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Global information
- Generated on Mon Aug 25 12:00:35 2025
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2025-08-25_130000.log, ..., /home/postgres/pg_data/data/pg_log/postgresql-2025-08-25_134815.log
- Parsed 3,348,786 log entries in 1m34s
- Log start from 2025-08-25 13:00:00 to 2025-08-25 14:00:00
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Overview
Global Stats
- 275 Number of unique normalized queries
- 197,784 Number of queries
- 2h2m48s Total query duration
- 2025-08-25 13:00:00 First query
- 2025-08-25 14:00:00 Last query
- 2,505 queries/s at 2025-08-25 13:15:04 Query peak
- 2h2m48s Total query duration
- 11s818ms Prepare/parse total duration
- 1m18s Bind total duration
- 2h1m17s 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
- 42 Total number of automatic vacuums
- 58 Total number of automatic analyzes
- 618 Number temporary file
- 177.58 MiB Max size of temporary file
- 7.74 MiB Average size of temporary file
- 4,926 Total number of sessions
- 12 sessions at 2025-08-25 13:45:36 Session peak
- 3d4h36m10s Total duration of sessions
- 55s982ms Average duration of sessions
- 40 Average queries per session
- 1s495ms Average queries duration per session
- 54s486ms Average idle time per session
- 4,926 Total number of connections
- 44 connections/s at 2025-08-25 13:19:27 Connection peak
- 2 Total number of databases
SQL Traffic
Key values
- 2,505 queries/s Query Peak
- 2025-08-25 13:15:04 Date
SELECT Traffic
Key values
- 2,426 queries/s Query Peak
- 2025-08-25 13:15:04 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 236 queries/s Query Peak
- 2025-08-25 13:00:55 Date
Queries duration
Key values
- 2h2m48s 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) Aug 25 13 197,783 0ms 45s629ms 36ms 3m39s 3m59s 4m6s 14 1 0ms 0ms 0ms 0ms 0ms 0ms Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Aug 25 13 147,749 26 1ms 7s203ms 13s469ms 16s421ms 14 1 0 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Aug 25 13 30,900 2,327 16 96 1ms 893ms 1s295ms 3s478ms 14 0 0 0 0 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Aug 25 13 33,166 171,291 5.16 17.48% 14 0 1 1.00 0.00% Day Hour Count Average / Second Aug 25 13 4,926 1.37/s 14 0 0.00/s Day Hour Count Average Duration Average idle time Aug 25 13 4,926 55s982ms 54s505ms 14 0 0ms 0ms -
Connections
Established Connections
Key values
- 44 connections Connection Peak
- 2025-08-25 13:19:27 Date
Connections per database
Key values
- acaweb_fx Main Database
- 4,926 connections Total
Connections per user
Key values
- postgres Main User
- 4,926 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 1458 connections
- 4,926 Total connections
Host Count 127.0.0.1 117 192.168.0.114 4 192.168.0.216 100 192.168.0.74 662 192.168.1.11 2 192.168.1.127 4 192.168.1.145 124 192.168.1.15 1,304 192.168.1.20 125 192.168.1.231 20 192.168.1.239 6 192.168.1.90 85 192.168.2.126 61 192.168.2.182 12 192.168.2.205 12 192.168.2.82 47 192.168.3.199 36 192.168.4.136 6 192.168.4.142 1,458 192.168.4.150 10 192.168.4.21 17 192.168.4.238 14 192.168.4.33 95 192.168.4.35 1 192.168.4.98 330 [local] 274 -
Sessions
Simultaneous sessions
Key values
- 12 sessions Session Peak
- 2025-08-25 13:45:36 Date
Histogram of session times
Key values
- 3,967 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 4,926 sessions Total
Sessions per user
Key values
- postgres Main User
- 4,926 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 4,926 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 114 19s28ms 166ms 182.165.1.54 1 3h38m33s 3h38m33s 192.168.0.114 4 20m11s 5m2s 192.168.0.216 100 43s122ms 431ms 192.168.0.74 664 11h59m43s 1m5s 192.168.1.11 2 1h3m11s 31m35s 192.168.1.127 4 14s160ms 3s540ms 192.168.1.145 124 3h57m32s 1m54s 192.168.1.15 1,304 11h10m1s 30s829ms 192.168.1.20 125 13h58m8s 6m42s 192.168.1.231 20 9h53m1s 29m39s 192.168.1.239 6 49ms 8ms 192.168.1.90 85 41s818ms 491ms 192.168.2.126 61 8s201ms 134ms 192.168.2.182 12 917ms 76ms 192.168.2.205 12 629ms 52ms 192.168.2.82 47 5s554ms 118ms 192.168.3.199 36 1s94ms 30ms 192.168.4.136 6 73ms 12ms 192.168.4.142 1,458 10m28s 430ms 192.168.4.150 10 20h3m30s 2h21s 192.168.4.21 17 11m21s 40s70ms 192.168.4.238 14 21s543ms 1s538ms 192.168.4.33 95 5m10s 3s263ms 192.168.4.35 1 168ms 168ms 192.168.4.98 330 13s28ms 39ms [local] 274 2m27s 538ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 10,798 buffers Checkpoint Peak
- 2025-08-25 13:36:32 Date
- 209.892 seconds Highest write time
- 0.011 seconds Sync time
Checkpoints Wal files
Key values
- 6 files Wal files usage Peak
- 2025-08-25 13:06:32 Date
Checkpoints distance
Key values
- 174.93 Mo Distance Peak
- 2025-08-25 13:06:32 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Aug 25 13 44,013 1,745.007s 0.063s 1,745.365s 14 0 0s 0s 0s Day Hour Added Removed Recycled Synced files Longest sync Average sync Aug 25 13 0 0 25 1,972 0.005s 0s 14 0 0 0 0 0s 0s Day Hour Count Avg time (sec) Aug 25 13 0 0s 14 0 0s Day Hour Mean distance Mean estimate Aug 25 13 33,422.75 kB 71,710.58 kB 14 0.00 kB 0.00 kB -
Temporary Files
Size of temporary files
Key values
- 155.05 MiB Temp Files size Peak
- 2025-08-25 13:50:07 Date
Number of temporary files
Key values
- 30 per second Temp Files Peak
- 2025-08-25 13:17:09 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Aug 25 13 618 4.67 GiB 7.74 MiB 14 0 0 0 Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 159 688.08 MiB 3.19 MiB 9.37 MiB 4.33 MiB with rar_max as ( ;-
WITH rar_max as ( ;
Date: 2025-08-25 13:49:17 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver
2 42 1.68 GiB 2.73 MiB 177.58 MiB 40.94 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), 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: 2025-08-25 13:00:10 Duration: 7s693ms 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: 2025-08-25 13:40:10 Duration: 7s621ms 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: 2025-08-25 13:30:09 Duration: 6s966ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
3 16 489.70 MiB 30.60 MiB 30.61 MiB 30.61 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: 2025-08-25 13:26:13 Duration: 1s515ms 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: 2025-08-25 13:48:13 Duration: 1s358ms 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: 2025-08-25 13:35:13 Duration: 1s265ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
4 16 996.75 MiB 62.30 MiB 62.30 MiB 62.30 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: 2025-08-25 13:35:16 Duration: 3s284ms 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: 2025-08-25 13:26:16 Duration: 3s225ms 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: 2025-08-25 13:01:15 Duration: 2s23ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
5 8 556.11 MiB 69.50 MiB 69.53 MiB 69.51 MiB select updateresultsmaterializedview ();-
select updateresultsmaterializedview ();
Date: 2025-08-25 13:35:37 Duration: 4s177ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-08-25 13:32:17 Duration: 3s137ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-08-25 13:17:17 Duration: 3s57ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
