDKK', $78 = 'GBPNZD', $79 = 'EURNOK', $80 = 'EURPLN', $81 = 'EURHUF', $82 = 'GBPAUD', $83 = 'USDTRY', $84 = 'EURNZD', $85 = 'ZARJPY', $86 = 'EURAUD', $87 = 'GBPCAD', $88 = 'XAGEUR', $89 = 'EURGBP', $90 = 'GBPUSD', $91 = 'EURCHF', $92 = 'EURCAD', $93 = 'USDMXN', $94 = 'CADCHF', $95 = 'USDHUF', $96 = 'XAUEUR', $97 = 'USDSGD', $98 = 'GBPCHF', $99 = 'EURPLN', $100 = 'XAGUSD', $101 = 'USDCAD', $102 = 'USDPLN', $103 = 'EURCAD', $104 = 'USDSEK'
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select category, ;
Date: 2025-09-17 13:26:30 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '515852059317765307', $2 = 'symbol', $3 = 'AUDJPY', $4 = 'EURJPY', $5 = 'CHFJPY', $6 = 'GBPJPY', $7 = 'OIL', $8 = 'DOW30', $9 = 'NASDAQ100', $10 = 'USDJPY', $11 = 'SP500', $12 = 'XAGUSD', $13 = 'NZDJPY', $14 = 'XAUUSD', $15 = 'GBPAUD', $16 = 'EURAUD', $17 = 'RK_SSI', $18 = 'R_SSI', $19 = 'EURCAD', $20 = 'XAGUSD', $21 = 'EURCAD', $22 = 'EURUSD', $23 = 'EURCHF', $24 = 'GBPCHF', $25 = 'EURGBP', $26 = 'USDCAD', $27 = 'AUDNZD', $28 = 'GBPUSD', $29 = 'EURAUD', $30 = 'AUDUSD', $31 = 'EURJPY', $32 = 'OIL', $33 = 'DOW30', $34 = 'USDCAD', $35 = 'GBPAUD', $36 = 'EURUSD', $37 = 'AUDJPY', $38 = 'USDCHF', $39 = 'NZDUSD', $40 = 'CHFJPY', $41 = 'SP500', $42 = 'AUDUSD', $43 = 'GBPUSD', $44 = 'GBPJPY', $45 = 'NZDUSD', $46 = 'USDCHF', $47 = 'USDJPY', $48 = 'NZDJPY', $49 = 'XAUUSD', $50 = 'GBPCHF', $51 = 'NASDAQ100', $52 = 'EURCHF', $53 = '515852059317765307', $54 = 'symbol', $55 = 'AUDJPY', $56 = 'EURJPY', $57 = 'CHFJPY', $58 = 'GBPJPY', $59 = 'OIL', $60 = 'DOW30', $61 = 'NASDAQ100', $62 = 'USDJPY', $63 = 'SP500', $64 = 'XAGUSD', $65 = 'NZDJPY', $66 = 'XAUUSD', $67 = 'GBPAUD', $68 = 'EURAUD', $69 = 'RK_SSI', $70 = 'R_SSI', $71 = 'EURCAD', $72 = 'XAGUSD', $73 = 'EURCAD', $74 = 'EURUSD', $75 = 'EURCHF', $76 = 'GBPCHF', $77 = 'EURGBP', $78 = 'USDCAD', $79 = 'AUDNZD', $80 = 'GBPUSD', $81 = 'EURAUD', $82 = 'AUDUSD', $83 = 'EURJPY', $84 = 'OIL', $85 = 'DOW30', $86 = 'USDCAD', $87 = 'GBPAUD', $88 = 'EURUSD', $89 = 'AUDJPY', $90 = 'USDCHF', $91 = 'NZDUSD', $92 = 'CHFJPY', $93 = 'SP500', $94 = 'AUDUSD', $95 = 'GBPUSD', $96 = 'GBPJPY', $97 = 'NZDUSD', $98 = 'USDCHF', $99 = 'USDJPY', $100 = 'NZDJPY', $101 = 'XAUUSD', $102 = 'GBPCHF', $103 = 'NASDAQ100', $104 = 'EURCHF'
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select category, ;
Date: 2025-09-17 13:18:24 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '515852059313898307', $2 = 'symbol', $3 = 'BTCUSD', $4 = 'USDMXN', $5 = 'AUDJPY', $6 = 'USDTHB', $7 = 'EURJPY', $8 = 'USDZAR', $9 = 'CADJPY', $10 = 'SEKJPY', $11 = 'NZDJPY', $12 = 'CHFJPY', $13 = 'GBPJPY', $14 = 'USDHUF', $15 = 'USDSEK', $16 = 'USDJPY', $17 = 'EURZAR', $18 = 'NOKJPY', $19 = 'USDNOK', $20 = 'SGDJPY', $21 = 'EURTRY', $22 = 'EURHKD', $23 = 'EURNOK', $24 = 'USDCZK', $25 = 'USDDKK', $26 = 'GBPNOK', $27 = 'USDPLN', $28 = 'EURSEK', $29 = 'GBPDKK', $30 = 'GBPSEK', $31 = 'BTCUSD', $32 = 'USDCNH', $33 = 'GBPAUD', $34 = 'EURPLN', $35 = 'EURNZD', $36 = 'GBPNZD', $37 = 'EURAUD', $38 = 'USDTRY', $39 = 'GBPCAD', $40 = 'EURCAD', $41 = 'GBPCAD', $42 = 'EURSEK', $43 = 'GBPUSD', $44 = 'SEKJPY', $45 = 'CHFSGD', $46 = 'GBPNOK', $47 = 'GBPSGD', $48 = 'EURGBP', $49 = 'USDZAR', $50 = 'USDHUF', $51 = 'CHFSGD', $52 = 'GBPSGD', $53 = '515852059313898307', $54 = 'symbol', $55 = 'BTCUSD', $56 = 'USDMXN', $57 = 'AUDJPY', $58 = 'USDTHB', $59 = 'EURJPY', $60 = 'USDZAR', $61 = 'CADJPY', $62 = 'SEKJPY', $63 = 'NZDJPY', $64 = 'CHFJPY', $65 = 'GBPJPY', $66 = 'USDHUF', $67 = 'USDSEK', $68 = 'USDJPY', $69 = 'EURZAR', $70 = 'NOKJPY', $71 = 'USDNOK', $72 = 'SGDJPY', $73 = 'EURTRY', $74 = 'EURHKD', $75 = 'EURNOK', $76 = 'USDCZK', $77 = 'USDDKK', $78 = 'GBPNOK', $79 = 'USDPLN', $80 = 'EURSEK', $81 = 'GBPDKK', $82 = 'GBPSEK', $83 = 'BTCUSD', $84 = 'USDCNH', $85 = 'GBPAUD', $86 = 'EURPLN', $87 = 'EURNZD', $88 = 'GBPNZD', $89 = 'EURAUD', $90 = 'USDTRY', $91 = 'GBPCAD', $92 = 'EURCAD', $93 = 'GBPCAD', $94 = 'EURSEK', $95 = 'GBPUSD', $96 = 'SEKJPY', $97 = 'CHFSGD', $98 = 'GBPNOK', $99 = 'GBPSGD', $100 = 'EURGBP', $101 = 'USDZAR', $102 = 'USDHUF', $103 = 'CHFSGD', $104 = 'GBPSGD'
