-
Global information
- Generated on Fri Jun 27 07:00:23 2025
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2025-06-27_080000.log, ..., /home/postgres/pg_data/data/pg_log/postgresql-2025-06-27_084707.log
- Parsed 3,104,489 log entries in 1m22s
- Log start from 2025-06-27 08:00:00 to 2025-06-27 09:00:00
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Overview
Global Stats
- 214 Number of unique normalized queries
- 165,360 Number of queries
- 2h24m14s Total query duration
- 2025-06-27 08:00:00 First query
- 2025-06-27 08:59:59 Last query
- 3,016 queries/s at 2025-06-27 08:45:04 Query peak
- 2h24m14s Total query duration
- 8s556ms Prepare/parse total duration
- 1m18s Bind total duration
- 2h22m46s Execute total duration
- 0 Number of events
- 0 Number of unique normalized events
- 0 Max number of times the same event was reported
- 0 Number of cancellation
- 51 Total number of automatic vacuums
- 64 Total number of automatic analyzes
- 556 Number temporary file
- 147.01 MiB Max size of temporary file
- 6.74 MiB Average size of temporary file
- 3,463 Total number of sessions
- 12 sessions at 2025-06-27 08:45:04 Session peak
- 4d8h42m44s Total duration of sessions
- 1m48s Average duration of sessions
- 47 Average queries per session
- 2s499ms Average queries duration per session
- 1m46s Average idle time per session
- 3,475 Total number of connections
- 37 connections/s at 2025-06-27 08:58:48 Connection peak
- 2 Total number of databases
SQL Traffic
Key values
- 3,016 queries/s Query Peak
- 2025-06-27 08:45:04 Date
SELECT Traffic
Key values
- 2,960 queries/s Query Peak
- 2025-06-27 08:45:04 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 222 queries/s Query Peak
- 2025-06-27 08:01:09 Date
Queries duration
Key values
- 2h24m14s Total query duration
Prepared queries ratio
Key values
- 0.00 Ratio of bind vs prepare
- 0.00 % Ratio between prepared and "usual" statements
General Activity
↑ Back to the top of the General Activity tableDay Hour Count Min duration Max duration Avg duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jun 27 08 165,360 0ms 36s660ms 51ms 3m39s 3m52s 4m22s 09 0 0ms 0ms 0ms 0ms 0ms 0ms Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jun 27 08 114,717 26 2ms 4s615ms 24s14ms 31s259ms 09 0 0 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jun 27 08 31,556 2,512 16 96 1ms 742ms 1s275ms 4s246ms 09 0 0 0 0 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Jun 27 08 24,082 141,018 5.86 14.80% 09 0 0 0.00 0.00% Day Hour Count Average / Second Jun 27 08 3,475 0.97/s 09 0 0.00/s Day Hour Count Average Duration Average idle time Jun 27 08 3,463 1m48s 1m46s 09 0 0ms 0ms -
Connections
Established Connections
Key values
- 37 connections Connection Peak
- 2025-06-27 08:58:48 Date
Connections per database
Key values
- acaweb_fx Main Database
- 3,475 connections Total
Connections per user
Key values
- postgres Main User
- 3,475 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 1246 connections
- 3,475 Total connections
Host Count 127.0.0.1 114 192.168.0.216 100 192.168.0.236 7 192.168.0.74 364 192.168.1.127 1 192.168.1.145 120 192.168.1.15 409 192.168.1.20 152 192.168.1.201 9 192.168.1.239 6 192.168.1.49 7 192.168.1.8 7 192.168.1.90 52 192.168.1.97 7 192.168.2.126 62 192.168.2.182 12 192.168.2.205 12 192.168.2.82 47 192.168.3.199 36 192.168.4.142 1,246 192.168.4.150 10 192.168.4.185 1 192.168.4.238 16 192.168.4.246 9 192.168.4.33 60 192.168.4.98 330 [local] 279 -
Sessions
Simultaneous sessions
Key values
- 12 sessions Session Peak
- 2025-06-27 08:45:04 Date
Histogram of session times
Key values
- 2,624 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 3,463 sessions Total
Sessions per user
Key values
- postgres Main User
- 3,463 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 3,463 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 115 10m8s 5s288ms 192.168.0.216 100 43s31ms 430ms 192.168.0.236 1 14ms 14ms 192.168.0.74 363 4h9m6s 41s174ms 192.168.1.127 1 2s148ms 2s148ms 192.168.1.145 120 4h55s 2m 192.168.1.15 409 7h35m6s 1m6s 192.168.1.20 152 14h45m19s 5m49s 192.168.1.201 9 1d23h59m12s 5h19m54s 192.168.1.239 6 46ms 7ms 192.168.1.49 7 2h45m32s 23m38s 192.168.1.8 7 2h45m33s 23m39s 192.168.1.90 52 42s269ms 812ms 192.168.1.97 1 4ms 4ms 192.168.2.126 62 6s268ms 101ms 192.168.2.182 12 8s227ms 685ms 192.168.2.205 12 559ms 46ms 192.168.2.82 47 8s469ms 180ms 192.168.3.199 36 1s322ms 36ms 192.168.4.142 1,246 18m13s 877ms 192.168.4.150 10 20h2m8s 2h12s 192.168.4.185 1 224ms 224ms 192.168.4.238 16 26s505ms 1s656ms 192.168.4.246 9 4m40s 31s214ms 192.168.4.33 60 1m4s 1s79ms 192.168.4.98 330 19s981ms 60ms [local] 279 3m3s 656ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 32,180 buffers Checkpoint Peak
- 2025-06-27 08:29:17 Date
- 209.964 seconds Highest write time
- 0.010 seconds Sync time
Checkpoints Wal files
Key values
- 19 files Wal files usage Peak
- 2025-06-27 08:24:17 Date
Checkpoints distance
Key values
- 582.98 Mo Distance Peak
- 2025-06-27 08:24:17 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Jun 27 08 134,165 2,029.015s 0.054s 2,029.534s 09 0 0s 0s 0s Day Hour Added Removed Recycled Synced files Longest sync Average sync Jun 27 08 0 0 72 2,092 0.007s 0s 09 0 0 0 0 0s 0s Day Hour Count Avg time (sec) Jun 27 08 0 0s 09 0 0s Day Hour Mean distance Mean estimate Jun 27 08 98,853.58 kB 196,931.42 kB 09 0.00 kB 0.00 kB -
Temporary Files
Size of temporary files
Key values
- 162.35 MiB Temp Files size Peak
- 2025-06-27 08:40:08 Date
Number of temporary files
Key values
- 30 per second Temp Files Peak
- 2025-06-27 08:02:05 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Jun 27 08 556 3.66 GiB 6.74 MiB 09 0 0 0 Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 118 563.42 MiB 3.09 MiB 8.46 MiB 4.77 MiB with rar_max as ( ;-
WITH rar_max as ( ;
Date: 2025-06-27 08:47:25 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver
2 40 1.62 GiB 3.83 MiB 147.01 MiB 41.58 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-27 08:30:11 Duration: 8s91ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-27 08:00:10 Duration: 7s845ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-27 08:10:10 Duration: 7s319ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
3 16 372.25 MiB 23.27 MiB 23.27 MiB 23.27 MiB update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:31:12 Duration: 1s213ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:33:12 Duration: 1s178ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:03:12 Duration: 1s137ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
4 16 762.25 MiB 47.64 MiB 47.64 MiB 47.64 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:20:15 Duration: 2s541ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:01:15 Duration: 2s489ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:41:14 Duration: 2s25ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
5 8 155.61 MiB 19.45 MiB 19.45 MiB 19.45 MiB select updateresultsmaterializedview ();-
select updateresultsmaterializedview ();
Date: 2025-06-27 08:32:16 Duration: 4s248ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-06-27 08:02:13 Duration: 1s787ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-06-27 08:47:13 Duration: 1s770ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
6 5 225.56 MiB 24.31 MiB 56.47 MiB 45.11 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2025-06-27 08:32:12 Duration: 10s250ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-06-27 08:02:12 Duration: 9s954ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-06-27 08:17:12 Duration: 9s707ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
7 1 4.40 MiB 4.40 MiB 4.40 MiB 4.40 MiB select resultuid from relevance_fibonacci_results order by resultuid desc limit ?), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp)))), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;-
SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4, $5, $6, $7, $8, $9, $10)) AND ($11 = 0 OR s.exchange in ($12)) AND ($13 = 0 OR coalesce(bim.code, s.symbol) in ($14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226)) AND ($227 = 0 OR fr.pattern in ($228)) AND ($229 = 0 OR fr.patternlengthbars <= $230) AND ($231 = 0 OR ($232 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($233 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $234 OR relevant = 1) AND ($235 = 0 OR age <= $236) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-27 08:22:59 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver
Queries generating the largest temporary files
Rank Size Query 1 147.01 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-27 08:50:05 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
2 126.39 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-27 08:40:06 ]
3 108.47 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-27 08:10:04 ]
4 96.45 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-27 08:00:06 ]
5 94.99 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-27 08:20:04 ]
6 93.23 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-27 08:30:07 ]
7 77.24 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-27 08:10:05 ]
8 73.75 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-27 08:20:06 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
9 72.91 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-27 08:30:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
10 69.76 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: 2025-06-27 08:40:05 ]
11 67.47 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-27 08:00:08 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
12 56.47 MiB select updateageforrelevantresults ();[ Date: 2025-06-27 08:02:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
13 56.43 MiB select updateageforrelevantresults ();[ Date: 2025-06-27 08:32:07 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
14 56.31 MiB select updateageforrelevantresults ();[ Date: 2025-06-27 08:17:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
15 47.64 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2025-06-27 08:01:15 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
16 47.64 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2025-06-27 08:03:14 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
17 47.64 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2025-06-27 08:05:14 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
18 47.64 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2025-06-27 08:11:14 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
19 47.64 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2025-06-27 08:16:14 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
20 47.64 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2025-06-27 08:18:15 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
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Vacuums
Vacuums / Analyzes Distribution
Key values
- 0 sec Highest CPU-cost vacuum
Table
Database - Date
- 0 sec Highest CPU-cost analyze
Table
Database - Date
Analyzes per table
Key values
- public.solr_relevance_old (16) Main table analyzed (database acaweb_fx)
- 64 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 5 acaweb_fx.public.relevance_keylevels_results 4 acaweb_fx.pg_catalog.pg_class 4 acaweb_fx.public.relevance_fibonacci_results 4 acaweb_fx.pg_catalog.pg_type 4 acaweb_fx.public.relevance_autochartist_results 4 acaweb_fx.pg_catalog.pg_index 2 acaweb_fx.public.autochartist_symbolupdates 2 acaweb_fx.pg_catalog.pg_depend 2 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.public.mat_oldest_t15_candle_per_symbolid 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.autochartist_results 1 acaweb_fx.public.mat_oldest_t240_candle_per_symbolid 1 acaweb_fx.public.t240 1 acaweb_fx.public.relevance_consecutivecandles_results 1 acaweb_fx.public.symbollatestupdatetime 1 acaweb_fx.public.t15 1 Total 64 Vacuums per table
Key values
- public.solr_relevance_old (24) Main table vacuumed on database acaweb_fx
- 51 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 24 18 19,003 0 79 0 158 10,188 777 4,811,599 acaweb_fx.public.datafeeds_latestrun 4 0 481 0 7 0 0 69 7 55,136 acaweb_fx.pg_toast.pg_toast_2619 2 2 294 0 49 0 0 209 47 205,128 acaweb_fx.public.autochartist_symbolupdates 2 2 49,523 0 3,416 8 76,276 14,587 5,146 2,603,904 acaweb_fx.pg_catalog.pg_attribute 2 2 1,622 0 333 0 134 750 290 1,729,194 acaweb_fx.public.latest_t15_candle_view 2 2 129 0 4 0 0 12 1 9,910 acaweb_fx.public.relevance_keylevels_results 2 2 8,045 0 292 4 146 2,281 284 860,992 acaweb_fx.public.relevance_fibonacci_results 2 2 2,572 0 65 1 92 509 51 140,060 acaweb_fx.public.relevance_autochartist_results 2 2 7,129 0 198 0 445 1,720 186 570,684 acaweb_fx.pg_catalog.pg_index 1 1 91 0 11 0 0 28 10 75,241 acaweb_fx.public.solr_imports 1 1 43 0 3 0 0 6 2 14,033 acaweb_fx.public.mat_oldest_t15_candle_per_symbolid 1 1 93 0 2 0 0 54 26 106,436 acaweb_fx.pg_catalog.pg_class 1 1 369 0 45 0 40 155 42 189,525 acaweb_fx.pg_catalog.pg_type 1 1 136 0 28 0 0 54 22 112,395 acaweb_fx.public.t240 1 1 182,761 0 26,640 0 21,153 69,014 34,160 191,339,060 acaweb_fx.public.mat_oldest_t240_candle_per_symbolid 1 1 114 0 1 0 0 53 1 19,180 acaweb_fx.pg_catalog.pg_statistic 1 1 898 0 168 0 647 516 155 582,623 acaweb_fx.public.t15 1 1 610,089 0 51,934 0 135,553 123,882 52,028 193,193,355 Total 51 41 883,392 669,193 83,275 13 234,644 224,087 93,235 396,618,455 Tuples removed per table
Key values
- public.t15 (116882) Main table with removed tuples on database acaweb_fx
- 299481 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.t15 1 1 116,882 2,826,279 0 0 172,175 acaweb_fx.public.t240 1 1 82,101 1,582,538 0 0 41,499 acaweb_fx.public.solr_relevance_old 24 18 56,744 201,834 46,840 0 5,308 acaweb_fx.public.autochartist_symbolupdates 2 2 30,446 105,601 294 0 81,382 acaweb_fx.public.relevance_keylevels_results 2 2 3,492 24,936 0 0 558 acaweb_fx.public.relevance_autochartist_results 2 2 3,153 18,504 0 0 760 acaweb_fx.pg_catalog.pg_attribute 2 2 2,495 19,250 504 0 500 acaweb_fx.public.mat_oldest_t240_candle_per_symbolid 1 1 1,193 1,530 0 0 15 acaweb_fx.public.mat_oldest_t15_candle_per_symbolid 1 1 782 1,262 0 0 14 acaweb_fx.pg_catalog.pg_statistic 1 1 679 4,234 0 0 1,194 acaweb_fx.public.relevance_fibonacci_results 2 2 611 3,354 0 0 204 acaweb_fx.public.datafeeds_latestrun 4 0 246 56 0 0 64 acaweb_fx.pg_catalog.pg_class 1 1 180 1,947 0 0 150 acaweb_fx.pg_toast.pg_toast_2619 2 2 154 338 1 0 101 acaweb_fx.pg_catalog.pg_type 1 1 149 1,338 0 0 38 acaweb_fx.public.latest_t15_candle_view 2 2 104 42 14 0 2 acaweb_fx.public.solr_imports 1 1 52 1 0 0 2 acaweb_fx.pg_catalog.pg_index 1 1 18 825 12 0 22 Total 51 41 299,481 4,793,869 47,665 0 303,988 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 18 0 acaweb_fx.pg_toast.pg_toast_2619 2 2 154 0 acaweb_fx.public.datafeeds_latestrun 4 0 246 0 acaweb_fx.public.autochartist_symbolupdates 2 2 30446 0 acaweb_fx.pg_catalog.pg_attribute 2 2 2495 0 acaweb_fx.public.solr_imports 1 1 52 0 acaweb_fx.public.latest_t15_candle_view 2 2 104 0 acaweb_fx.public.mat_oldest_t15_candle_per_symbolid 1 1 782 0 acaweb_fx.public.relevance_keylevels_results 2 2 3492 0 acaweb_fx.pg_catalog.pg_class 1 1 180 0 acaweb_fx.public.relevance_fibonacci_results 2 2 611 0 acaweb_fx.pg_catalog.pg_type 1 1 149 0 acaweb_fx.public.t240 1 1 82101 0 acaweb_fx.public.mat_oldest_t240_candle_per_symbolid 1 1 1193 0 acaweb_fx.pg_catalog.pg_statistic 1 1 679 0 acaweb_fx.public.relevance_autochartist_results 2 2 3153 0 acaweb_fx.public.t15 1 1 116882 0 acaweb_fx.public.solr_relevance_old 24 18 56744 0 Total 51 41 299,481 0 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Jun 27 08 51 64 09 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
- 114,717 Total read queries
- 47,958 Total write queries
Queries by database
Key values
- acaweb_fx Main database
- 158,206 Requests
- 2h22m36s (acaweb_fx)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 158,206 2h22m36s copy from 96 6s25ms copy to 26 7s242ms cte 13,076 2h16m15s ddl 16 514ms delete 16 22ms insert 24,744 28s888ms others 2,683 15s46ms select 114,377 5m4s tcl 660 192ms update 2,512 19s199ms socialmedia Total 7,154 9s838ms insert 6,812 7s846ms others 2 0ms select 340 1s992ms Queries by user
Key values
- postgres Main user
- 165,360 Requests