6 4 331.00 MiB 82.70 MiB 82.79 MiB 82.75 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2025-08-25 13:32:14 Duration: 11s793ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-08-25 13:17:14 Duration: 11s479ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-08-25 13:02:14 Duration: 11s374ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
Queries generating the largest temporary files
Rank Size Query 1 177.58 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 = 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: 2025-08-25 13:30:04 ]
2 145.33 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-08-25 13:10:07 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
3 130.42 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: 2025-08-25 13:00:05 ]
4 105.47 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: 2025-08-25 13:20:05 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
5 103.95 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-08-25 13:40:05 ]
6 97.85 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: 2025-08-25 13:20:04 ]
7 93.12 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-08-25 13:50:05 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
8 86.70 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-08-25 13:50:04 ]
9 82.79 MiB select updateageforrelevantresults ();[ Date: 2025-08-25 13:02:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
10 82.77 MiB select updateageforrelevantresults ();[ Date: 2025-08-25 13:32:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
11 82.74 MiB select updateageforrelevantresults ();[ Date: 2025-08-25 13:47:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
12 82.70 MiB select updateageforrelevantresults ();[ Date: 2025-08-25 13:17:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
13 79.56 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: 2025-08-25 13:40:06 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
14 69.53 MiB select updateresultsmaterializedview ();[ Date: 2025-08-25 13:47:14 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
15 69.53 MiB select updateresultsmaterializedview ();[ Date: 2025-08-25 13:32:14 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
16 69.52 MiB select updateresultsmaterializedview ();[ Date: 2025-08-25 13:50:33 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
17 69.51 MiB select updateresultsmaterializedview ();[ Date: 2025-08-25 13:35:34 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
18 69.51 MiB select updateresultsmaterializedview ();[ Date: 2025-08-25 13:02:14 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
19 69.51 MiB select updateresultsmaterializedview ();[ Date: 2025-08-25 13:17:14 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
20 69.50 MiB select updateresultsmaterializedview ();[ Date: 2025-08-25 13:05:33 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
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Vacuums
Vacuums / Analyzes Distribution
Key values
- 0 sec Highest CPU-cost vacuum
Table
Database - Date
- 0 sec Highest CPU-cost analyze
Table
Database - Date
Analyzes per table
Key values
- public.solr_relevance_old (16) Main table analyzed (database acaweb_fx)
- 58 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 16 acaweb_fx.pg_catalog.pg_attribute 6 acaweb_fx.public.datafeeds_latestrun 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.latest_t15_candle_view 2 socialmedia.public.executions 1 acaweb_fx.public.autochartist_symbolupdates 1 socialmedia.public.processes 1 acaweb_fx.pg_catalog.pg_depend 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.patternresultsage 1 acaweb_fx.public.bigmovement_results_underlying 1 Total 58 Vacuums per table
Key values
- public.solr_relevance_old (19) Main table vacuumed on database acaweb_fx
- 42 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 19 16 15,378 0 57 0 0 9,982 16 1,814,839 acaweb_fx.public.datafeeds_latestrun 5 0 586 0 18 0 0 85 13 80,649 acaweb_fx.pg_toast.pg_toast_2619 2 2 334 0 74 0 0 206 63 235,860 acaweb_fx.pg_catalog.pg_attribute 2 2 1,649 0 325 0 134 755 288 1,735,353 acaweb_fx.public.relevance_keylevels_results 2 2 7,787 0 256 2 114 1,849 240 698,778 acaweb_fx.pg_catalog.pg_class 2 2 760 0 109 0 70 263 100 510,524 acaweb_fx.public.relevance_autochartist_results 2 2 6,916 0 149 3 499 1,348 134 408,153 acaweb_fx.public.relevance_fibonacci_results 2 2 2,552 0 38 2 103 439 23 97,700 acaweb_fx.pg_catalog.pg_index 1 1 90 0 11 0 0 28 10 75,281 acaweb_fx.pg_catalog.pg_type 1 1 137 0 21 0 0 54 15 88,760 acaweb_fx.public.autochartist_symbolupdates 1 1 25,303 0 2,924 1 38,067 7,354 537 650,795 acaweb_fx.pg_catalog.pg_statistic 1 1 975 0 174 0 609 485 158 618,440 acaweb_fx.public.relevance_consecutivecandles_results 1 1 73 0 4 0 0 18 4 22,802 acaweb_fx.public.latest_t15_candle_view 1 1 65 0 1 0 0 6 1 9,085 Total 42 34 62,605 44,459 4,161 8 39,596 22,872 1,602 7,047,019 Tuples removed per table
Key values
- public.solr_relevance_old (72986) Main table with removed tuples on database acaweb_fx
- 86661 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 19 16 72,986 135,035 20,737 0 3,961 acaweb_fx.public.autochartist_symbolupdates 1 1 5,364 44,588 16 0 40,691 acaweb_fx.pg_catalog.pg_attribute 2 2 2,656 18,998 252 0 500 acaweb_fx.public.relevance_keylevels_results 2 2 2,164 23,496 0 0 558 acaweb_fx.public.relevance_autochartist_results 2 2 1,258 17,329 0 0 760 acaweb_fx.pg_catalog.pg_statistic 1 1 606 4,180 0 0 1,194 acaweb_fx.public.relevance_fibonacci_results 2 2 561 2,993 0 0 204 acaweb_fx.pg_catalog.pg_class 2 2 285 4,016 18 0 300 acaweb_fx.public.datafeeds_latestrun 5 0 272 70 0 0 80 acaweb_fx.pg_catalog.pg_type 1 1 224 1,338 0 0 38 acaweb_fx.pg_toast.pg_toast_2619 2 2 139 346 10 0 100 acaweb_fx.public.latest_t15_candle_view 1 1 66 14 0 0 1 acaweb_fx.public.relevance_consecutivecandles_results 1 1 62 232 0 0 7 acaweb_fx.pg_catalog.pg_index 1 1 18 825 12 0 22 Total 42 34 86,661 253,460 21,045 0 48,416 Pages removed per table
Key values
- unknown (0) Main table with removed pages on database unknown
- 0 pages Total removed
Pages removed per tables
NO DATASET
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_toast.pg_toast_2619 2 2 139 0 acaweb_fx.pg_catalog.pg_index 1 1 18 0 acaweb_fx.pg_catalog.pg_type 1 1 224 0 acaweb_fx.public.autochartist_symbolupdates 1 1 5364 0 acaweb_fx.public.datafeeds_latestrun 5 0 272 0 acaweb_fx.pg_catalog.pg_statistic 1 1 606 0 acaweb_fx.pg_catalog.pg_attribute 2 2 2656 0 acaweb_fx.public.relevance_consecutivecandles_results 1 1 62 0 acaweb_fx.public.latest_t15_candle_view 1 1 66 0 acaweb_fx.public.relevance_keylevels_results 2 2 2164 0 acaweb_fx.pg_catalog.pg_class 2 2 285 0 acaweb_fx.public.solr_relevance_old 19 16 72986 0 acaweb_fx.public.relevance_autochartist_results 2 2 1258 0 acaweb_fx.public.relevance_fibonacci_results 2 2 561 0 Total 42 34 86,661 0 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Aug 25 13 42 58 14 0 0 - 0 sec Highest CPU-cost vacuum
-
Locks
Locks by types
Key values
- unknown Main Lock Type
- 0 locks Total
Most frequent waiting queries (N)
Rank Count Total time Min time Max time Avg duration Query NO DATASET
Queries that waited the most
Rank Wait time Query NO DATASET