14 286ms 3,469 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 13 3,469 286ms 0ms [ User: postgres - Total duration: 1s880ms - Times executed: 3469 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s880ms - Times executed: 3469 ]
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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: 2025-09-17 13:30:55 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-09-17 14:00:00', $2 = '112.16', $3 = '112.51', $4 = '112.09', $5 = '112.42', $6 = '475', $7 = '515840247891126300', $8 = '0', $9 = '2025-09-17 13:30:55.59', $10 = '2025-09-17 13:30:55.506', $11 = '112.16', $12 = '112.51', $13 = '112.09', $14 = '112.42', $15 = '475', $16 = '0', $17 = '2025-09-17 13:30:55.59', $18 = '2025-09-17 13:30:55.506'
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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: 2025-09-17 13:41:55 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-09-17 14:00:00', $2 = '24243.5', $3 = '24266.2', $4 = '24237', $5 = '24248', $6 = '2946', $7 = '515840248039147300', $8 = '0', $9 = '2025-09-17 13:41:55.538', $10 = '2025-09-17 13:41:55.5', $11 = '24243.5', $12 = '24266.2', $13 = '24237', $14 = '24248', $15 = '2946', $16 = '0', $17 = '2025-09-17 13:41:55.538', $18 = '2025-09-17 13:41:55.5'
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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: 2025-09-17 13:00:44 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-09-17 13:30:00', $2 = '106.335', $3 = '106.346', $4 = '106.303', $5 = '106.326', $6 = '1955', $7 = '515840247880157300', $8 = '0', $9 = '2025-09-17 13:00:44.06', $10 = '2025-09-17 13:00:43.947', $11 = '106.335', $12 = '106.346', $13 = '106.303', $14 = '106.326', $15 = '1955', $16 = '0', $17 = '2025-09-17 13:00:44.06', $18 = '2025-09-17 13:00:43.947'
15 212ms 2,247 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 #15
Day Hour Count Duration Avg duration 13 2,247 212ms 0ms [ User: postgres - Total duration: 1s38ms - Times executed: 2247 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s38ms - Times executed: 2247 ]
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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: 2025-09-17 13:00:50 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-09-17 13:00:00', $2 = '1.98205', $3 = '1.9823', $4 = '1.98083', $5 = '1.98116', $6 = '5724', $7 = '515840247884031300', $8 = '0', $9 = '2025-09-17 13:00:50.461', $10 = '2025-09-17 13:00:50.268', $11 = '1.98205', $12 = '1.9823', $13 = '1.98083', $14 = '1.98116', $15 = '5724', $16 = '0', $17 = '2025-09-17 13:00:50.461', $18 = '2025-09-17 13:00:50.268'
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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: 2025-09-17 13:10:56 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-09-17 12:00:00', $2 = '24267.5', $3 = '24278.2', $4 = '24256.5', $5 = '24264.3', $6 = '5316', $7 = '515840248039327300', $8 = '0', $9 = '2025-09-17 13:10:56.625', $10 = '2025-09-17 13:10:56.583', $11 = '24267.5', $12 = '24278.2', $13 = '24256.5', $14 = '24264.3', $15 = '5316', $16 = '0', $17 = '2025-09-17 13:10:56.625', $18 = '2025-09-17 13:10:56.583'
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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: 2025-09-17 13:01:02 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-09-17 13:00:00', $2 = '17.37547', $3 = '17.38711', $4 = '17.36655', $5 = '17.37556', $6 = '8587', $7 = '515840247968908300', $8 = '0', $9 = '2025-09-17 13:01:02.886', $10 = '2025-09-17 13:01:02.819', $11 = '17.37547', $12 = '17.38711', $13 = '17.36655', $14 = '17.37556', $15 = '8587', $16 = '0', $17 = '2025-09-17 13:01:02.886', $18 = '2025-09-17 13:01:02.819'
16 183ms 320 0ms 1ms 0ms SELECT absolutetimezoneoffset;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 13 320 183ms 0ms [ User: postgres - Total duration: 677ms - Times executed: 320 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 677ms - Times executed: 320 ]