User Request type Count Duration postgres Total 165,360 2h22m46s copy from 96 6s25ms copy to 26 7s242ms cte 13,076 2h16m15s ddl 16 514ms delete 16 22ms insert 31,556 36s734ms others 2,685 15s46ms select 114,717 5m6s tcl 660 192ms update 2,512 19s199ms Duration by user
Key values
- 2h22m46s (postgres) Main time consuming user
User Request type Count Duration postgres Total 165,360 2h22m46s copy from 96 6s25ms copy to 26 7s242ms cte 13,076 2h16m15s ddl 16 514ms delete 16 22ms insert 31,556 36s734ms others 2,685 15s46ms select 114,717 5m6s tcl 660 192ms update 2,512 19s199ms Queries by host
Key values
- 192.168.1.145 Main host
- 38,586 Requests
- 40m58s (192.168.1.15)
- Main time consuming host
Host Request type Count Duration 127.0.0.1 Total 14,433 49s500ms copy to 26 7s242ms cte 25 284ms insert 11,759 17s888ms others 3 0ms select 627 22s178ms update 1,993 1s906ms 182.165.1.42 Total 104 218ms select 104 218ms 192.168.0.216 Total 400 337ms others 200 20ms select 192 212ms update 8 104ms 192.168.0.236 Total 104 70ms cte 12 38ms others 7 0ms select 85 32ms 192.168.0.239 Total 627 2s293ms select 627 2s293ms 192.168.0.42 Total 1,034 1s865ms insert 225 26ms select 809 1s839ms 192.168.0.74 Total 17,809 32m30s cte 5,090 32m25s others 728 8ms select 11,991 5s285ms 192.168.1.127 Total 222 1s903ms others 2 0ms select 220 1s903ms 192.168.1.135 Total 126 858ms cte 11 288ms select 115 570ms 192.168.1.145 Total 38,586 31m43s cte 873 30m37s others 240 2ms select 37,473 1m5s 192.168.1.15 Total 26,350 40m58s cte 5,436 40m47s others 818 9ms select 20,096 10s804ms 192.168.1.20 Total 34,576 31m37s cte 888 30m43s others 304 3ms select 33,384 54s172ms 192.168.1.201 Total 2,062 4s436ms others 18 0ms select 2,044 4s436ms 192.168.1.23 Total 2,159 5s662ms select 2,159 5s662ms 192.168.1.239 Total 24 18ms others 12 1ms select 12 16ms 192.168.1.49 Total 96 82ms cte 11 39ms others 7 0ms select 78 43ms 192.168.1.8 Total 104 102ms cte 12 26ms others 7 0ms select 85 76ms 192.168.1.90 Total 60 39s999ms cte 6 39s951ms others 8 0ms select 46 47ms 192.168.1.93 Total 4 0ms select 4 0ms 192.168.1.97 Total 92 96ms cte 12 29ms others 7 0ms select 73 67ms 192.168.2.126 Total 80 72ms others 18 0ms select 62 72ms 192.168.2.182 Total 48 366ms others 24 2ms select 12 12ms update 12 352ms 192.168.2.205 Total 137 108ms insert 89 9ms others 24 2ms select 20 21ms update 4 75ms 192.168.2.82 Total 757 1s601ms insert 407 825ms others 94 10ms select 157 99ms update 99 666ms 192.168.3.199 Total 144 274ms others 72 8ms select 60 70ms update 12 195ms 192.168.4.142 Total 13,763 11s497ms insert 12,264 10s138ms select 1,499 1s358ms 192.168.4.150 Total 22 1s171ms others 21 0ms select 1 1s171ms 192.168.4.185 Total 3 98ms cte 1 98ms others 2 0ms 192.168.4.238 Total 48 25s443ms cte 16 25s442ms others 32 0ms 192.168.4.246 Total 3,115 2s807ms cte 587 2s319ms others 27 0ms select 2,501 487ms 192.168.4.33 Total 6,932 7s934ms insert 6,812 7s846ms select 120 88ms 192.168.4.98 Total 996 15s674ms others 6 14s730ms select 6 27ms tcl 660 192ms update 324 725ms [local] Total 343 3m2s copy from 96 6s25ms cte 96 33s576ms ddl 16 514ms delete 16 22ms others 4 246ms select 55 2m7s update 60 15s174ms Queries by application
Key values
- PostgreSQL JDBC Driver Main application
- 125,431 Requests
- 2h17m34s (PostgreSQL JDBC Driver)
- Main time consuming application
Application Request type Count Duration PostgreSQL JDBC Driver Total 125,431 2h17m34s cte 12,902 2h15m1s insert 225 26ms others 1,101 14ms select 111,203 2m32s [unknown] Total 39,473 2m2s cte 53 40s85ms insert 31,331 36s708ms others 1,580 14s786ms select 3,407 26s391ms tcl 660 192ms update 2,442 4s5ms psql Total 456 3m10s copy from 96 6s25ms copy to 26 7s242ms cte 121 33s860ms ddl 16 514ms delete 16 22ms others 4 246ms select 107 2m7s update 70 15s194ms Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2025-06-27 08:02:46 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 100,751 0-1ms duration
Slowest individual queries
Rank Duration Query 1 36s660ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:10:20 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
2 34s78ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:15:26 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
3 34s26ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:15:32 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
4 33s594ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:00:59 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
5 33s30ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:34:23 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
6 32s967ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:31:49 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
7 32s750ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:58:59 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
8 32s730ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:55:23 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
9 32s696ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:20:48 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
10 32s675ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:48:14 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
11 32s636ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:49:55 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
12 32s493ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:26:31 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
13 32s316ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:39:48 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
14 32s263ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:29:00 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
15 32s101ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:08:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
16 31s873ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:38:44 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
17 31s680ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-27 08:44:50 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
18 22s752ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-06-27 08:34:30 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
19 21s334ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-06-27 08:30:48 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
20 20s943ms 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: 2025-06-27 08:16:05 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
Time consuming queries
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 58m9s 444 375ms 22s752ms 7s858ms with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ), ar as ( select a.*, rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end ), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on sg.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jun 27 08 444 58m9s 7s858ms [ User: postgres - Total duration: 58m9s - Times executed: 444 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 58m9s - Times executed: 444 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-27 08:34:30 Duration: 22s752ms 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 ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-27 08:30:48 Duration: 21s334ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '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: 2025-06-27 08:16:05 Duration: 20s943ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
2 54m39s 445 204ms 36s660ms 7s370ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Jun 27 08 445 54m39s 7s370ms [ User: postgres - Total duration: 54m39s - Times executed: 445 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 54m39s - Times executed: 445 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-06-27 08:10:20 Duration: 36s660ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-06-27 08:15:26 Duration: 34s78ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-06-27 08:15:32 Duration: 34s26ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
3 17m52s 406 598ms 7s945ms 2s641ms with rar_max as ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ? ), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end ), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp))) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jun 27 08 406 17m52s 2s641ms [ User: postgres - Total duration: 17m52s - Times executed: 406 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 17m52s - Times executed: 406 ]
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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 ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-27 08:30:41 Duration: 7s945ms 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 = '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 ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-27 08:30:55 Duration: 6s379ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('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 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 ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-27 08:25:58 Duration: 6s260ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
4 2m22s 267 102ms 1s901ms 534ms with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Jun 27 08 267 2m22s 534ms [ User: postgres - Total duration: 2m22s - Times executed: 267 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m22s - Times executed: 267 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-27 08:27:48 Duration: 1s901ms 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 ('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 ccr.patternlengthbars <= '0') ), 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;
Date: 2025-06-27 08:44:51 Duration: 1s590ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' 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 ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-27 08:30:58 Duration: 1s458ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
5 1m21s 21,783 0ms 46ms 3ms select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Jun 27 08 21,783 1m21s 3ms [ User: postgres - Total duration: 1m21s - Times executed: 21783 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m21s - Times executed: 21783 ]
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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 = 'UK100' OR dss.downloadersymbol = 'UK100') AND dss.enabled = 1;
Date: 2025-06-27 08:00:06 Duration: 46ms 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 = 'HK50' OR dss.downloadersymbol = 'HK50') AND dss.enabled = 1;
Date: 2025-06-27 08:15:05 Duration: 30ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'JPM.US' OR dss.downloadersymbol = 'JPM.US') AND dss.enabled = 1;
Date: 2025-06-27 08:00:05 Duration: 30ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
6 1m20s 195 88ms 2s762ms 414ms 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 #6
Day Hour Count Duration Avg duration Jun 27 08 195 1m20s 414ms [ User: postgres - Total duration: 1m20s - Times executed: 195 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m20s - Times executed: 195 ]
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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 = '667' 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 = '667' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-06-27 08:32:23 Duration: 2s762ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '667' 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 = '667' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-06-27 08:20:47 Duration: 2s440ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '689' 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 = '689' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-06-27 08:12:15 Duration: 1s356ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
7 46s278ms 31,184 0ms 34ms 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 #7
Day Hour Count Duration Avg duration Jun 27 08 31,184 46s278ms 1ms [ User: postgres - Total duration: 46s278ms - Times executed: 31184 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 46s278ms - Times executed: 31184 ]
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243225790300';
Date: 2025-06-27 08:00:06 Duration: 34ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840249432335300';
Date: 2025-06-27 08:00:05 Duration: 30ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243171165300';
Date: 2025-06-27 08:00:05 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
8 39s951ms 6 5s42ms 8s91ms 6s658ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Jun 27 08 6 39s951ms 6s658ms [ User: postgres - Total duration: 39s951ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 39s951ms - Times executed: 6 ]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-27 08:30:11 Duration: 8s91ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-27 08:00:10 Duration: 7s845ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-27 08:10:10 Duration: 7s319ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
9 38s875ms 4 8s962ms 10s250ms 9s718ms select updateageforrelevantresults ();Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jun 27 08 4 38s875ms 9s718ms [ User: postgres - Total duration: 38s875ms - Times executed: 4 ]
[ Application: psql - Total duration: 38s875ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-06-27 08:32:12 Duration: 10s250ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-06-27 08:02:12 Duration: 9s954ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-06-27 08:17:12 Duration: 9s707ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
10 31s389ms 16 1s798ms 2s541ms 1s961ms with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Jun 27 08 16 31s389ms 1s961ms [ User: postgres - Total duration: 31s389ms - Times executed: 16 ]
[ Application: psql - Total duration: 31s389ms - Times executed: 16 ]
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:20:15 Duration: 2s541ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:01:15 Duration: 2s489ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:41:14 Duration: 2s25ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 30s166ms 34 12ms 11s8ms 887ms select fixcandlegaps (?, false);Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jun 27 08 34 30s166ms 887ms [ User: postgres - Total duration: 30s166ms - Times executed: 34 ]
[ Application: psql - Total duration: 30s166ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-06-27 08:06:32 Duration: 11s8ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-06-27 08:06:09 Duration: 3s802ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('AXIORY', false);
Date: 2025-06-27 08:06:12 Duration: 2s846ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