-
Queries
Queries by type
Key values
- 147,750 Total read queries
- 41,965 Total write queries
Queries by database
Key values
- acaweb_fx Main database
- 187,177 Requests
- 2h55s (acaweb_fx)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 187,177 2h55s copy from 96 6s668ms copy to 26 18s258ms cte 7,866 1h55m40s ddl 16 500ms delete 16 24ms insert 23,225 23s537ms others 8,040 7s347ms select 144,971 3m58s tcl 676 196ms update 2,245 20s489ms socialmedia Total 10,607 21s563ms insert 7,675 8s699ms others 29 0ms select 2,779 12s706ms tcl 42 1ms update 82 155ms Queries by user
Key values
- postgres Main user
- 197,784 Requests
User Request type Count Duration postgres Total 197,784 2h1m17s copy from 96 6s668ms copy to 26 18s258ms cte 7,866 1h55m40s ddl 16 500ms delete 16 24ms insert 30,900 32s237ms others 8,069 7s348ms select 147,750 4m11s tcl 718 197ms update 2,327 20s645ms Duration by user
Key values
- 2h1m17s (postgres) Main time consuming user
User Request type Count Duration postgres Total 197,784 2h1m17s copy from 96 6s668ms copy to 26 18s258ms cte 7,866 1h55m40s ddl 16 500ms delete 16 24ms insert 30,900 32s237ms others 8,069 7s348ms select 147,750 4m11s tcl 718 197ms update 2,327 20s645ms Queries by host
Key values
- 192.168.1.15 Main host
- 86,750 Requests
- 31m57s (192.168.1.15)
- Main time consuming host
Host Request type Count Duration 127.0.0.1 Total 12,808 44s563ms copy to 26 18s258ms cte 25 263ms insert 10,341 11s804ms others 7 0ms select 716 13s146ms update 1,693 1s89ms 182.165.1.42 Total 50 104ms select 50 104ms 192.168.0.114 Total 139 39ms others 23 0ms select 52 31ms tcl 58 7ms update 6 0ms 192.168.0.216 Total 400 338ms others 200 20ms select 192 223ms update 8 94ms 192.168.0.236 Total 146 42ms cte 18 8ms select 128 33ms 192.168.0.239 Total 511 458ms select 511 458ms 192.168.0.42 Total 1,356 641ms insert 457 49ms select 899 592ms 192.168.0.74 Total 15,891 30m25s cte 1,805 30m18s others 1,324 15ms select 12,762 6s761ms 192.168.1.11 Total 3,621 392ms others 4 0ms select 3,617 392ms 192.168.1.127 Total 2,342 12s407ms others 8 0ms select 2,334 12s406ms 192.168.1.135 Total 262 641ms cte 8 295ms select 254 346ms 192.168.1.145 Total 18,589 26m58s cte 893 26m36s others 248 3ms select 17,448 22s505ms 192.168.1.15 Total 86,750 31m57s cte 3,547 30m38s others 2,608 30ms select 80,595 1m19s 192.168.1.20 Total 20,178 26m49s cte 890 26m27s others 250 3ms select 19,038 21s706ms 192.168.1.201 Total 1,557 1s459ms select 1,557 1s459ms 192.168.1.23 Total 1,870 1s526ms select 1,870 1s526ms 192.168.1.231 Total 43 3ms others 40 0ms select 3 3ms 192.168.1.239 Total 24 14ms others 12 1ms select 12 13ms 192.168.1.45 Total 52 97ms select 52 97ms 192.168.1.90 Total 225 39s341ms cte 6 39s151ms others 74 0ms select 145 188ms 192.168.1.93 Total 2 0ms select 2 0ms 192.168.1.97 Total 140 33ms cte 18 9ms select 122 23ms 192.168.2.126 Total 78 66ms others 17 0ms select 61 65ms 192.168.2.182 Total 48 316ms others 24 2ms select 12 12ms update 12 301ms 192.168.2.205 Total 138 131ms insert 90 7ms others 24 2ms select 20 20ms update 4 100ms 192.168.2.82 Total 1,074 2s5ms insert 672 1s142ms others 94 9ms select 184 100ms update 124 753ms 192.168.3.199 Total 144 228ms others 72 8ms select 60 71ms update 12 149ms 192.168.4.136 Total 18 1ms others 12 0ms select 4 1ms update 2 0ms 192.168.4.142 Total 16,068 11s833ms insert 11,663 10s524ms others 2,916 32ms select 1,489 1s276ms 192.168.4.150 Total 22 1s9ms others 21 0ms select 1 1s9ms 192.168.4.21 Total 3,699 3s298ms cte 547 2s802ms others 51 0ms select 3,101 495ms 192.168.4.238 Total 42 20s760ms cte 12 20s751ms insert 2 9ms others 28 0ms 192.168.4.33 Total 8,160 9s125ms insert 7,675 8s699ms select 403 270ms update 82 155ms 192.168.4.35 Total 3 39ms cte 1 39ms others 2 0ms 192.168.4.98 Total 996 7s805ms others 6 6s976ms select 6 26ms tcl 660 190ms update 324 611ms [local] Total 338 2m27s copy from 96 6s668ms cte 96 35s865ms ddl 16 500ms delete 16 24ms others 4 237ms select 50 1m26s update 60 17s387ms Queries by application
Key values
- PostgreSQL JDBC Driver Main application
- 166,921 Requests
- 1h56m53s (PostgreSQL JDBC Driver)
- Main time consuming application
Application Request type Count Duration PostgreSQL JDBC Driver Total 166,921 1h56m53s cte 7,703 1h54m25s insert 12,122 10s582ms others 3,794 51ms select 143,300 2m18s update 2 0ms [unknown] Total 30,411 1m37s cte 42 39s169ms insert 18,778 21s654ms others 4,271 7s59ms select 4,348 26s456ms tcl 718 197ms update 2,254 3s235ms psql Total 452 2m45s copy from 96 6s668ms copy to 26 18s258ms cte 121 36s128ms ddl 16 500ms delete 16 24ms others 4 237ms select 102 1m26s update 71 17s409ms Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2025-08-25 13:08:41 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 123,246 0-1ms duration
Slowest individual queries
Rank Duration Query 1 45s629ms 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: 2025-08-25 13:01:06 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
2 39s592ms 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: 2025-08-25 13:56:06 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
3 38s126ms 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: 2025-08-25 13:00:17 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
4 37s813ms 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: 2025-08-25 13:50:31 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
5 37s760ms 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: 2025-08-25 13:40:19 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
6 37s419ms 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: 2025-08-25 13:44:59 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
7 37s318ms 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: 2025-08-25 13:30:22 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
8 36s760ms 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: 2025-08-25 13:55:52 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
9 36s749ms 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: 2025-08-25 13:29:15 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
10 36s444ms 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: 2025-08-25 13:40:57 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
11 36s354ms 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: 2025-08-25 13:23:47 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
12 36s161ms 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: 2025-08-25 13:50:42 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
13 35s944ms 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: 2025-08-25 13:16:37 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
14 35s941ms 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: 2025-08-25 13:45:45 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
15 35s519ms 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: 2025-08-25 13:35:05 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
16 35s434ms 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: 2025-08-25 13:09:20 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
17 35s228ms 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: 2025-08-25 13:25:47 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