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SELECT absolutetimezoneoffset;
Date: 2025-09-17 13:52:48 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.54 parameters: $1 = '538', $2 = 'Forex Majors'
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SELECT absolutetimezoneoffset;
Date: 2025-09-17 13:26:30 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '489', $2 = 'BROKER'
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SELECT absolutetimezoneoffset;
Date: 2025-09-17 13:22:37 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '538', $2 = 'Forex Majors'
17 129ms 141 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 #17
Day Hour Count Duration Avg duration 13 141 129ms 0ms [ User: postgres - Total duration: 897ms - Times executed: 141 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 828ms - Times executed: 132 ]
[ Application: [unknown] - Total duration: 69ms - Times executed: 9 ]
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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: 2025-09-17 13:17:01 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.42 parameters: $1 = '689', $2 = 'XAUUSD', $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: 2025-09-17 13:17:22 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '529', $2 = 'GBPJPY', $3 = '529'
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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: 2025-09-17 13:56:18 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '558', $2 = 'USDJPY', $3 = '558'
18 90ms 20 3ms 7ms 4ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 13 20 90ms 4ms [ User: postgres - Total duration: 2s323ms - Times executed: 20 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s323ms - Times executed: 20 ]
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-09-17 13:22:56 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '489', $2 = '489'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-09-17 13:31:31 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '1018', $2 = '1018'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-09-17 13:08:03 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '689', $2 = '689'
19 52ms 10,304 0ms 3ms 0ms SET extra_float_digits = 3;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 13 10,304 52ms 0ms [ User: postgres - Total duration: 101ms - Times executed: 10304 ]
[ Application: [unknown] - Total duration: 101ms - Times executed: 10304 ]
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SET extra_float_digits = 3;
Date: 2025-09-17 13:40:51 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
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SET extra_float_digits = 3;
Date: 2025-09-17 13:17:43 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
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SET extra_float_digits = 3;
Date: 2025-09-17 13:10:38 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
20 40ms 10,278 0ms 0ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 13 10,278 40ms 0ms [ User: postgres - Total duration: 118ms - Times executed: 10278 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 118ms - Times executed: 10278 ]
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-09-17 13:05:03 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: 2025-09-17 13:16:50 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: 2025-09-17 13:20:05 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
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Events
Log levels
Key values
- 675,575 Log entries
Events distribution
Key values
- 0 PANIC entries
- 2 FATAL entries
- 0 ERROR entries
- 0 WARNING entries
Most Frequent Errors/Events
Key values
- 2 Max number of times the same event was reported
- 2 Total events found
Rank Times reported Error 1 2 FATAL: connection to client lost
Times Reported Most Frequent Error / Event #1
Day Hour Count Sep 17 13 2 - FATAL: connection to client lost
Date: 2025-09-17 13:22:13 Database: acaweb_fx Application: PostgreSQL JDBC Driver User: postgres Remote: 192.168.1.15