12 25s442ms 16 1s335ms 2s135ms 1s590ms with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = ? left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bg.brokerid and bim.type = ? where bg.brokerid = ? and basegroupname = ? and g.designation = ? and s.nonliquid = ? ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= ? and patternquality >= ?.? and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, case when direction > ? then ? else ? end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (...) and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= ? and _tmp.qtycandlesapart <= ? and ((cpresultuid > ( select coalesce(max(cpresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?)) or (klresultuid > ( select coalesce(max(klresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = ? and cs.basegroupname = ? and date_trunc(?, cs.gmttimefound) = date_trunc(?, now()) and sent is true and filtered is false ) <= ( select case when coalesce(daily_max, ?) < ? then ? else coalesce(daily_max,?) end from corr_sigs_config_v where broker_id = ? limit ? ) and extract(epoch from age(current_timestamp at time zone ?, max_patternendtime - absolutetimezoneoffset * interval ?))/? < mint*? ), maxstats as ( select max(statsid) as maxid , st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = ? then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * ? as numeric), ?) as percent, round(cast((kl_correct) / (kl_total) * ? as numeric), ?) as klpercent, round(cast((cp_correct ) / (cp_total ) * ? as numeric), ?) as cppercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), ?) as openprice, round(cast(sig.forecastprice as numeric), ?) as forecastprice, cast(round(cast(abs(sig.forecastprice - sig.openprice)/pip as numeric), ?)as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname , si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = ? then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = ? and date_part(?, sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = ? and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = ? and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = ? and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = ? and date_part(?, sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = ? and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = ? and kl_sym.name ilike si.symbol ) as tmp order by tmp.gmttimefound desc;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jun 27 08 16 25s442ms 1s590ms [ User: postgres - Total duration: 25s442ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 25s442ms - Times executed: 16 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '627' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '627' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '627' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-06-27 08:07:05 Duration: 2s135ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '627' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '627' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '627' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-06-27 08:21:56 Duration: 1s932ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '627' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '627' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '627' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-06-27 08:37:01 Duration: 1s794ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
13 18s831ms 1 18s831ms 18s831ms 18s831ms select cleanupt15 (?, ?, ?); refresh materialized view concurrently mat_oldest_t15_candle_per_symbolid;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jun 27 08 1 18s831ms 18s831ms [ User: postgres - Total duration: 18s831ms - Times executed: 1 ]
[ Application: psql - Total duration: 18s831ms - Times executed: 1 ]
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select cleanupt15 (15, 5, 20); refresh materialized view concurrently mat_oldest_t15_candle_per_symbolid;
Date: 2025-06-27 08:20:20 Duration: 18s831ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
14 15s781ms 8 1s511ms 4s248ms 1s972ms select updateresultsmaterializedview ();Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Jun 27 08 8 15s781ms 1s972ms [ User: postgres - Total duration: 15s781ms - Times executed: 8 ]
[ Application: psql - Total duration: 15s781ms - Times executed: 8 ]
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select updateresultsmaterializedview ();
Date: 2025-06-27 08:32:16 Duration: 4s248ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-06-27 08:02:13 Duration: 1s787ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-06-27 08:47:13 Duration: 1s770ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
15 14s730ms 6 1s63ms 5s442ms 2s455ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Jun 27 08 6 14s730ms 2s455ms [ User: postgres - Total duration: 14s730ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 14s730ms - Times executed: 6 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-27 08:31:21 Duration: 5s442ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-27 08:46:20 Duration: 4s345ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-27 08:01:18 Duration: 1s688ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
16 14s700ms 16 660ms 1s213ms 918ms 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 #16
Day Hour Count Duration Avg duration Jun 27 08 16 14s700ms 918ms [ User: postgres - Total duration: 14s700ms - Times executed: 16 ]
[ Application: psql - Total duration: 14s700ms - Times executed: 16 ]
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:31:12 Duration: 1s213ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:33:12 Duration: 1s178ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:03:12 Duration: 1s137ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
17 11s257ms 151 16ms 347ms 74ms select distinct k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid from relevance_keylevels_results p inner join keylevels_results k on p.resultuid = k.resultuid inner join autochartist_stocklist asl on k.symbolid = asl.symbolid where k.patternclassid in (...) and asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Jun 27 08 151 11s257ms 74ms [ User: postgres - Total duration: 11s257ms - Times executed: 151 ]
[ Application: [unknown] - Total duration: 11s257ms - Times executed: 151 ]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-06-27 08:30:06 Duration: 347ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-06-27 08:15:54 Duration: 220ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-06-27 08:30:56 Duration: 200ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
18 10s726ms 151 18ms 363ms 71ms 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 #18
Day Hour Count Duration Avg duration Jun 27 08 151 10s726ms 71ms [ User: postgres - Total duration: 10s726ms - Times executed: 151 ]
[ Application: [unknown] - Total duration: 10s726ms - Times executed: 151 ]
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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: 2025-06-27 08:30:05 Duration: 363ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2025-06-27 08:30:53 Duration: 216ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-06-27 08:01:22 Duration: 216ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
19 9s584ms 6,673 0ms 17ms 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 #19
Day Hour Count Duration Avg duration Jun 27 08 6,673 9s584ms 1ms [ User: postgres - Total duration: 9s584ms - Times executed: 6673 ]
[ Application: [unknown] - Total duration: 9s584ms - Times executed: 6673 ]
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INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('5158402432248563000.386|45834.7083|45835.2083|45834.875|45835.25|18.9384|18.8747|18.8481|18.8574', 515840243224856300, 2.000000000000000000000000000000, 'Triangle', 4, '2025-06-27 05:57:41'::timestamp without time zone, 1, 0.393296664455829447800000000000, 0.385971548046518675400000000000, 0.486064713618637844800000000000, 0.085358497015437531650000000000, 0.848920500729870353200000000000, 18.897178088754397860000000000000, 18.937383413010554280000000000000, '2025-06-27 07:00:00'::timestamp without time zone, '2025-06-27 14:00:00'::timestamp without time zone, '2025-06-26 15:00:00'::timestamp without time zone, '2025-06-27 07:00:00'::timestamp without time zone, 18.845109999999998250000000000000, 18.864086666666668890000000000000, '2025-06-26 17:00:00'::timestamp without time zone, '2025-06-27 05:00:00'::timestamp without time zone, '2025-06-26 21:00:00'::timestamp without time zone, '2025-06-27 06:00:00'::timestamp without time zone, 18.938449999999999560000000000000, 18.874710000000000320000000000000, 18.848099999999998740000000000000, 18.857379999999999140000000000000, 0.001031111111111155353000000000, - 0.005311666666666603476000000000, 2.745047313302698466000000000000, 0.635707554054195211900000000000, 'Continuation', 0.003663333333332019492000000000, '2025-06-27 07:00:00'::timestamp without time zone, 18.868459999999998900000000000000, 14, 0, 0.022381666666667261040000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-27 08:02:12 Duration: 17ms 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 ('515840245887141300-1|45831.8125|45835.3542|45832.7083|45834.7708|403.77|399.357|400.12|398.434', 515840245887141300, 4.000000000000000000000000000000, 'Falling Wedge', 5, '2025-06-27 06:26:25'::timestamp without time zone, - 1, 0.552864915407084711600000000000, - 1.000000000000000000000000000000, 0.000000000000000000000000000000, 0.119685332738642527500000000000, 0.795370202024570316400000000000, 395.597317314348231300000000000000, 397.495298880978452900000000000000, '2025-06-27 09:00:00'::timestamp without time zone, '2025-06-29 03:45:00'::timestamp without time zone, '2025-06-20 14:30:00'::timestamp without time zone, '2025-06-27 09:00:00'::timestamp without time zone, 401.677000000000020900000000000000, 398.833000000000026800000000000000, '2025-06-23 19:30:00'::timestamp without time zone, '2025-06-27 08:30:00'::timestamp without time zone, '2025-06-24 17:00:00'::timestamp without time zone, '2025-06-26 18:30:00'::timestamp without time zone, 403.769999999999981800000000000000, 399.357000000000027800000000000000, 400.120000000000004600000000000000, 398.434000000000025900000000000000, - 0.017030303030302815920000000000, - 0.025958823529411496200000000000, 3.888779781863425988000000000000, 0.742849928231004153000000000000, 'Reversal', 0.000000000000000000000000000000, '2025-06-27 09:00:00'::timestamp without time zone, 398.850999999999999100000000000000, 171, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-27 08:30:56 Duration: 17ms 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 ('515840249482774300-1|45834.5208|45834.9792|45834.7083|45835.0625|1.3771|1.3749|1.3704|1.3719', 515840249482774300, 2.000000000000000000000000000000, 'Triangle', 4, '2025-06-27 06:26:00'::timestamp without time zone, 1, 0.418530949964878606900000000000, - 1.000000000000000000000000000000, 0.187511573909203560500000000000, 0.118365519101517532900000000000, 0.625712562895413770800000000000, 1.375344514776416060000000000000, 1.378332835463398354000000000000, '2025-06-27 02:00:00'::timestamp without time zone, '2025-06-27 08:45:00'::timestamp without time zone, '2025-06-26 07:30:00'::timestamp without time zone, '2025-06-27 02:00:00'::timestamp without time zone, 1.369799999999999907000000000000, 1.373480000000000034000000000000, '2025-06-26 12:30:00'::timestamp without time zone, '2025-06-26 23:30:00'::timestamp without time zone, '2025-06-26 17:00:00'::timestamp without time zone, '2025-06-27 01:30:00'::timestamp without time zone, 1.377099999999999991000000000000, 1.374900000000000011000000000000, 1.370449999999999946000000000000, 1.371899999999999897000000000000, 0.000085294117647055956480000000, - 0.000099999999999999083220000000, 2.792978807405853470000000000000, 0.641959331252924925200000000000, 'Continuation', 0.000000000000000000000000000000, '2025-06-27 02:00:00'::timestamp without time zone, 1.373210000000000042000000000000, 27, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-27 08:30:30 Duration: 16ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
20 8s833ms 1 8s833ms 8s833ms 8s833ms select cleanupt240 (?, ?); refresh materialized view concurrently mat_oldest_t240_candle_per_symbolid;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Jun 27 08 1 8s833ms 8s833ms [ User: postgres - Total duration: 8s833ms - Times executed: 1 ]
[ Application: psql - Total duration: 8s833ms - Times executed: 1 ]
-
select cleanupt240 (240, 10); refresh materialized view concurrently mat_oldest_t240_candle_per_symbolid;
Date: 2025-06-27 08:30:09 Duration: 8s833ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 49,843 221ms 0ms 6ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jun 27 08 49,843 221ms 0ms [ User: postgres - Total duration: 221ms - Times executed: 49843 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 207ms - Times executed: 49453 ]
[ Application: [unknown] - Total duration: 13ms - Times executed: 390 ]
-
select 1;
Date: 2025-06-27 08:38:13 Duration: 6ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-06-27 08:30:07 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-06-27 08:15:06 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
2 31,184 46s278ms 0ms 34ms 1ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Jun 27 08 31,184 46s278ms 1ms [ User: postgres - Total duration: 46s278ms - Times executed: 31184 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 46s278ms - Times executed: 31184 ]
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243225790300';
Date: 2025-06-27 08:00:06 Duration: 34ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840249432335300';
Date: 2025-06-27 08:00:05 Duration: 30ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243171165300';
Date: 2025-06-27 08:00:05 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
3 21,783 1m21s 0ms 46ms 3ms select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jun 27 08 21,783 1m21s 3ms [ User: postgres - Total duration: 1m21s - Times executed: 21783 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m21s - Times executed: 21783 ]
-
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 = 'UK100' OR dss.downloadersymbol = 'UK100') AND dss.enabled = 1;
Date: 2025-06-27 08:00:06 Duration: 46ms 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 = 'HK50' OR dss.downloadersymbol = 'HK50') AND dss.enabled = 1;
Date: 2025-06-27 08:15:05 Duration: 30ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'JPM.US' OR dss.downloadersymbol = 'JPM.US') AND dss.enabled = 1;
Date: 2025-06-27 08:00:05 Duration: 30ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
4 6,812 7s846ms 0ms 7ms 1ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Jun 27 08 6,812 7s846ms 1ms [ User: postgres - Total duration: 7s846ms - Times executed: 6812 ]
[ Application: [unknown] - Total duration: 7s846ms - Times executed: 6812 ]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 107, schedule: 1 * * * * Africa/Johannesburg', NULL, NULL);
Date: 2025-06-27 08:30:51 Duration: 7ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 53, schedule: 0 8 * * 1 Africa/Johannesburg', NULL, NULL);
Date: 2025-06-27 08:20:49 Duration: 7ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 100, schedule: 0 * * * * Africa/Johannesburg', NULL, NULL);
Date: 2025-06-27 08:30:51 Duration: 6ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
5 6,673 9s584ms 0ms 17ms 1ms insert into autochartist_results (resultid, symbolid, bandwidth, pattern, qtytp, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, relevancestartdistance, simulation, writtendatetime) values (?, ?, ?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Jun 27 08 6,673 9s584ms 1ms [ User: postgres - Total duration: 9s584ms - Times executed: 6673 ]
[ Application: [unknown] - Total duration: 9s584ms - Times executed: 6673 ]
-