18 35s187ms 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: 2025-08-25 13:34:26 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
19 35s163ms 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: 2025-08-25 13:18:01 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
20 34s819ms 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: 2025-08-25 13:11:45 - 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 54m53s 361 139ms 45s629ms 9s123ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Aug 25 13 361 54m53s 9s123ms [ User: postgres - Total duration: 54m53s - Times executed: 361 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 54m53s - Times executed: 361 ]
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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: 2025-08-25 13:01:06 Duration: 45s629ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-08-25 13:56:06 Duration: 39s592ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-08-25 13:00:17 Duration: 38s126ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
2 42m19s 361 401ms 20s572ms 7s33ms with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ), ar as ( select a.*, rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end ), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on sg.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Aug 25 13 361 42m19s 7s33ms [ User: postgres - Total duration: 42m19s - Times executed: 361 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 42m19s - Times executed: 361 ]
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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 ('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 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 ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-08-25 13:45:03 Duration: 20s572ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('700' = 0 OR ar.patternlengthbars <= '700') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-08-25 13:44:46 Duration: 20s11ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('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 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 ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-08-25 13:08:39 Duration: 17s876ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
3 14m51s 328 584ms 8s793ms 2s716ms 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 Aug 25 13 328 14m51s 2s716ms [ User: postgres - Total duration: 14m51s - Times executed: 328 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14m51s - Times executed: 328 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('700' = 0 OR fr.patternlengthbars <= '700') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-08-25 13:44:55 Duration: 8s793ms 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 = '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 ('500' = 0 OR fr.patternlengthbars <= '500') 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: 2025-08-25 13:33:31 Duration: 6s817ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_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 = '529' 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 ('183' = 0 OR coalesce(bim.code, s.symbol) in ('AUDUSD', 'EURUSD', 'GBPUSD', 'USDCAD', 'USDCHF', 'USDJPY', 'XAGAUD', 'XAGEUR', 'XAGUSD', 'XAUAUD', 'XAUCHF', 'XAUEUR', 'XAUGBP', 'XAUJPY', 'XAUUSD', 'XPDUSD', 'XPTUSD', 'AUS200', 'CA60', 'CHINAH', 'CN50', 'EUSTX50', 'FRA40', 'GER40', 'GERTEC30', 'HK50', 'JPN225', 'MidDE50', 'NAS100', 'NETH25', 'NOR25', 'SA40', 'SCI25', 'SPA35', 'SWI20', 'UK100', 'US2000', 'US30', 'US500', 'VIX', 'AUDCAD', 'AUDCHF', 'AUDNZD', 'AUDSGD', 'EURAUD', 'EURCHF', 'EURGBP', 'GBPAUD', 'GBPCHF', 'NZDUSD', 'CHFSGD', 'EURCZK', 'EURHUF', 'EURMXN', 'EURNOK', 'EURPLN', 'EURSEK', 'EURSGD', 'EURTRY', 'EURZAR', 'GBPMXN', 'GBPNOK', 'GBPSEK', 'GBPSGD', 'GBPTRY', 'NOKJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'SEKJPY', 'SGDJPY', 'USDCNH', 'USDCZK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTHB', 'USDTRY', 'USDZAR', 'ZARJPY', 'ADAUSD', 'AVAXUSD', 'BCHUSD', 'BNBUSD', 'BTCUSD', 'Crypto10', 'Crypto20', 'Crypto30', 'DOGEUSD', 'DOTUSD', 'EOSUSD', 'ETHUSD', 'LINKUSD', 'LTCUSD', 'MATICUSD', 'SOLUSD', 'UNIUSD', 'XLMUSD', 'XRPUSD', 'XTZUSD', 'EURX', 'JPYX', 'USDX', 'Gasoline', 'NatGas', 'SpotBrent', 'SpotCrude', 'AAPL.US', 'ABNB.US', 'AMD.US', 'AMZN.US', 'AXP.US', 'BA.US', 'BABA.US', 'BIDU.US', 'BYND.US', 'C.US', 'COIN.US', 'CRM.US', 'DIS.US', 'EA.US', 'GOOG.US', 'GS.US', 'IBM.US', 'JPM.US', 'LMT.US', 'MA.US', 'MCD.US', 'META.US', 'MRNA.US', 'MSFT.US', 'NFLX.US', 'NKE.US', 'NVDA.US', 'ORCL.US', 'PFE.US', 'PG.US', 'PLTR.US', 'PTON.US', 'PYPL.US', 'QCOM.US', 'SNAP.US', 'SPCE.US', 'SPY.US', 'T.US', 'TMUS.US', 'TSLA.US', 'UBER.US', 'V.US', 'WMT.US', 'ZM.US', 'Cattle', 'Cocoa', 'Coffee', 'Corn', 'Cotton', 'LDSugar', 'LeanHogs', 'LondonSugar', 'Lumber', 'OJ', 'Oats', 'RghRice', 'SoyMeal', 'SoyOil', 'Soybeans', 'Sugar', 'Wheat', 'AUDJPY', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURCAD', 'EURJPY', 'EURNZD', 'GBPCAD', 'GBPJPY', 'GBPNZD', 'NZDJPY')) AND ('0' = 0 OR fr.pattern in ('')) AND ('500' = 0 OR fr.patternlengthbars <= '500') 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: 2025-08-25 13:35:25 Duration: 6s115ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
4 1m7s 27,816 0ms 21ms 2ms select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Aug 25 13 27,816 1m7s 2ms [ User: postgres - Total duration: 1m7s - Times executed: 27816 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m7s - Times executed: 27816 ]
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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 = '667' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'USDJPY' OR dss.downloadersymbol = 'USDJPY') AND dss.enabled = 1;
Date: 2025-08-25 13:15:05 Duration: 21ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 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 = 'XPDUSD' OR dss.downloadersymbol = 'XPDUSD') AND dss.enabled = 1;
Date: 2025-08-25 13:30:04 Duration: 21ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT 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 = 'MidDE50' OR dss.downloadersymbol = 'MidDE50') AND dss.enabled = 1;
Date: 2025-08-25 13:45:04 Duration: 20ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
5 58s399ms 197 59ms 1s2ms 296ms with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Aug 25 13 197 58s399ms 296ms [ User: postgres - Total duration: 58s399ms - Times executed: 197 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 58s399ms - Times executed: 197 ]
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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 ('500' = 0 OR ccr.patternlengthbars <= '500') ), 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: 2025-08-25 13:44:13 Duration: 1s2ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_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 ('500' = 0 OR ccr.patternlengthbars <= '500') ), 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: 2025-08-25 13:49:47 Duration: 983ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_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 ('500' = 0 OR ccr.patternlengthbars <= '500') ), 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: 2025-08-25 13:54:52 Duration: 979ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
6 54s240ms 40,616 0ms 29ms 1ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Aug 25 13 40,616 54s240ms 1ms [ User: postgres - Total duration: 54s240ms - Times executed: 40616 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 54s240ms - Times executed: 40616 ]
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '958' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '958' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243162375300';
Date: 2025-08-25 13:49:16 Duration: 29ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '958' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '958' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840248627808300';
Date: 2025-08-25 13:19:27 Duration: 25ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '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 = '515840243238020300';
Date: 2025-08-25 13:15:04 Duration: 22ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
7 49s103ms 136 142ms 864ms 361ms with last_candle as ( select acs.symbolid as symbolid, acs.latestpricedatetime as latest_candle_time, bsl.brokerid as broker_id, coalesce(bim.code, s.symbol) as symbol, bim.code as symbol_mapping, s.exchange as exchange, s.timegranularity as timegranularity from autochartist_symbolupdates acs inner join brokersymbollist bsl on acs.symbolid = bsl.symbolid inner join symbols s on acs.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bsl.brokerid = ? and s.deleted = ? and s.nonliquid = ? and acs.latestpricedatetime is not null ) select * from ( select lc.broker_id as brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / ?) + ? as sast_hh, mod(cast(psp.fromtime as int), ?) as sast_mm, current_timestamp as datetime, (powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice as closingprice, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / ?.?) as low_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / ?.?) as high_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / ?.?) as low_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / ?.?) as high_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / ?.?) as low_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / ?.?) as high_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / ?.?) as low_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / ?.?) as high_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / ?.?) as low_1440, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / ?.?) as high_1440, dtt.absolutetimezoneoffset as datafeedtimezoneoffset, dtt.timezone as datafeedtimezonename, (round((cast(? as float) - rank) / ? * ?)) as rank_rounded, ((cast(? as float) - rank) / ? * ?) as rank from last_candle lc inner join downloadersymbolsettings dss on lc.symbolid = dss.symbolid inner join datafeedstimetable dtt on trim(dss.classname) = trim(dtt.classname) and dtt.dayofweek = ? -- assuming timezone is same for whole week. inner join powerstats_symboldata psd on psd.symbolid = lc.symbolid left outer join powerstats_trumpet psp on psd.trumpetsymbolid = psp.symbolid and psp.dayofweek = extract(dow from lc.latest_candle_time) and psp.fromtime = cast(extract(? from lc.latest_candle_time) as integer) * ? + extract(? from (cast(extract(? from lc.latest_candle_time) as integer) / ?) * ? * interval ?) inner join prfsymboltree prf on psd.symbolid = prf.symbolid and date_trunc(?, prf.enddate) = date_trunc(?, psp.enddate) left join lateral ( select ph.hour, (ave + stddev) as volatility, rank() over (order by (ave + stddev) desc) as rank from powerstats_hourly ph where ph.symbolid = psd.hourlysymbolid and date_trunc(?,ph.enddate) = date_trunc(?, prf.enddate) ) rank_query on true where prf.brokerid = ? and rank_query.hour = floor((psp.fromtime) / ?) and volatility > ? order by rank desc, rank_rounded desc, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Aug 25 13 136 49s103ms 361ms [ User: postgres - Total duration: 49s103ms - Times executed: 136 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 49s103ms - Times executed: 136 ]
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-08-25 13:48:09 Duration: 864ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-08-25 13:48:08 Duration: 857ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-08-25 13:28:06 Duration: 851ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
8 45s996ms 4 11s349ms 11s793ms 11s499ms select updateageforrelevantresults ();Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Aug 25 13 4 45s996ms 11s499ms [ User: postgres - Total duration: 45s996ms - Times executed: 4 ]
[ Application: psql - Total duration: 45s996ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-08-25 13:32:14 Duration: 11s793ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-08-25 13:17:14 Duration: 11s479ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-08-25 13:02:14 Duration: 11s374ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
9 39s151ms 6 5s379ms 7s693ms 6s525ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Aug 25 13 6 39s151ms 6s525ms [ User: postgres - Total duration: 39s151ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 39s151ms - 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: 2025-08-25 13:00:10 Duration: 7s693ms 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: 2025-08-25 13:40:10 Duration: 7s621ms 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: 2025-08-25 13:30:09 Duration: 6s966ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
10 33s815ms 16 1s896ms 3s284ms 2s113ms 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 Aug 25 13 16 33s815ms 2s113ms [ User: postgres - Total duration: 33s815ms - Times executed: 16 ]
[ Application: psql - Total duration: 33s815ms - 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: 2025-08-25 13:35:16 Duration: 3s284ms 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: 2025-08-25 13:26:16 Duration: 3s225ms 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: 2025-08-25 13:01:15 Duration: 2s23ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 24s687ms 8 2s747ms 4s177ms 3s85ms select updateresultsmaterializedview ();Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Aug 25 13 8 24s687ms 3s85ms [ User: postgres - Total duration: 24s687ms - Times executed: 8 ]
[ Application: psql - Total duration: 24s687ms - Times executed: 8 ]
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select updateresultsmaterializedview ();
Date: 2025-08-25 13:35:37 Duration: 4s177ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-08-25 13:32:17 Duration: 3s137ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-08-25 13:17:17 Duration: 3s57ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