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 ('5158402432248563000.386|45834.7083|45835.2083|45834.875|45835.25|18.9384|18.8747|18.8481|18.8574', 515840243224856300, 2.000000000000000000000000000000, 'Triangle', 4, '2025-06-27 05:57:41'::timestamp without time zone, 1, 0.393296664455829447800000000000, 0.385971548046518675400000000000, 0.486064713618637844800000000000, 0.085358497015437531650000000000, 0.848920500729870353200000000000, 18.897178088754397860000000000000, 18.937383413010554280000000000000, '2025-06-27 07:00:00'::timestamp without time zone, '2025-06-27 14:00:00'::timestamp without time zone, '2025-06-26 15:00:00'::timestamp without time zone, '2025-06-27 07:00:00'::timestamp without time zone, 18.845109999999998250000000000000, 18.864086666666668890000000000000, '2025-06-26 17:00:00'::timestamp without time zone, '2025-06-27 05:00:00'::timestamp without time zone, '2025-06-26 21:00:00'::timestamp without time zone, '2025-06-27 06:00:00'::timestamp without time zone, 18.938449999999999560000000000000, 18.874710000000000320000000000000, 18.848099999999998740000000000000, 18.857379999999999140000000000000, 0.001031111111111155353000000000, - 0.005311666666666603476000000000, 2.745047313302698466000000000000, 0.635707554054195211900000000000, 'Continuation', 0.003663333333332019492000000000, '2025-06-27 07:00:00'::timestamp without time zone, 18.868459999999998900000000000000, 14, 0, 0.022381666666667261040000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-27 08:02:12 Duration: 17ms 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 ('515840245887141300-1|45831.8125|45835.3542|45832.7083|45834.7708|403.77|399.357|400.12|398.434', 515840245887141300, 4.000000000000000000000000000000, 'Falling Wedge', 5, '2025-06-27 06:26:25'::timestamp without time zone, - 1, 0.552864915407084711600000000000, - 1.000000000000000000000000000000, 0.000000000000000000000000000000, 0.119685332738642527500000000000, 0.795370202024570316400000000000, 395.597317314348231300000000000000, 397.495298880978452900000000000000, '2025-06-27 09:00:00'::timestamp without time zone, '2025-06-29 03:45:00'::timestamp without time zone, '2025-06-20 14:30:00'::timestamp without time zone, '2025-06-27 09:00:00'::timestamp without time zone, 401.677000000000020900000000000000, 398.833000000000026800000000000000, '2025-06-23 19:30:00'::timestamp without time zone, '2025-06-27 08:30:00'::timestamp without time zone, '2025-06-24 17:00:00'::timestamp without time zone, '2025-06-26 18:30:00'::timestamp without time zone, 403.769999999999981800000000000000, 399.357000000000027800000000000000, 400.120000000000004600000000000000, 398.434000000000025900000000000000, - 0.017030303030302815920000000000, - 0.025958823529411496200000000000, 3.888779781863425988000000000000, 0.742849928231004153000000000000, 'Reversal', 0.000000000000000000000000000000, '2025-06-27 09:00:00'::timestamp without time zone, 398.850999999999999100000000000000, 171, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-27 08:30:56 Duration: 17ms 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 ('515840249482774300-1|45834.5208|45834.9792|45834.7083|45835.0625|1.3771|1.3749|1.3704|1.3719', 515840249482774300, 2.000000000000000000000000000000, 'Triangle', 4, '2025-06-27 06:26:00'::timestamp without time zone, 1, 0.418530949964878606900000000000, - 1.000000000000000000000000000000, 0.187511573909203560500000000000, 0.118365519101517532900000000000, 0.625712562895413770800000000000, 1.375344514776416060000000000000, 1.378332835463398354000000000000, '2025-06-27 02:00:00'::timestamp without time zone, '2025-06-27 08:45:00'::timestamp without time zone, '2025-06-26 07:30:00'::timestamp without time zone, '2025-06-27 02:00:00'::timestamp without time zone, 1.369799999999999907000000000000, 1.373480000000000034000000000000, '2025-06-26 12:30:00'::timestamp without time zone, '2025-06-26 23:30:00'::timestamp without time zone, '2025-06-26 17:00:00'::timestamp without time zone, '2025-06-27 01:30:00'::timestamp without time zone, 1.377099999999999991000000000000, 1.374900000000000011000000000000, 1.370449999999999946000000000000, 1.371899999999999897000000000000, 0.000085294117647055956480000000, - 0.000099999999999999083220000000, 2.792978807405853470000000000000, 0.641959331252924925200000000000, 'Continuation', 0.000000000000000000000000000000, '2025-06-27 02:00:00'::timestamp without time zone, 1.373210000000000042000000000000, 27, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-27 08:30:30 Duration: 16ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
6 6,175 6s440ms 0ms 13ms 1ms insert into t15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Jun 27 08 6,175 6s440ms 1ms [ User: postgres - Total duration: 6s440ms - Times executed: 6175 ]
[ Application: [unknown] - Total duration: 6s440ms - Times executed: 6175 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-27 09:15:00', '3294.28', '3297.085', '3293.025', '3294.605', '2070', '605679104921734300', '0', '2025-06-27 08:30:53.269', '2025-06-27 08:30:53.097') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '3294.28', high = '3297.085', low = '3293.025', close = '3294.605', volume = '2070', bsf = '0', sastdatetimewritten = '2025-06-27 08:30:53.269', sastdatetimereceived = '2025-06-27 08:30:53.097';
Date: 2025-06-27 08:30:53 Duration: 13ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-27 09:00:00', '144.425', '144.505', '144.3765', '144.4345', '1065', '515840230603785300', '0', '2025-06-27 08:15:54.597', '2025-06-27 08:15:54.446') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '144.425', high = '144.505', low = '144.3765', close = '144.4345', volume = '1065', bsf = '0', sastdatetimewritten = '2025-06-27 08:15:54.597', sastdatetimereceived = '2025-06-27 08:15:54.446';
Date: 2025-06-27 08:15:54 Duration: 12ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-27 09:30:00', '40122', '40204', '40122', '40167', '1086', '515840249388737300', '0', '2025-06-27 08:45:06.18', '2025-06-27 08:45:06.132') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '40122', high = '40204', low = '40122', close = '40167', volume = '1086', bsf = '0', sastdatetimewritten = '2025-06-27 08:45:06.18', sastdatetimereceived = '2025-06-27 08:45:06.132';
Date: 2025-06-27 08:45:06 Duration: 12ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
7 5,873 3s878ms 0ms 25ms 0ms with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ) select a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, s.exchange, s.symbol, s.longname, s.shortname, breakout, dtt.timezone, patternstartprice, patternendprice, qtytp, newlevels.profit, newlevels.stop, newlevels.filtered, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern inner join rar_max rm on ? = ? left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid left join lateral calc_cp_signal (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Jun 27 08 5,873 3s878ms 0ms [ User: postgres - Total duration: 3s878ms - Times executed: 5873 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s808ms - Times executed: 5847 ]
[ Application: [unknown] - Total duration: 69ms - Times executed: 26 ]
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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 = '606362360335087301' 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 = '606362360335087301' OR a.resultuid = '606362360335087301') AND dtt.dayofweek = 3;
Date: 2025-06-27 08:00:03 Duration: 25ms 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 = '606362360335087301' 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 = '606362360335087301' OR a.resultuid = '606362360335087301') AND dtt.dayofweek = 3;
Date: 2025-06-27 08:59:55 Duration: 24ms 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 = '606362120657368301' 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 = '606362120657368301' OR a.resultuid = '606362120657368301') AND dtt.dayofweek = 3;
Date: 2025-06-27 08:00:03 Duration: 18ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
8 3,517 1s966ms 0ms 21ms 0ms insert into t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Jun 27 08 3,517 1s966ms 0ms [ User: postgres - Total duration: 1s966ms - Times executed: 3517 ]
[ Application: [unknown] - Total duration: 1s966ms - Times executed: 3517 ]
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-27 09:00:00', '0.89247', '0.89304', '0.89219', '0.89266', '3316', '515840233451602300', '0', '2025-06-27 08:30:54.998', '2025-06-27 08:30:54.997') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.89247', high = '0.89304', low = '0.89219', close = '0.89266', volume = '3316', bsf = '0', sastdatetimewritten = '2025-06-27 08:30:54.998', sastdatetimereceived = '2025-06-27 08:30:54.997';
Date: 2025-06-27 08:30:55 Duration: 21ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-27 09:00:00', '22492', '22517.5', '22491.5', '22514.6', '2028', '515840248039147300', '0', '2025-06-27 08:40:51.53', '2025-06-27 08:40:51.492') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '22492', high = '22517.5', low = '22491.5', close = '22514.6', volume = '2028', bsf = '0', sastdatetimewritten = '2025-06-27 08:40:51.53', sastdatetimereceived = '2025-06-27 08:40:51.492';
Date: 2025-06-27 08:40:51 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-27 09:00:00', '34.25', '34.45', '34.22', '34.26', '1044', '515840247893477300', '0', '2025-06-27 08:30:58.961', '2025-06-27 08:30:58.742') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '34.25', high = '34.45', low = '34.22', close = '34.26', volume = '1044', bsf = '0', sastdatetimewritten = '2025-06-27 08:30:58.961', sastdatetimereceived = '2025-06-27 08:30:58.742';
Date: 2025-06-27 08:30:58 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
9 3,345 1s408ms 0ms 21ms 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ) select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as ruid, s.symbolid as sid, s.symbol as sym, longname, shortname, exchange as e, timegranularity as tg, a.patternid as pid, a.direction as d, a.patternprice as pp, atbaridentified as pet, case when (x9 != ?) then x9 when (x8 != ?) then x8 when (x7 != ?) then x7 when (x6 != ?) then x6 when (x5 != ?) then x5 when (x4 != ?) then x4 when (x3 != ?) then x3 when (x2 != ?) then x2 end as pst, patternprice as patp, x0, x1, x2, case when (x3 != ?) then x3 else ? end as x3, case when (x4 != ?) then x4 else ? end as x4, case when (x5 != ?) then x5 else ? end as x5, case when (x6 != ?) then x6 else ? end as x6, case when (x7 != ?) then x7 else ? end as x7, case when (x8 != ?) then x8 else ? end as x8, errormargin as erm, breakoutprice as pe, breakoutbars as be, breakout, atbaridentified as atbar, atpriceidentified as atprice, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzos, dtt.timezone as timezone, approachingtimestamp as apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, furthestprice as fp, newlevels.filtered, a.uniquepointsvalue as upv, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from keylevels_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join hrspatterns p on a.patternid = p.patternid inner join rar_max rm on ? = ? left outer join relevance_keylevels_results rar on a.resultuid = rar.resultuid left join lateral calc_kl_signal_filter (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jun 27 08 3,345 1s408ms 0ms [ User: postgres - Total duration: 1s408ms - Times executed: 3345 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s408ms - Times executed: 3345 ]
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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 = '606362120017765303' 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 = '606362120017765303' OR a.resultuid = '606362120017765303') AND dtt.dayofweek = 3;
Date: 2025-06-27 08:59:55 Duration: 21ms 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 = '606361649074377303' 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 = '606361649074377303' OR a.resultuid = '606361649074377303') AND dtt.dayofweek = 3;
Date: 2025-06-27 08:59:55 Duration: 16ms 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 = '606361411503876303' 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 = '606361411503876303' OR a.resultuid = '606361411503876303') AND dtt.dayofweek = 3;
Date: 2025-06-27 08:59:55 Duration: 13ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
10 3,054 6s437ms 0ms 12ms 2ms 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 #10
Day Hour Count Duration Avg duration Jun 27 08 3,054 6s437ms 2ms [ User: postgres - Total duration: 6s437ms - Times executed: 3054 ]
[ Application: [unknown] - Total duration: 6s437ms - Times executed: 3054 ]
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INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (9.000000000000000000000000000000, - 1, 2, '2025-06-27 06:26:09'::timestamp without time zone, '2025-06-27 09:15:00', 0.513000000000000899700000000000, 3, 371, 197.701999999999998200000000000000, '2025-06-26 11:30:00', '2025-06-25 10:45:00', '2025-06-23 12:30:00', '', '', '', '', '', '', '', 568, 197.620100000000007900000000000000, '2025-06-27 09:15:00'::timestamp without time zone, '2025-06-27 09:15:00', 198.199999999999988600000000000000, 0.081900000000000305890000000000, - 1, 500991628222653200, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|500991628222653200|197.702|2|2025-06-27 09:15:00|2025-06-27 09:15:00|-1|-1', 198.409940000000006000000000000000, 0.707940000000007785200000000000, 2, '2025-06-23 12:30:00', 198.519000000000005500000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-27 08:30:40 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (7.000000000000000000000000000000, - 1, 1, '2025-06-27 06:26:19'::timestamp without time zone, '', 0.500000000000000000000000000000, 6, 316, 10.102830000000000865000000000000, '2025-06-27 08:00:00', '2025-06-27 04:00:00', '2025-06-26 15:00:00', '2025-06-24 13:45:00', '2025-06-24 01:45:00', '2025-06-24 01:00:00', '', '', '', '', 1106, 10.110677000000000803000000000000, '2025-06-27 09:15:00'::timestamp without time zone, '2025-06-27 09:15:00', 0.000000000000000000000000000000, 0.007868000000000031219000000000, - 1, 500991628252276200, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|500991628252276200|10.10283|1|2025-06-27 09:15:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-06-24 01:00:00', 10.183669999999999334000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-27 08:30:49 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (7.000000000000000000000000000000, - 1, 1, '2025-06-27 06:26:04'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 171, 0.176449999999999995700000000000, '2025-06-26 23:30:00', '2025-06-23 17:00:00', '2025-06-23 10:00:00', '', '', '', '', '', '', '', 342, 0.177345000000000002600000000000, '2025-06-27 09:00:00'::timestamp without time zone, '2025-06-27 09:00:00', 0.000000000000000000000000000000, 0.000894999999999999962200000000, - 1, 515840249474910300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249474910300|0.17645|1|2025-06-27 09:00:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-06-23 10:00:00', 0.185349999999999987000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-27 08:30:34 Duration: 11ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
11 2,313 1s473ms 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 #11
Day Hour Count Duration Avg duration Jun 27 08 2,313 1s473ms 0ms [ User: postgres - Total duration: 1s473ms - Times executed: 2313 ]
[ Application: [unknown] - Total duration: 1s473ms - Times executed: 2313 ]
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-27 08:00:00', '105.882', '105.932', '105.789', '105.834', '5538', '515840247880591300', '0', '2025-06-27 08:00:43.42', '2025-06-27 08:00:43.297') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '105.882', high = '105.932', low = '105.789', close = '105.834', volume = '5538', bsf = '0', sastdatetimewritten = '2025-06-27 08:00:43.42', sastdatetimereceived = '2025-06-27 08:00:43.297';
Date: 2025-06-27 08:00:43 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-27 08:00:00', '0.4668', '0.4708', '0.4645', '0.4655', '99', '515840247923246300', '0', '2025-06-27 08:01:44.284', '2025-06-27 08:01:44.222') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.4668', high = '0.4708', low = '0.4645', close = '0.4655', volume = '99', bsf = '0', sastdatetimewritten = '2025-06-27 08:01:44.284', sastdatetimereceived = '2025-06-27 08:01:44.222';
Date: 2025-06-27 08:01:44 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-27 08:00:00', '11.13954', '11.14204', '11.13024', '11.13034', '6268', '515840247888021300', '0', '2025-06-27 08:00:51.641', '2025-06-27 08:00:51.329') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '11.13954', high = '11.14204', low = '11.13024', close = '11.13034', volume = '6268', bsf = '0', sastdatetimewritten = '2025-06-27 08:00:51.641', sastdatetimereceived = '2025-06-27 08:00:51.329';
Date: 2025-06-27 08:00:51 Duration: 6ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
12 1,983 1s886ms 0ms 9ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jun 27 08 1,983 1s886ms 0ms [ User: postgres - Total duration: 1s886ms - Times executed: 1983 ]
[ Application: [unknown] - Total duration: 1s886ms - Times executed: 1983 ]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-06-27 09:00:00', reason = 'Price has entered the prediction area for a completed pattern' WHERE uniqueIndex = '5009916282671442000.0763|45835.0417|45835.25|45835.1875|45835.3333|43516.45|43508.65|43450.65|43476.' and relevant = 1;
Date: 2025-06-27 08:30:54 Duration: 9ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-06-27 09:00:00', reason = 'Emerging pattern formed a completed pattern.' WHERE uniqueIndex = '500991628254848200-1|45835.1667|45835.3333|45835.0208|45835.2708|9.5618|9.5351|9.4628|9.5052' and relevant = 1;
Date: 2025-06-27 08:30:54 Duration: 9ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-06-27 05:45:00', reason = 'Price has moved too far in the wrong direction' WHERE uniqueIndex = '|515840249721914300|0.93723|1|2025-06-27 05:30:00|2025-06-27 05:30:00|1|-1' and relevant = 1;