12 20s751ms 12 1s324ms 2s274ms 1s729ms 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 Aug 25 13 12 20s751ms 1s729ms [ User: postgres - Total duration: 20s751ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 20s751ms - Times executed: 12 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '692' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '692' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '692' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-08-25 13:37:16 Duration: 2s274ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '617' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '617' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '617' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-08-25 13:36:55 Duration: 2s204ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '620' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '620' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '620' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-08-25 13:36:50 Duration: 2s169ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
13 16s941ms 16 722ms 1s515ms 1s58ms update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Aug 25 13 16 16s941ms 1s58ms [ User: postgres - Total duration: 16s941ms - Times executed: 16 ]
[ Application: psql - Total duration: 16s941ms - 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: 2025-08-25 13:26:13 Duration: 1s515ms 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: 2025-08-25 13:48:13 Duration: 1s358ms 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: 2025-08-25 13:35:13 Duration: 1s265ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
14 16s202ms 13 53ms 7s161ms 1s246ms copy ( select array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ?) as broker_ids, string_to_array(coalesce(replace(broker_symbol_mappings, ?, ?), ?), ?) as broker_symbol_mappings, replace(exchange, ?, ?) as exchange, symbol_id, replace(symbol, ?, ?) as symbol, replace(short_name, ?, ?) as short_name, replace(long_name, ?, ?) as long_name, interval, replace(timezone, ?, ?) as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ?) as search_groups, string_to_array(pattern_basegroupnames, ?) as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results (?::character varying, current_timestamp::timestamp without time zone)) t) to ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Aug 25 13 13 16s202ms 1s246ms [ User: postgres - Total duration: 16s202ms - Times executed: 13 ]
[ Application: psql - Total duration: 16s202ms - Times executed: 13 ]
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COPY ( select /*_solr_fetch_results__*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_acaweb_fx.json';
Date: 2025-08-25 13:33:09 Duration: 7s161ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results__*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_acaweb_fx.json';
Date: 2025-08-25 13:18:06 Duration: 4s143ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results__*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_acaweb_fx.json';
Date: 2025-08-25 13:48:05 Duration: 2s301ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
15 10s658ms 1,938 5ms 10ms 5ms select * from status_perbroker;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Aug 25 13 1,938 10s658ms 5ms [ User: postgres - Total duration: 10s658ms - Times executed: 1938 ]
[ Application: [unknown] - Total duration: 10s658ms - Times executed: 1938 ]
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select * from status_perbroker;
Date: 2025-08-25 13:31:25 Duration: 10ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
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select * from status_perbroker;
Date: 2025-08-25 13:31:28 Duration: 10ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
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select * from status_perbroker;
Date: 2025-08-25 13:31:28 Duration: 10ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
16 10s72ms 34 12ms 3s414ms 296ms select fixcandlegaps (?, false);Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Aug 25 13 34 10s72ms 296ms [ User: postgres - Total duration: 10s72ms - Times executed: 34 ]
[ Application: psql - Total duration: 10s72ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-08-25 13:06:11 Duration: 3s414ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-08-25 13:06:03 Duration: 1s199ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('PEPPERSTONE', false);
Date: 2025-08-25 13:06:06 Duration: 1s30ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
17 8s179ms 7,390 0ms 4ms 1ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Aug 25 13 7,390 8s179ms 1ms [ User: postgres - Total duration: 8s179ms - Times executed: 7390 ]
[ Application: [unknown] - Total duration: 8s179ms - Times executed: 7390 ]
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INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 81, schedule: 10 15 * * 6 Africa/Johannesburg', NULL, NULL);
Date: 2025-08-25 13:22:49 Duration: 4ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
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INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 121, schedule: 0 15 * * 6 Africa/Johannesburg', NULL, NULL);
Date: 2025-08-25 13:35:51 Duration: 3ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
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INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'running 138', NULL, NULL);
Date: 2025-08-25 13:00:52 Duration: 2ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
18 7s641ms 192 16ms 164ms 39ms 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 Aug 25 13 192 7s641ms 39ms [ User: postgres - Total duration: 7s641ms - Times executed: 192 ]
[ Application: [unknown] - Total duration: 7s641ms - Times executed: 192 ]
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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: 2025-08-25 13:32:04 Duration: 164ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-08-25 13:45:55 Duration: 158ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-08-25 13:45:04 Duration: 155ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
19 7s292ms 6,010 0ms 16ms 1ms insert into t15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Aug 25 13 6,010 7s292ms 1ms [ User: postgres - Total duration: 7s292ms - Times executed: 6010 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 7s292ms - Times executed: 6010 ]
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-08-25 14:30:00', '1.6169', '1.61723', '1.616655', '1.616755', '773', '515840230465070300', '0', '2025-08-25 13:45:04.578', '2025-08-25 13:45:04.531') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '1.6169', high = '1.61723', low = '1.616655', close = '1.616755', volume = '773', bsf = '0', sastdatetimewritten = '2025-08-25 13:45:04.579', sastdatetimereceived = '2025-08-25 13:45:04.531';
Date: 2025-08-25 13:45:04 Duration: 16ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-08-25 14:00:00', '7.15915', '7.15949', '7.15882', '7.15917', '1230', '515840243215255300', '0', '2025-08-25 13:15:38.779', '2025-08-25 13:15:38.351') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '7.15915', high = '7.15949', low = '7.15882', close = '7.15917', volume = '1230', bsf = '0', sastdatetimewritten = '2025-08-25 13:15:38.779', sastdatetimereceived = '2025-08-25 13:15:38.351';