Date: 2025-06-27 08:01:17 Duration: 9ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
13 1,952 1s626ms 0ms 10ms 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 Jun 27 08 1,952 1s626ms 0ms [ User: postgres - Total duration: 1s626ms - Times executed: 1952 ]
[ Application: [unknown] - Total duration: 1s626ms - Times executed: 1952 ]
-
INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, 'ABCD', '2025-06-27 06:26:01'::timestamp without time zone, - 1, '2025-06-26 12:30:00'::timestamp without time zone, '2025-06-27 02:00:00'::timestamp without time zone, 1.598899999999999988000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 1.593299999999999938000000000000, '2025-06-26 18:30:00'::timestamp without time zone, 1.596470000000000056000000000000, '2025-06-26 23:00:00'::timestamp without time zone, 1.593900000000000094000000000000, '2025-06-27 02:00:00'::timestamp without time zone, 1.597070000000000212000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.740613026819921471700000000000, - 1.000000000000000000000000000000, 5.598920397352395994000000000000, 24, 1.593900000000000094000000000000, 1.595110832255821176000000000000, 1.591940832255821059000000000000, 1.594577900132374104000000000000, 1.593037697711085166000000000000, 1.595485000000000042000000000000, 1.595859167744179130000000000000, 515840249481758300, 0.518773946360157056600000000000, 'BC=0.786*AB (0.811) ', 0, 'ABCD|-1|2025-06-26 12:30:00|1.5989|-1|4|24|BC=0.786*AB (0.811)|0|515840249481758300|1899-12-29 00:00:00|2025-06-26 18:30:00|2025-06-26 23:00:00|2025-06-27 02:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-27 08:30:32 Duration: 10ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, '3 Point Extension', '2025-06-27 05:56:58'::timestamp without time zone, - 1, '2025-06-27 04:30:00'::timestamp without time zone, '2025-06-27 08:45:00'::timestamp without time zone, 1.928639999999999910000000000000, 1.927340000000000053000000000000, 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, 1.928639999999999910000000000000, '2025-06-27 04:30:00'::timestamp without time zone, 1.926060000000000105000000000000, '2025-06-27 05:30:00'::timestamp without time zone, 1.929359999999999964000000000000, '2025-06-27 08:45:00'::timestamp without time zone, 0.339461716063826746100000000000, - 1.000000000000000000000000000000, 0.110849198668805312700000000000, 17, 1.926060000000000105000000000000, 1.927320487837290042000000000000, 1.924020487837290183000000000000, 1.926765700453260122000000000000, 1.925162335156650251000000000000, 1.927710000000000035000000000000, 1.928099512162710028000000000000, 515840243886409300, 0.431925766541151778800000000000, 'CD=1.272*BC (1.279) ', 0, '3 Point Extension|-1|2025-06-27 04:30:00|1.92864|1.92734|3|17|CD=1.272*BC (1.279)|0|515840243886409300|1899-12-29 00:00:00|1899-12-29 00:00:00|2025-06-27 04:30:00|2025-06-27 05:30:00|2025-06-27 08:45:00', 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-27 08:01:28 Duration: 9ms 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', '2025-06-27 05:56:58'::timestamp without time zone, - 1, '2025-06-27 04:30:00'::timestamp without time zone, '2025-06-27 08:45:00'::timestamp without time zone, 1.928639999999999910000000000000, 1.927340000000000053000000000000, 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, 1.928639999999999910000000000000, '2025-06-27 04:30:00'::timestamp without time zone, 1.926060000000000105000000000000, '2025-06-27 05:30:00'::timestamp without time zone, 1.929359999999999964000000000000, '2025-06-27 08:45:00'::timestamp without time zone, 0.339461716063826746100000000000, - 1.000000000000000000000000000000, 0.110849198668805312700000000000, 17, 1.926060000000000105000000000000, 1.927320487837290042000000000000, 1.924020487837290183000000000000, 1.926765700453260122000000000000, 1.925162335156650251000000000000, 1.927710000000000035000000000000, 1.928099512162710028000000000000, 515840243886409300, 0.431925766541151778800000000000, 'CD=1.272*BC (1.279) ', 0, '3 Point Extension|-1|2025-06-27 04:30:00|1.92864|1.92734|3|17|CD=1.272*BC (1.279)|0|515840243886409300|1899-12-29 00:00:00|1899-12-29 00:00:00|2025-06-27 04:30:00|2025-06-27 05:30:00|2025-06-27 08:45:00', 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-27 08:01:28 Duration: 9ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
14 1,159 458ms 0ms 7ms 0ms with rar_max as ( select resultuid from relevance_fibonacci_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, exchange as e, longname as lo, shortname as sho, timegranularity as tg, p.patternid as pid, direction as d, patternstarttime as pst, patternendtime as pet, patternstartprice as psp, patternendprice as pep, pricex as px, timex as tx, pricea as pa, timea as ta, priceb as pb, timeb as tb, pricec as pc, timec as tc, priced as pd, timed as td, averagequality as aq, timequality as tq, ? - errormargin as rq, ? - noise as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, patternlengthbars as l, temporarypattern as tp, bandwidth as bw, qtytp as qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzos, dtt.timezone as tz, 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, newlevels.filtered from fibonacci_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 fibonaccipatterns p on a.pattern = p.patternname inner join rar_max rm on ? = ? left outer join relevance_fibonacci_results rar on a.resultuid = rar.resultuid left join currencypips cps on cps.symbol = s.symbol left join lateral calc_fib_signal_filter (a.resultuid) newlevels on true where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Jun 27 08 1,159 458ms 0ms [ User: postgres - Total duration: 458ms - Times executed: 1159 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 458ms - Times executed: 1159 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '606362359489802302' THEN a.old_resultuid ELSE a.resultuid END AS ruid, s.symbolid AS sid, s.symbol AS sym, Exchange AS e, longname AS lo, shortname AS sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX AS px, timeX AS tx, priceA AS pa, timeA AS ta, priceB AS pb, timeB AS tb, priceC AS pc, timeC AS tc, priceD AS pd, timeD AS td, averagequality AS aq, timequality AS tq, 1 - errormargin AS rq, 1 - noise AS c, target10 AS t10, target06 AS t06, target16 AS t16, target07 AS t07, target12 AS t12, target03 AS t03, target05 AS t05, PatternLengthBars AS l, temporarypattern AS tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname AS patternname, dtt.absolutetimezoneoffset AS tzOs, dtt.timezone AS tz, 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, newLevels.filtered FROM Fibonacci_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 fibonaccipatterns p ON a.pattern = p.patternname INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_fibonacci_results rar ON a.resultuid = rar.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT JOIN LATERAL calc_fib_signal_filter (a.resultuid) newLevels on true WHERE (a.old_resultuid = '606362359489802302' OR a.resultuid = '606362359489802302') AND dtt.dayofweek = 3;
Date: 2025-06-27 08:00:03 Duration: 7ms 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_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '606362001463486302' THEN a.old_resultuid ELSE a.resultuid END AS ruid, s.symbolid AS sid, s.symbol AS sym, Exchange AS e, longname AS lo, shortname AS sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX AS px, timeX AS tx, priceA AS pa, timeA AS ta, priceB AS pb, timeB AS tb, priceC AS pc, timeC AS tc, priceD AS pd, timeD AS td, averagequality AS aq, timequality AS tq, 1 - errormargin AS rq, 1 - noise AS c, target10 AS t10, target06 AS t06, target16 AS t16, target07 AS t07, target12 AS t12, target03 AS t03, target05 AS t05, PatternLengthBars AS l, temporarypattern AS tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname AS patternname, dtt.absolutetimezoneoffset AS tzOs, dtt.timezone AS tz, 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, newLevels.filtered FROM Fibonacci_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 fibonaccipatterns p ON a.pattern = p.patternname INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_fibonacci_results rar ON a.resultuid = rar.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT JOIN LATERAL calc_fib_signal_filter (a.resultuid) newLevels on true WHERE (a.old_resultuid = '606362001463486302' OR a.resultuid = '606362001463486302') AND dtt.dayofweek = 3;
Date: 2025-06-27 08:16:50 Duration: 6ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '606362594793372302' THEN a.old_resultuid ELSE a.resultuid END AS ruid, s.symbolid AS sid, s.symbol AS sym, Exchange AS e, longname AS lo, shortname AS sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX AS px, timeX AS tx, priceA AS pa, timeA AS ta, priceB AS pb, timeB AS tb, priceC AS pc, timeC AS tc, priceD AS pd, timeD AS td, averagequality AS aq, timequality AS tq, 1 - errormargin AS rq, 1 - noise AS c, target10 AS t10, target06 AS t06, target16 AS t16, target07 AS t07, target12 AS t12, target03 AS t03, target05 AS t05, PatternLengthBars AS l, temporarypattern AS tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname AS patternname, dtt.absolutetimezoneoffset AS tzOs, dtt.timezone AS tz, 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, newLevels.filtered FROM Fibonacci_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 fibonaccipatterns p ON a.pattern = p.patternname INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_fibonacci_results rar ON a.resultuid = rar.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT JOIN LATERAL calc_fib_signal_filter (a.resultuid) newLevels on true WHERE (a.old_resultuid = '606362594793372302' OR a.resultuid = '606362594793372302') AND dtt.dayofweek = 3;
Date: 2025-06-27 08:54:53 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
15 1,145 10ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Jun 27 08 1,145 10ms 0ms [ User: postgres - Total duration: 10ms - Times executed: 1145 ]
[ Application: [unknown] - Total duration: 10ms - Times executed: 1145 ]
-
SET extra_float_digits = 3;
Date: 2025-06-27 08:05:42 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2025-06-27 08:51:21 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2025-06-27 08:47:28 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: [unknown] Bind query: yes
16 1,092 301ms 0ms 3ms 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars as length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternstartprice, resy1, supporty1, dtt.timezone, cps.pip, newlevels.profit from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern left join currencypips cps on cps.symbol = s.symbol left join lateral calc_cp_signal (a.resultuid) newlevels on true where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Jun 27 08 1,092 301ms 0ms [ User: postgres - Total duration: 301ms - Times executed: 1092 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 301ms - Times executed: 1092 ]
-
SELECT CASE WHEN a.old_resultuid = '606361650868180301' 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 = '606361650868180301' OR a.resultuid = '606361650868180301') AND dtt.dayofweek = 3;
Date: 2025-06-27 08:11:00 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '606362711670639301' 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 = '606362711670639301' OR a.resultuid = '606362711670639301') AND dtt.dayofweek = 3;
Date: 2025-06-27 08:36:00 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '606362529265212301' 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 = '606362529265212301' OR a.resultuid = '606362529265212301') AND dtt.dayofweek = 3;
Date: 2025-06-27 08:24:25 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
17 1,091 14ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Jun 27 08 1,091 14ms 0ms [ User: postgres - Total duration: 14ms - Times executed: 1091 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14ms - Times executed: 1091 ]
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-27 08:52:32 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-27 08:25:32 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-27 08:00:03 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
18 811 7ms 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 #18
Day Hour Count Duration Avg duration Jun 27 08 811 7ms 0ms [ User: postgres - Total duration: 7ms - Times executed: 811 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 7ms - Times executed: 811 ]
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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: 2025-06-27 08:13:48 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.246 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: 2025-06-27 08:13:17 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.246 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: 2025-06-27 08:13:17 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.246 Application: PostgreSQL JDBC Driver Bind query: yes
19 733 1s223ms 0ms 6ms 1ms select s.symbolid, dss.downloadfrequency, dss.downloadersymbol from downloadersymbolsettings dss inner join symbols s on dss.symbolid = s.symbolid where dss.classname = ? and s.deleted = ? and dss.enabled = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Jun 27 08 733 1s223ms 1ms [ User: postgres - Total duration: 1s223ms - Times executed: 733 ]
[ Application: [unknown] - Total duration: 1s223ms - Times executed: 733 ]
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'Alpari' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-27 08:30:24 Duration: 6ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'GLOBALGTMT5' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-27 08:00:05 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'PEPPERSTONE' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-27 08:30:13 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
20 733 127ms 0ms 0ms 0ms select downloadersymbol, spike_threshold from price_datafeed_spike_threshold where classname = ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Jun 27 08 733 127ms 0ms [ User: postgres - Total duration: 127ms - Times executed: 733 ]
[ Application: [unknown] - Total duration: 127ms - Times executed: 733 ]
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SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'AXIORY';
Date: 2025-06-27 08:30:41 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'PEPPERSTONE';
Date: 2025-06-27 08:45:51 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'PEPPERSTONE';
Date: 2025-06-27 08:30:40 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 18s831ms 18s831ms 18s831ms 1 18s831ms select cleanupt15 (?, ?, ?); refresh materialized view concurrently mat_oldest_t15_candle_per_symbolid;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jun 27 08 1 18s831ms 18s831ms [ User: postgres - Total duration: 18s831ms - Times executed: 1 ]
[ Application: psql - Total duration: 18s831ms - Times executed: 1 ]
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select cleanupt15 (15, 5, 20); refresh materialized view concurrently mat_oldest_t15_candle_per_symbolid;
Date: 2025-06-27 08:20:20 Duration: 18s831ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
2 8s962ms 10s250ms 9s718ms 4 38s875ms select updateageforrelevantresults ();Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Jun 27 08 4 38s875ms 9s718ms [ User: postgres - Total duration: 38s875ms - Times executed: 4 ]
[ Application: psql - Total duration: 38s875ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-06-27 08:32:12 Duration: 10s250ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-06-27 08:02:12 Duration: 9s954ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-06-27 08:17:12 Duration: 9s707ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
3 8s833ms 8s833ms 8s833ms 1 8s833ms select cleanupt240 (?, ?); refresh materialized view concurrently mat_oldest_t240_candle_per_symbolid;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jun 27 08 1 8s833ms 8s833ms [ User: postgres - Total duration: 8s833ms - Times executed: 1 ]
[ Application: psql - Total duration: 8s833ms - Times executed: 1 ]
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select cleanupt240 (240, 10); refresh materialized view concurrently mat_oldest_t240_candle_per_symbolid;
Date: 2025-06-27 08:30:09 Duration: 8s833ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
4 375ms 22s752ms 7s858ms 444 58m9s 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 #4
Day Hour Count Duration Avg duration Jun 27 08 444 58m9s 7s858ms [ User: postgres - Total duration: 58m9s - Times executed: 444 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 58m9s - Times executed: 444 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-27 08:34:30 Duration: 22s752ms 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 ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-27 08:30:48 Duration: 21s334ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '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: 2025-06-27 08:16:05 Duration: 20s943ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
5 204ms 36s660ms 7s370ms 445 54m39s 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 #5
Day Hour Count Duration Avg duration Jun 27 08 445 54m39s 7s370ms [ User: postgres - Total duration: 54m39s - Times executed: 445 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 54m39s - Times executed: 445 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-06-27 08:10:20 Duration: 36s660ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-06-27 08:15:26 Duration: 34s78ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-06-27 08:15:32 Duration: 34s26ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
6 5s42ms 8s91ms 6s658ms 6 39s951ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Jun 27 08 6 39s951ms 6s658ms [ User: postgres - Total duration: 39s951ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 39s951ms - Times executed: 6 ]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-27 08:30:11 Duration: 8s91ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-27 08:00:10 Duration: 7s845ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-27 08:10:10 Duration: 7s319ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
7 598ms 7s945ms 2s641ms 406 17m52s 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 #7
Day Hour Count Duration Avg duration Jun 27 08 406 17m52s 2s641ms [ User: postgres - Total duration: 17m52s - Times executed: 406 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 17m52s - Times executed: 406 ]
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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 ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-27 08:30:41 Duration: 7s945ms 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 = '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 ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-27 08:30:55 Duration: 6s379ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('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 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 ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-27 08:25:58 Duration: 6s260ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
8 1s63ms 5s442ms 2s455ms 6 14s730ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Jun 27 08 6 14s730ms 2s455ms [ User: postgres - Total duration: 14s730ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 14s730ms - Times executed: 6 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-27 08:31:21 Duration: 5s442ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-27 08:46:20 Duration: 4s345ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-27 08:01:18 Duration: 1s688ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
9 1s511ms 4s248ms 1s972ms 8 15s781ms select updateresultsmaterializedview ();Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jun 27 08 8 15s781ms 1s972ms [ User: postgres - Total duration: 15s781ms - Times executed: 8 ]
[ Application: psql - Total duration: 15s781ms - Times executed: 8 ]
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select updateresultsmaterializedview ();
Date: 2025-06-27 08:32:16 Duration: 4s248ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-06-27 08:02:13 Duration: 1s787ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-06-27 08:47:13 Duration: 1s770ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
10 1s798ms 2s541ms 1s961ms 16 31s389ms with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Jun 27 08 16 31s389ms 1s961ms [ User: postgres - Total duration: 31s389ms - Times executed: 16 ]
[ Application: psql - Total duration: 31s389ms - Times executed: 16 ]
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:20:15 Duration: 2s541ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:01:15 Duration: 2s489ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:41:14 Duration: 2s25ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 1s335ms 2s135ms 1s590ms 16 25s442ms with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = ? left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bg.brokerid and bim.type = ? where bg.brokerid = ? and basegroupname = ? and g.designation = ? and s.nonliquid = ? ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= ? and patternquality >= ?.? and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, case when direction > ? then ? else ? end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (...) and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= ? and _tmp.qtycandlesapart <= ? and ((cpresultuid > ( select coalesce(max(cpresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?)) or (klresultuid > ( select coalesce(max(klresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = ? and cs.basegroupname = ? and date_trunc(?, cs.gmttimefound) = date_trunc(?, now()) and sent is true and filtered is false ) <= ( select case when coalesce(daily_max, ?) < ? then ? else coalesce(daily_max,?) end from corr_sigs_config_v where broker_id = ? limit ? ) and extract(epoch from age(current_timestamp at time zone ?, max_patternendtime - absolutetimezoneoffset * interval ?))/? < mint*? ), maxstats as ( select max(statsid) as maxid , st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = ? then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * ? as numeric), ?) as percent, round(cast((kl_correct) / (kl_total) * ? as numeric), ?) as klpercent, round(cast((cp_correct ) / (cp_total ) * ? as numeric), ?) as cppercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), ?) as openprice, round(cast(sig.forecastprice as numeric), ?) as forecastprice, cast(round(cast(abs(sig.forecastprice - sig.openprice)/pip as numeric), ?)as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname , si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = ? then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = ? and date_part(?, sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = ? and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = ? and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = ? and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = ? and date_part(?, sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = ? and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = ? and kl_sym.name ilike si.symbol ) as tmp order by tmp.gmttimefound desc;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jun 27 08 16 25s442ms 1s590ms [ User: postgres - Total duration: 25s442ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 25s442ms - Times executed: 16 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '627' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '627' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '627' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-06-27 08:07:05 Duration: 2s135ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '627' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '627' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '627' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-06-27 08:21:56 Duration: 1s932ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '627' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '627' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '627' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-06-27 08:37:01 Duration: 1s794ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
12 660ms 1s213ms 918ms 16 14s700ms update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jun 27 08 16 14s700ms 918ms [ User: postgres - Total duration: 14s700ms - Times executed: 16 ]
[ Application: psql - Total duration: 14s700ms - Times executed: 16 ]
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:31:12 Duration: 1s213ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:33:12 Duration: 1s178ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-27 08:03:12 Duration: 1s137ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
13 12ms 11s8ms 887ms 34 30s166ms select fixcandlegaps (?, false);Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jun 27 08 34 30s166ms 887ms [ User: postgres - Total duration: 30s166ms - Times executed: 34 ]
[ Application: psql - Total duration: 30s166ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-06-27 08:06:32 Duration: 11s8ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-06-27 08:06:09 Duration: 3s802ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('AXIORY', false);
Date: 2025-06-27 08:06:12 Duration: 2s846ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
14 102ms 1s901ms 534ms 267 2m22s 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 #14
Day Hour Count Duration Avg duration Jun 27 08 267 2m22s 534ms [ User: postgres - Total duration: 2m22s - Times executed: 267 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m22s - Times executed: 267 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-27 08:27:48 Duration: 1s901ms 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 ('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 ccr.patternlengthbars <= '0') ), 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;
Date: 2025-06-27 08:44:51 Duration: 1s590ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' 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 ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-27 08:30:58 Duration: 1s458ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
15 88ms 2s762ms 414ms 195 1m20s 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 #15
Day Hour Count Duration Avg duration Jun 27 08 195 1m20s 414ms [ User: postgres - Total duration: 1m20s - Times executed: 195 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m20s - Times executed: 195 ]
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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 = '667' 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 = '667' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-06-27 08:32:23 Duration: 2s762ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '667' 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 = '667' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-06-27 08:20:47 Duration: 2s440ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '689' 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 = '689' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-06-27 08:12:15 Duration: 1s356ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
16 16ms 347ms 74ms 151 11s257ms select distinct k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid from relevance_keylevels_results p inner join keylevels_results k on p.resultuid = k.resultuid inner join autochartist_stocklist asl on k.symbolid = asl.symbolid where k.patternclassid in (...) and asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Jun 27 08 151 11s257ms 74ms [ User: postgres - Total duration: 11s257ms - Times executed: 151 ]
[ Application: [unknown] - Total duration: 11s257ms - Times executed: 151 ]
-
SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-06-27 08:30:06 Duration: 347ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-06-27 08:15:54 Duration: 220ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-06-27 08:30:56 Duration: 200ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
17 18ms 363ms 71ms 151 10s726ms select distinct a.symbolid, p.resultuid, case when a.breakout >= ? then ? else ? end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient from relevance_autochartist_results p inner join autochartist_results a on p.resultuid = a.resultuid inner join autochartist_stocklist asl on a.symbolid = asl.symbolid where asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Jun 27 08 151 10s726ms 71ms [ User: postgres - Total duration: 10s726ms - Times executed: 151 ]
[ Application: [unknown] - Total duration: 10s726ms - Times executed: 151 ]
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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: 2025-06-27 08:30:05 Duration: 363ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2025-06-27 08:30:53 Duration: 216ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-06-27 08:01:22 Duration: 216ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
18 0ms 46ms 3ms 21,783 1m21s 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 #18
Day Hour Count Duration Avg duration Jun 27 08 21,783 1m21s 3ms [ User: postgres - Total duration: 1m21s - Times executed: 21783 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m21s - Times executed: 21783 ]
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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 = 'UK100' OR dss.downloadersymbol = 'UK100') AND dss.enabled = 1;
Date: 2025-06-27 08:00:06 Duration: 46ms 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 = 'HK50' OR dss.downloadersymbol = 'HK50') AND dss.enabled = 1;
Date: 2025-06-27 08:15:05 Duration: 30ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'JPM.US' OR dss.downloadersymbol = 'JPM.US') AND dss.enabled = 1;
Date: 2025-06-27 08:00:05 Duration: 30ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
19 0ms 12ms 2ms 3,054 6s437ms insert into keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errormargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestprice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) values (?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?, ?, ?.?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?.?, ?::timestamp without time zone, ?, ?.?, ?.?, ?, ?, ?.?, ?.?, ?::timestamp without time zone, ?, ?, ?.?, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Jun 27 08 3,054 6s437ms 2ms [ User: postgres - Total duration: 6s437ms - Times executed: 3054 ]
[ Application: [unknown] - Total duration: 6s437ms - Times executed: 3054 ]
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INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (9.000000000000000000000000000000, - 1, 2, '2025-06-27 06:26:09'::timestamp without time zone, '2025-06-27 09:15:00', 0.513000000000000899700000000000, 3, 371, 197.701999999999998200000000000000, '2025-06-26 11:30:00', '2025-06-25 10:45:00', '2025-06-23 12:30:00', '', '', '', '', '', '', '', 568, 197.620100000000007900000000000000, '2025-06-27 09:15:00'::timestamp without time zone, '2025-06-27 09:15:00', 198.199999999999988600000000000000, 0.081900000000000305890000000000, - 1, 500991628222653200, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|500991628222653200|197.702|2|2025-06-27 09:15:00|2025-06-27 09:15:00|-1|-1', 198.409940000000006000000000000000, 0.707940000000007785200000000000, 2, '2025-06-23 12:30:00', 198.519000000000005500000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-27 08:30:40 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (7.000000000000000000000000000000, - 1, 1, '2025-06-27 06:26:19'::timestamp without time zone, '', 0.500000000000000000000000000000, 6, 316, 10.102830000000000865000000000000, '2025-06-27 08:00:00', '2025-06-27 04:00:00', '2025-06-26 15:00:00', '2025-06-24 13:45:00', '2025-06-24 01:45:00', '2025-06-24 01:00:00', '', '', '', '', 1106, 10.110677000000000803000000000000, '2025-06-27 09:15:00'::timestamp without time zone, '2025-06-27 09:15:00', 0.000000000000000000000000000000, 0.007868000000000031219000000000, - 1, 500991628252276200, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|500991628252276200|10.10283|1|2025-06-27 09:15:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-06-24 01:00:00', 10.183669999999999334000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-27 08:30:49 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (7.000000000000000000000000000000, - 1, 1, '2025-06-27 06:26:04'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 171, 0.176449999999999995700000000000, '2025-06-26 23:30:00', '2025-06-23 17:00:00', '2025-06-23 10:00:00', '', '', '', '', '', '', '', 342, 0.177345000000000002600000000000, '2025-06-27 09:00:00'::timestamp without time zone, '2025-06-27 09:00:00', 0.000000000000000000000000000000, 0.000894999999999999962200000000, - 1, 515840249474910300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249474910300|0.17645|1|2025-06-27 09:00:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-06-23 10:00:00', 0.185349999999999987000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-27 08:30:34 Duration: 11ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