Date: 2025-08-25 13:15:38 Duration: 16ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-08-25 14:15:00', '20.99395', '20.99465', '20.98715', '20.9892', '694', '605679104092484300', '0', '2025-08-25 13:30:04.47', '2025-08-25 13:30:04.425') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '20.99395', high = '20.99465', low = '20.98715', close = '20.9892', volume = '694', bsf = '0', sastdatetimewritten = '2025-08-25 13:30:04.47', sastdatetimereceived = '2025-08-25 13:30:04.425';
Date: 2025-08-25 13:30:04 Duration: 15ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
20 6s976ms 6 1s34ms 1s643ms 1s162ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Aug 25 13 6 6s976ms 1s162ms [ User: postgres - Total duration: 6s976ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 6s976ms - Times executed: 6 ]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-08-25 13:49:18 Duration: 1s643ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-08-25 13:01:17 Duration: 1s117ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-08-25 13:16:17 Duration: 1s92ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 59,268 244ms 0ms 0ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Aug 25 13 59,267 244ms 0ms 14 1 0ms 0ms [ User: postgres - Total duration: 244ms - Times executed: 59268 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 232ms - Times executed: 58953 ]
[ Application: [unknown] - Total duration: 12ms - Times executed: 315 ]
-
select 1;
Date: 2025-08-25 13:49:17 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT 1;
Date: 2025-08-25 13:48:19 Duration: 0ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
select 1;
Date: 2025-08-25 13:59:08 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
2 40,616 54s240ms 0ms 29ms 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 Aug 25 13 40,616 54s240ms 1ms [ User: postgres - Total duration: 54s240ms - Times executed: 40616 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 54s240ms - Times executed: 40616 ]
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '958' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '958' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243162375300';
Date: 2025-08-25 13:49:16 Duration: 29ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '958' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '958' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840248627808300';
Date: 2025-08-25 13:19:27 Duration: 25ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '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 = '515840243238020300';
Date: 2025-08-25 13:15:04 Duration: 22ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
3 27,816 1m7s 0ms 21ms 2ms select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Aug 25 13 27,816 1m7s 2ms [ User: postgres - Total duration: 1m7s - Times executed: 27816 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m7s - Times executed: 27816 ]
-
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 = '667' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'USDJPY' OR dss.downloadersymbol = 'USDJPY') AND dss.enabled = 1;
Date: 2025-08-25 13:15:05 Duration: 21ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 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 = 'XPDUSD' OR dss.downloadersymbol = 'XPDUSD') AND dss.enabled = 1;
Date: 2025-08-25 13:30:04 Duration: 21ms 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 = 'MidDE50' OR dss.downloadersymbol = 'MidDE50') AND dss.enabled = 1;
Date: 2025-08-25 13:45:04 Duration: 20ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
4 7,390 8s179ms 0ms 4ms 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 Aug 25 13 7,390 8s179ms 1ms [ User: postgres - Total duration: 8s179ms - Times executed: 7390 ]
[ Application: [unknown] - Total duration: 8s179ms - Times executed: 7390 ]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 81, schedule: 10 15 * * 6 Africa/Johannesburg', NULL, NULL);
Date: 2025-08-25 13:22:49 Duration: 4ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 121, schedule: 0 15 * * 6 Africa/Johannesburg', NULL, NULL);
Date: 2025-08-25 13:35:51 Duration: 3ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'running 138', NULL, NULL);
Date: 2025-08-25 13:00:52 Duration: 2ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
5 6,010 7s292ms 0ms 16ms 1ms insert into t15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Aug 25 13 6,010 7s292ms 1ms [ User: postgres - Total duration: 7s292ms - Times executed: 6010 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 7s292ms - Times executed: 6010 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-08-25 14:30:00', '1.6169', '1.61723', '1.616655', '1.616755', '773', '515840230465070300', '0', '2025-08-25 13:45:04.578', '2025-08-25 13:45:04.531') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '1.6169', high = '1.61723', low = '1.616655', close = '1.616755', volume = '773', bsf = '0', sastdatetimewritten = '2025-08-25 13:45:04.579', sastdatetimereceived = '2025-08-25 13:45:04.531';
Date: 2025-08-25 13:45:04 Duration: 16ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-08-25 14:00:00', '7.15915', '7.15949', '7.15882', '7.15917', '1230', '515840243215255300', '0', '2025-08-25 13:15:38.779', '2025-08-25 13:15:38.351') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '7.15915', high = '7.15949', low = '7.15882', close = '7.15917', volume = '1230', bsf = '0', sastdatetimewritten = '2025-08-25 13:15:38.779', sastdatetimereceived = '2025-08-25 13:15:38.351';
Date: 2025-08-25 13:15:38 Duration: 16ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-08-25 14:15:00', '20.99395', '20.99465', '20.98715', '20.9892', '694', '605679104092484300', '0', '2025-08-25 13:30:04.47', '2025-08-25 13:30:04.425') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '20.99395', high = '20.99465', low = '20.98715', close = '20.9892', volume = '694', bsf = '0', sastdatetimewritten = '2025-08-25 13:30:04.47', sastdatetimereceived = '2025-08-25 13:30:04.425';
Date: 2025-08-25 13:30:04 Duration: 15ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
6 5,502 6s868ms 0ms 11ms 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 #6
Day Hour Count Duration Avg duration Aug 25 13 5,502 6s868ms 1ms [ User: postgres - Total duration: 6s868ms - Times executed: 5502 ]
[ Application: [unknown] - Total duration: 6s868ms - Times executed: 5502 ]
-