20 0ms 6ms 1ms 733 1s223ms select s.symbolid, dss.downloadfrequency, dss.downloadersymbol from downloadersymbolsettings dss inner join symbols s on dss.symbolid = s.symbolid where dss.classname = ? and s.deleted = ? and dss.enabled = ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Jun 27 08 733 1s223ms 1ms [ User: postgres - Total duration: 1s223ms - Times executed: 733 ]
[ Application: [unknown] - Total duration: 1s223ms - Times executed: 733 ]
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'Alpari' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-27 08:30:24 Duration: 6ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'GLOBALGTMT5' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-27 08:00:05 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'PEPPERSTONE' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-27 08:30:13 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 3s578ms 4,015 0ms 20ms 0ms WITH rar_max as ( ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Jun 27 08 4,015 3s578ms 0ms [ User: postgres - Total duration: 2h4m - Times executed: 4015 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2h3m59s - Times executed: 3968 ]
[ Application: [unknown] - Total duration: 133ms - Times executed: 47 ]
-
WITH rar_max as ( ;
Date: 2025-06-27 08:27:41 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.236
-
WITH rar_max as ( ;
Date: 2025-06-27 08:59:55 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
WITH rar_max as ( ;
Date: 2025-06-27 08:00:03 Duration: 16ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
2 1s918ms 5,390 0ms 9ms 0ms SELECT ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 08 5,390 1s918ms 0ms [ User: postgres - Total duration: 11s811ms - Times executed: 5390 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 11s458ms - Times executed: 4489 ]
[ Application: [unknown] - Total duration: 353ms - Times executed: 901 ]
-
SELECT ;
Date: 2025-06-27 08:16:41 Duration: 9ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
SELECT ;
Date: 2025-06-27 08:45:05 Duration: 8ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
SELECT ;
Date: 2025-06-27 08:58:48 Duration: 8ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
3 966ms 733 0ms 5ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 08 733 966ms 1ms [ User: postgres - Total duration: 1s223ms - Times executed: 733 ]
[ Application: [unknown] - Total duration: 1s223ms - Times executed: 733 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-27 08:30:34 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-27 08:46:31 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-27 08:30:57 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
4 501ms 1,856 0ms 1ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 08 1,856 501ms 0ms [ User: postgres - Total duration: 4s133ms - Times executed: 1856 ]
[ Application: [unknown] - Total duration: 4s133ms - Times executed: 1856 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:15:03 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:47:09 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:30:11 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
5 310ms 3,222 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 08 3,222 310ms 0ms [ User: postgres - Total duration: 1s841ms - Times executed: 3222 ]
[ Application: [unknown] - Total duration: 1s841ms - Times executed: 3222 ]
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:30:58 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:30:42 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:10:51 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
6 235ms 2,121 0ms 0ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #6
Day Hour Count Duration Avg duration 08 2,121 235ms 0ms [ User: postgres - Total duration: 1s378ms - Times executed: 2121 ]
[ Application: [unknown] - Total duration: 1s378ms - Times executed: 2121 ]
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:10:53 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:00:43 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:10:35 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
7 180ms 1,145 0ms 6ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 08 1,145 180ms 0ms [ User: postgres - Total duration: 10ms - Times executed: 1145 ]
[ Application: [unknown] - Total duration: 10ms - Times executed: 1145 ]
-
SET extra_float_digits = 3;
Date: 2025-06-27 08:00:04 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
SET extra_float_digits = 3;
Date: 2025-06-27 08:25:32 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
SET extra_float_digits = 3;
Date: 2025-06-27 08:27:40 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.8
8 155ms 2,802 0ms 6ms 0ms select 1;Times Reported Time consuming prepare #8
Day Hour Count Duration Avg duration 08 2,802 155ms 0ms [ User: postgres - Total duration: 11ms - Times executed: 2802 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 11ms - Times executed: 2695 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 107 ]
-
select 1;
Date: 2025-06-27 08:45:05 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
select 1;
Date: 2025-06-27 08:00:03 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
select 1;
Date: 2025-06-27 08:15:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
9 128ms 811 0ms 1ms 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 08 811 128ms 0ms [ User: postgres - Total duration: 7ms - Times executed: 811 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 7ms - Times executed: 811 ]
-
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: 2025-06-27 08:13:17 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.246
-
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: 2025-06-27 08:13:17 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.246
-
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: 2025-06-27 08:13:48 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.246
10 93ms 16 4ms 8ms 5ms with sym_info as ( ;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 08 16 93ms 5ms [ User: postgres - Total duration: 25s442ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 25s442ms - Times executed: 16 ]
-
with sym_info as ( ;
Date: 2025-06-27 08:21:43 Duration: 8ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
-
with sym_info as ( ;
Date: 2025-06-27 08:51:45 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
-
with sym_info as ( ;
Date: 2025-06-27 08:06:46 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
11 66ms 58 0ms 5ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 08 58 66ms 1ms [ User: postgres - Total duration: 21s907ms - Times executed: 58 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 21s907ms - Times executed: 58 ]
-
WITH last_candle AS ( ;
Date: 2025-06-27 08:00:03 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
WITH last_candle AS ( ;
Date: 2025-06-27 08:48:14 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
WITH last_candle AS ( ;
Date: 2025-06-27 08:44:07 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
12 54ms 124 0ms 3ms 0ms WITH pre_symbols AS ( /* find relevant symbols */ ;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 08 124 54ms 0ms [ User: postgres - Total duration: 2s103ms - Times executed: 124 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s103ms - Times executed: 124 ]
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-06-27 08:13:23 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.246
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-06-27 08:13:51 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.246
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-06-27 08:12:47 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.246
13 48ms 18 1ms 3ms 2ms select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 08 18 48ms 2ms [ User: postgres - Total duration: 33ms - Times executed: 18 ]
[ Application: [unknown] - Total duration: 33ms - Times executed: 18 ]
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-06-27 08:50:03 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-06-27 08:21:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-06-27 08:10:02 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
14 48ms 30 0ms 2ms 1ms with wh_patitioned as ( ;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 08 30 48ms 1ms [ User: postgres - Total duration: 1s91ms - Times executed: 30 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s91ms - Times executed: 30 ]
-
with wh_patitioned as ( ;
Date: 2025-06-27 08:03:24 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
with wh_patitioned as ( ;
Date: 2025-06-27 08:05:02 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
with wh_patitioned as ( ;
Date: 2025-06-27 08:19:10 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
15 38ms 145 0ms 0ms 0ms INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #15
Day Hour Count Duration Avg duration 08 145 38ms 0ms [ User: postgres - Total duration: 183ms - Times executed: 145 ]
[ Application: [unknown] - Total duration: 183ms - Times executed: 145 ]
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:01:36 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:00:45 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:10:53 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
16 22ms 44 0ms 1ms 0ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 08 44 22ms 0ms [ User: postgres - Total duration: 0ms - Times executed: 44 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 0ms - Times executed: 44 ]
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-27 08:36:58 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-27 08:48:14 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-27 08:26:09 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
17 18ms 6 2ms 3ms 3ms select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 08 6 18ms 3ms [ User: postgres - Total duration: 12ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 12ms - 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: 2025-06-27 08:40:04 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: 2025-06-27 08:00:05 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: 2025-06-27 08:10:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
18 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 #18
Day Hour Count Duration Avg duration 08 6 17ms 2ms [ User: postgres - Total duration: 39s951ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 39s951ms - 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: 2025-06-27 08:00:03 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: 2025-06-27 08:10:02 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: 2025-06-27 08:30:03 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
19 17ms 24 0ms 1ms 0ms select count(*) from datafeed_restarter_events where is_current_entry = 1;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 08 24 17ms 0ms [ User: postgres - Total duration: 67ms - Times executed: 24 ]
[ Application: [unknown] - Total duration: 67ms - Times executed: 24 ]
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-06-27 08:55:00 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-06-27 08:00:07 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-06-27 08:10:03 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
20 15ms 1,091 0ms 1ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 08 1,091 15ms 0ms [ User: postgres - Total duration: 14ms - Times executed: 1091 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14ms - Times executed: 1091 ]
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-27 08:55:43 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-27 08:58:48 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-27 08:38:13 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 42s914ms 12,399 0ms 48ms 3ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Jun 27 08 12,399 42s914ms 3ms [ User: postgres - Total duration: 2h12m45s - Times executed: 12399 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2h12m45s - Times executed: 12352 ]
[ Application: [unknown] - Total duration: 133ms - Times executed: 47 ]
-
WITH rar_max as ( ;
Date: 2025-06-27 08:00:03 Duration: 48ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '606362359830488302', $2 = '606362359830488302', $3 = '606362359830488302'
-
WITH rar_max as ( ;
Date: 2025-06-27 08:27:40 Duration: 47ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.8 parameters: $1 = '606362118358819301', $2 = '606362118358819301', $3 = '606362118358819301'
-
WITH rar_max as ( ;
Date: 2025-06-27 08:00:03 Duration: 42ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '606362359489802302', $2 = '606362359489802302', $3 = '606362359489802302'
2 26s930ms 58,707 0ms 38ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 08 58,707 26s930ms 0ms [ User: postgres - Total duration: 2m14s - Times executed: 58707 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m14s - Times executed: 57806 ]
[ Application: [unknown] - Total duration: 353ms - Times executed: 901 ]
-
SELECT ;
Date: 2025-06-27 08:00:03 Duration: 38ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '0', $3 = '0', $4 = 'US30', $5 = 'US30'
-
SELECT ;
Date: 2025-06-27 08:00:03 Duration: 24ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '0', $3 = '0', $4 = 'CHINA50', $5 = 'CHINA50'
-
SELECT ;
Date: 2025-06-27 08:00:06 Duration: 23ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '529', $2 = '0', $3 = '0', $4 = 'Crypto10', $5 = 'Crypto10'
3 1s496ms 52 0ms 48ms 28ms with wh_patitioned as ( ;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 08 52 1s496ms 28ms [ User: postgres - Total duration: 1s704ms - Times executed: 52 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s704ms - Times executed: 52 ]
-
with wh_patitioned as ( ;
Date: 2025-06-27 08:03:24 Duration: 48ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '529', $2 = '529', $3 = '529', $4 = '529', $5 = '529', $6 = '529', $7 = '529', $8 = '529', $9 = '529'
-
with wh_patitioned as ( ;
Date: 2025-06-27 08:10:02 Duration: 45ms 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: 2025-06-27 08:55:01 Duration: 45ms 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'
4 1s374ms 195 4ms 18ms 7ms WITH last_candle AS ( ;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 08 195 1s374ms 7ms [ User: postgres - Total duration: 1m20s - Times executed: 195 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m20s - Times executed: 195 ]
-
WITH last_candle AS ( ;
Date: 2025-06-27 08:12:09 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2025-06-27 08:12:09 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2025-06-27 08:40:08 Duration: 16ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558'
5 1s371ms 733 1ms 14ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 08 733 1s371ms 1ms [ User: postgres - Total duration: 1s223ms - Times executed: 733 ]
[ Application: [unknown] - Total duration: 1s223ms - Times executed: 733 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-27 08:45:04 Duration: 14ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'AXIORY'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-27 08:30:51 Duration: 8ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'DXFEED_FX'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-27 08:30:43 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'MILLENNIUMPF'
6 988ms 49,693 0ms 16ms 0ms select 1;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 08 49,693 988ms 0ms [ User: postgres - Total duration: 208ms - Times executed: 49693 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 207ms - Times executed: 49453 ]
[ Application: [unknown] - Total duration: 1ms - Times executed: 240 ]
-
select 1;
Date: 2025-06-27 08:45:06 Duration: 16ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
select 1;
Date: 2025-06-27 08:00:03 Duration: 15ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
select 1;
Date: 2025-06-27 08:45:06 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
7 649ms 51 9ms 21ms 12ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 08 51 649ms 12ms [ User: postgres - Total duration: 0ms - Times executed: 51 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 0ms - Times executed: 51 ]
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-27 08:26:09 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-27 08:36:58 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-27 08:00:59 Duration: 19ms 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'
8 502ms 16 27ms 43ms 31ms with sym_info as ( ;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 08 16 502ms 31ms [ User: postgres - Total duration: 25s442ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 25s442ms - Times executed: 16 ]
-
with sym_info as ( ;
Date: 2025-06-27 08:07:09 Duration: 43ms 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: 2025-06-27 08:51:45 Duration: 39ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
-
with sym_info as ( ;
Date: 2025-06-27 08:06:46 Duration: 36ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
9 494ms 6,175 0ms 0ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 08 6,175 494ms 0ms [ User: postgres - Total duration: 6s440ms - Times executed: 6175 ]
[ Application: [unknown] - Total duration: 6s440ms - Times executed: 6175 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:30:57 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-27 09:15:00', $2 = '3.491', $3 = '3.5085', $4 = '3.491', $5 = '3.508', $6 = '222', $7 = '605679104052715300', $8 = '0', $9 = '2025-06-27 08:30:57.124', $10 = '2025-06-27 08:30:57.067', $11 = '3.491', $12 = '3.5085', $13 = '3.491', $14 = '3.508', $15 = '222', $16 = '0', $17 = '2025-06-27 08:30:57.125', $18 = '2025-06-27 08:30:57.067'
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:30:06 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-27 09:15:00', $2 = '1.37283', $3 = '1.37342', $4 = '1.37271', $5 = '1.37317', $6 = '1599', $7 = '515840243867772300', $8 = '0', $9 = '2025-06-27 08:30:06.694', $10 = '2025-06-27 08:30:06.634', $11 = '1.37283', $12 = '1.37342', $13 = '1.37271', $14 = '1.37317', $15 = '1599', $16 = '0', $17 = '2025-06-27 08:30:06.694', $18 = '2025-06-27 08:30:06.634'
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:30:11 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-27 09:00:00', $2 = '43516.2', $3 = '43542.725', $4 = '43511.7', $5 = '43537.725', $6 = '621', $7 = '515840249387894300', $8 = '0', $9 = '2025-06-27 08:30:11.76', $10 = '2025-06-27 08:30:11.694', $11 = '43516.2', $12 = '43542.725', $13 = '43511.7', $14 = '43537.725', $15 = '621', $16 = '0', $17 = '2025-06-27 08:30:11.76', $18 = '2025-06-27 08:30:11.694'
10 352ms 124 0ms 22ms 2ms WITH pre_symbols AS ( /* find relevant symbols */ ;Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 08 124 352ms 2ms [ User: postgres - Total duration: 2s103ms - Times executed: 124 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s103ms - Times executed: 124 ]
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-06-27 08:13:51 Duration: 22ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.246 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: 2025-06-27 08:13:51 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.246 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', $1851 = '5'
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-06-27 08:13:51 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.246 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'
11 329ms 811 0ms 5ms 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 #11
Day Hour Count Duration Avg duration 08 811 329ms 0ms [ User: postgres - Total duration: 7ms - Times executed: 811 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 7ms - Times executed: 811 ]
-
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: 2025-06-27 08:12:47 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.246
-
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: 2025-06-27 08:13:17 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.246
-
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: 2025-06-27 08:13:17 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.246
12 285ms 3,517 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 #12
Day Hour Count Duration Avg duration 08 3,517 285ms 0ms [ User: postgres - Total duration: 1s966ms - Times executed: 3517 ]
[ Application: [unknown] - Total duration: 1s966ms - Times executed: 3517 ]
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:30:43 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-27 09:00:00', $2 = '39.85859', $3 = '39.86021', $4 = '39.83326', $5 = '39.83636', $6 = '306', $7 = '515840245900740300', $8 = '0', $9 = '2025-06-27 08:30:43.576', $10 = '2025-06-27 08:30:43.575', $11 = '39.85859', $12 = '39.86021', $13 = '39.83326', $14 = '39.83636', $15 = '306', $16 = '0', $17 = '2025-06-27 08:30:43.576', $18 = '2025-06-27 08:30:43.575'
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:41:39 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-27 08:30:00', $2 = '8531', $3 = '8532', $4 = '8513.4', $5 = '8515.4', $6 = '344', $7 = '515840248015340300', $8 = '0', $9 = '2025-06-27 08:41:39.802', $10 = '2025-06-27 08:41:39.76', $11 = '8531', $12 = '8532', $13 = '8513.4', $14 = '8515.4', $15 = '344', $16 = '0', $17 = '2025-06-27 08:41:39.802', $18 = '2025-06-27 08:41:39.76'
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:11:50 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-26 22:30:00', $2 = '8750.2', $3 = '8760.4', $4 = '8747.7', $5 = '8758.2', $6 = '702', $7 = '515840247999481300', $8 = '0', $9 = '2025-06-27 08:11:50.265', $10 = '2025-06-27 08:11:50.208', $11 = '8750.2', $12 = '8760.4', $13 = '8747.7', $14 = '8758.2', $15 = '702', $16 = '0', $17 = '2025-06-27 08:11:50.265', $18 = '2025-06-27 08:11:50.208'
13 203ms 2,313 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 #13
Day Hour Count Duration Avg duration 08 2,313 203ms 0ms [ User: postgres - Total duration: 1s473ms - Times executed: 2313 ]
[ Application: [unknown] - Total duration: 1s473ms - Times executed: 2313 ]
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:10:53 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-27 07:00:00', $2 = '43490.85', $3 = '43496.85', $4 = '43476.85', $5 = '43485.35', $6 = '459', $7 = '515840248000890300', $8 = '0', $9 = '2025-06-27 08:10:53.844', $10 = '2025-06-27 08:10:53.651', $11 = '43490.85', $12 = '43496.85', $13 = '43476.85', $14 = '43485.35', $15 = '459', $16 = '0', $17 = '2025-06-27 08:10:53.844', $18 = '2025-06-27 08:10:53.651'
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:10:31 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-26 21:00:00', $2 = '157.43', $3 = '157.43', $4 = '157.04', $5 = '157.09', $6 = '649', $7 = '515840247929791300', $8 = '0', $9 = '2025-06-27 08:10:31.328', $10 = '2025-06-27 08:10:31.259', $11 = '157.43', $12 = '157.43', $13 = '157.04', $14 = '157.09', $15 = '649', $16 = '0', $17 = '2025-06-27 08:10:31.328', $18 = '2025-06-27 08:10:31.259'
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-27 08:10:51 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-27 07:00:00', $2 = '22472.6', $3 = '22480.8', $4 = '22469.6', $5 = '22476.9', $6 = '2043', $7 = '515840248039327300', $8 = '0', $9 = '2025-06-27 08:10:51.636', $10 = '2025-06-27 08:10:51.594', $11 = '22472.6', $12 = '22480.8', $13 = '22469.6', $14 = '22476.9', $15 = '2043', $16 = '0', $17 = '2025-06-27 08:10:51.636', $18 = '2025-06-27 08:10:51.594'
14 170ms 185 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 #14
Day Hour Count Duration Avg duration 08 185 170ms 0ms [ User: postgres - Total duration: 1s176ms - Times executed: 185 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s71ms - Times executed: 173 ]
[ Application: [unknown] - Total duration: 104ms - Times executed: 12 ]
-
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2025-06-27 08:01:38 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '558', $2 = 'USDJPY', $3 = '558'
-
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2025-06-27 08:00:07 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.239 parameters: $1 = '667', $2 = 'GBPUSD', $3 = '667'
-
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2025-06-27 08:21:06 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.42 parameters: $1 = '689', $2 = 'WTI', $3 = '689'
15 98ms 598 0ms 6ms 0ms /*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 08 598 98ms 0ms [ User: postgres - Total duration: 51ms - Times executed: 598 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 51ms - Times executed: 598 ]
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2025-06-27 08:01:35 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '606362532265346301'
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2025-06-27 08:01:35 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '606362120890676301'
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2025-06-27 08:01:35 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '606343482083086301'
16 78ms 18 3ms 6ms 4ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 08 18 78ms 4ms [ User: postgres - Total duration: 1s913ms - Times executed: 18 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s913ms - Times executed: 18 ]
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-06-27 08:00:55 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '627', $2 = '627'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-06-27 08:58:48 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '958', $2 = '958'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-06-27 08:46:03 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '627', $2 = '627'
17 67ms 50 0ms 2ms 1ms WITH rcr_max as ( ;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 08 50 67ms 1ms [ User: postgres - Total duration: 14ms - Times executed: 50 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14ms - Times executed: 50 ]
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WITH rcr_max as ( ;
Date: 2025-06-27 08:50:06 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '606362596299020305', $2 = '606362596299020305', $3 = '606362596299020305'
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WITH rcr_max as ( ;
Date: 2025-06-27 08:44:10 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '606362596299020305', $2 = '606362596299020305', $3 = '606362596299020305'
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WITH rcr_max as ( ;
Date: 2025-06-27 08:10:05 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '606362596299020305', $2 = '606362596299020305', $3 = '606362596299020305'
18 42ms 218 0ms 4ms 0ms /*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 08 218 42ms 0ms [ User: postgres - Total duration: 14ms - Times executed: 218 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14ms - Times executed: 218 ]
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/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;
Date: 2025-06-27 08:01:35 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '606362236786529303'
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/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;
Date: 2025-06-27 08:01:40 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '606362474216380303'
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/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;
Date: 2025-06-27 08:17:36 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '606362177287243303'
19 42ms 25 1ms 3ms 1ms SELECT DISTINCT trumpetSymbolID AS sid, trumpetTimeGranularity AS tg FROM brokersymbollist bsl INNER JOIN downloadersymbolsettings dss ON bsl.symbolid = dss.symbolid INNER JOIN symbols s ON dss.symbolid = s.symbolid LEFT JOIN powerstats_symboldata psd ON s.symbolid = psd.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE (code ILIKE $2 OR s.symbol ILIKE $3 OR ((length(code) >= 4 AND $4 ILIKE code || '%') OR (length(s.symbol) >= 4 AND $5 ILIKE s.symbol || '%'))) and bsl.brokerid = $6 AND dss.classname <> $7 GROUP BY trumpetSymbolID, trumpetTimeGranularity ORDER BY sid DESC LIMIT 1;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 08 25 42ms 1ms [ User: postgres - Total duration: 90ms - Times executed: 25 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 90ms - Times executed: 25 ]
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SELECT DISTINCT trumpetSymbolID AS sid, trumpetTimeGranularity AS tg FROM brokersymbollist bsl INNER JOIN downloadersymbolsettings dss ON bsl.symbolid = dss.symbolid INNER JOIN symbols s ON dss.symbolid = s.symbolid LEFT JOIN powerstats_symboldata psd ON s.symbolid = psd.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE (code ILIKE $2 OR s.symbol ILIKE $3 OR ((length(code) >= 4 AND $4 ILIKE code || '%') OR (length(s.symbol) >= 4 AND $5 ILIKE s.symbol || '%'))) and bsl.brokerid = $6 AND dss.classname <> $7 GROUP BY trumpetSymbolID, trumpetTimeGranularity ORDER BY sid DESC LIMIT 1;
Date: 2025-06-27 08:01:37 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '558', $2 = 'AUDNZD', $3 = 'AUDNZD', $4 = 'AUDNZD', $5 = 'AUDNZD', $6 = '558', $7 = 'IG UNSCALED'
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SELECT DISTINCT trumpetSymbolID AS sid, trumpetTimeGranularity AS tg FROM brokersymbollist bsl INNER JOIN downloadersymbolsettings dss ON bsl.symbolid = dss.symbolid INNER JOIN symbols s ON dss.symbolid = s.symbolid LEFT JOIN powerstats_symboldata psd ON s.symbolid = psd.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE (code ILIKE $2 OR s.symbol ILIKE $3 OR ((length(code) >= 4 AND $4 ILIKE code || '%') OR (length(s.symbol) >= 4 AND $5 ILIKE s.symbol || '%'))) and bsl.brokerid = $6 AND dss.classname <> $7 GROUP BY trumpetSymbolID, trumpetTimeGranularity ORDER BY sid DESC LIMIT 1;
Date: 2025-06-27 08:01:37 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '558', $2 = 'USDJPY', $3 = 'USDJPY', $4 = 'USDJPY', $5 = 'USDJPY', $6 = '558', $7 = 'IG UNSCALED'
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SELECT DISTINCT trumpetSymbolID AS sid, trumpetTimeGranularity AS tg FROM brokersymbollist bsl INNER JOIN downloadersymbolsettings dss ON bsl.symbolid = dss.symbolid INNER JOIN symbols s ON dss.symbolid = s.symbolid LEFT JOIN powerstats_symboldata psd ON s.symbolid = psd.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE (code ILIKE $2 OR s.symbol ILIKE $3 OR ((length(code) >= 4 AND $4 ILIKE code || '%') OR (length(s.symbol) >= 4 AND $5 ILIKE s.symbol || '%'))) and bsl.brokerid = $6 AND dss.classname <> $7 GROUP BY trumpetSymbolID, trumpetTimeGranularity ORDER BY sid DESC LIMIT 1;
Date: 2025-06-27 08:01:37 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '558', $2 = 'XAUUSD', $3 = 'XAUUSD', $4 = 'XAUUSD', $5 = 'XAUUSD', $6 = '558', $7 = 'IG UNSCALED'
20 32ms 647 0ms 1ms 0ms SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 08 647 32ms 0ms [ User: postgres - Total duration: 22ms - Times executed: 647 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 22ms - Times executed: 647 ]
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-06-27 08:01:35 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '515840243274925300'
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-06-27 08:01:35 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '515840243241002300'
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-06-27 08:17:40 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '515840233916163300'
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Events
Log levels
Key values
- 518,593 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 0 ERROR entries
- 0 WARNING entries
Errors per 5 minutes
NO DATASET
Most Frequent Errors/Events
Key values
- 0 Max number of times the same event was reported
- 0 Total events found
Rank Times reported Error NO DATASET