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 ('5158402459147563000.1419|45884.4167|45891.7083|45870.7083|45890.5833|15333.9|15446.5|14056.5|15157.2', 515840245914756300, 8.000000000000000000000000000000, 'Rising Wedge', 4, '2025-08-25 10:56:18'::timestamp without time zone, - 1, 0.445343572718566838000000000000, 0.141944408742541938700000000000, 0.123026204419759324600000000000, 0.000000000000000000000000000000, 0.778523285386672481200000000000, 14393.273806318593420000000000000000, 14922.139085966080530000000000000000, '2025-08-25 12:00:00'::timestamp without time zone, '2025-09-06 09:30:00'::timestamp without time zone, '2025-07-24 13:00:00'::timestamp without time zone, '2025-08-25 12:00:00'::timestamp without time zone, 14320.000000000000000000000000000000, 15302.988079470198500000000000000000, '2025-08-15 10:00:00'::timestamp without time zone, '2025-08-22 17:00:00'::timestamp without time zone, '2025-08-01 17:00:00'::timestamp without time zone, '2025-08-21 14:00:00'::timestamp without time zone, 15333.899999999999640000000000000000, 15446.500000000000000000000000000000, 14056.500000000000000000000000000000, 15157.200000000000730000000000000000, 7.289403973509938517000000000000, 1.816129032258070319000000000000, 2.447697697856673571000000000000, 0.591452816711945272800000000000, 'Continuation', 2.911920529801136581000000000000, '2025-08-25 12:00:00'::timestamp without time zone, 15299.899999999999640000000000000000, 171, 0, 290.566666666666321800000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-08-25 13:01:20 Duration: 11ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('5158402495426573000.1921|45891.4271|45891.6562|45891.5|45894.1875|151.1|149.82|149.09|149.43', 515840249542657300, 2.000000000000000000000000000000, 'Triangle', 4, '2025-08-25 10:56:11'::timestamp without time zone, 1, 0.561343602909711636400000000000, 0.192089938531202625300000000000, 0.603688716730177210600000000000, 0.396533652030857219900000000000, 0.017094457977512415160000000000, 150.025216079781131400000000000000, 150.508518591474711500000000000000, '2025-08-25 06:00:00'::timestamp without time zone, '2025-08-26 15:52:30'::timestamp without time zone, '2025-08-21 15:30:00'::timestamp without time zone, '2025-08-25 06:00:00'::timestamp without time zone, 148.610000000000013600000000000000, 149.645454545454555300000000000000, '2025-08-22 10:15:00'::timestamp without time zone, '2025-08-22 15:45:00'::timestamp without time zone, '2025-08-22 12:00:00'::timestamp without time zone, '2025-08-25 04:30:00'::timestamp without time zone, 151.099999999999994300000000000000, 149.819999999999993200000000000000, 149.090000000000003400000000000000, 149.430000000000006800000000000000, 0.020000000000000201640000000000, - 0.058181818181818230340000000000, 1.523225967172111117000000000000, 0.343498586846892384200000000000, 'Continuation', 0.034545454545451548260000000000, '2025-08-25 06:00:00'::timestamp without time zone, 149.680000000000006800000000000000, 25, 0, 0.521666666666661171800000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-08-25 13:01:13 Duration: 11ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('5158402495354313000.9745|45891.4271|45891.6667|45890.7708|45891.6562|201.8|201.37|196|200.955', 515840249535431300, 2.000000000000000000000000000000, 'Triangle', 4, '2025-08-25 11:11:34'::timestamp without time zone, - 1, 0.185065576737291848100000000000, 0.974538080216382995900000000000, 1.000000000000000000000000000000, 0.763193715591514831800000000000, 0.539233425466863813800000000000, 197.631980541717496200000000000000, 199.596658559048961500000000000000, '2025-08-22 18:15:00'::timestamp without time zone, '2025-08-23 06:07:30'::timestamp without time zone, '2025-08-21 12:30:00'::timestamp without time zone, '2025-08-22 18:15:00'::timestamp without time zone, 196.814999999999997700000000000000, 201.308928571428595000000000000000, '2025-08-22 10:15:00'::timestamp without time zone, '2025-08-22 16:00:00'::timestamp without time zone, '2025-08-21 18:30:00'::timestamp without time zone, '2025-08-22 15:45:00'::timestamp without time zone, 201.800000000000011400000000000000, 201.370000000000004600000000000000, 196.000000000000000000000000000000, 200.955000000000012500000000000000, 0.176964285714286157000000000000, - 0.018695652173913338700000000000, 1.937649694692413105000000000000, 0.483910841707255956500000000000, 'Continuation', - 0.308928571428594978000000000000, '2025-08-22 18:15:00'::timestamp without time zone, 201.000000000000000000000000000000, 30, 0, 1.176666666666666972000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-08-25 13:16:36 Duration: 11ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
7 3,801 36ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Aug 25 13 3,801 36ms 0ms [ User: postgres - Total duration: 36ms - Times executed: 3801 ]
[ Application: [unknown] - Total duration: 36ms - Times executed: 3801 ]
-
SET extra_float_digits = 3;
Date: 2025-08-25 13:07:12 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2025-08-25 13:06:34 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2025-08-25 13:54:52 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: [unknown] Bind query: yes
8 3,776 51ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Aug 25 13 3,776 51ms 0ms [ User: postgres - Total duration: 51ms - Times executed: 3776 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 51ms - Times executed: 3776 ]
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-08-25 13:57:34 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-08-25 13:55:15 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-08-25 13:50:58 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
9 3,456 4s443ms 0ms 49ms 1ms with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ) select a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, s.exchange, s.symbol, s.longname, s.shortname, breakout, dtt.timezone, patternstartprice, patternendprice, qtytp, newlevels.profit, newlevels.stop, newlevels.filtered, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern inner join rar_max rm on ? = ? left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid left join lateral calc_cp_signal (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Aug 25 13 3,456 4s443ms 1ms [ User: postgres - Total duration: 4s443ms - Times executed: 3456 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 4s427ms - Times executed: 3422 ]
[ Application: [unknown] - Total duration: 15ms - Times executed: 34 ]
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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 = '606694542424101301' 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 = '606694542424101301' OR a.resultuid = '606694542424101301') AND dtt.dayofweek = 3;
Date: 2025-08-25 13:57:45 Duration: 49ms 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 = '606682284542831301' 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 = '606682284542831301' OR a.resultuid = '606682284542831301') AND dtt.dayofweek = 3;
Date: 2025-08-25 13:49:16 Duration: 24ms 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 = '606682284309376301' 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 = '606682284309376301' OR a.resultuid = '606682284309376301') AND dtt.dayofweek = 3;
Date: 2025-08-25 13:19:27 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
10 3,427 2s31ms 0ms 7ms 0ms insert into t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Aug 25 13 3,427 2s31ms 0ms [ User: postgres - Total duration: 2s31ms - Times executed: 3427 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s31ms - Times executed: 3427 ]
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-08-25 13:30:00', '1.34837', '1.34903', '1.34837', '1.34899', '1489', '515840247884826300', '0', '2025-08-25 13:00:50.978', '2025-08-25 13:00:50.879') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '1.34837', high = '1.34903', low = '1.34837', close = '1.34899', volume = '1489', bsf = '0', sastdatetimewritten = '2025-08-25 13:00:50.978', sastdatetimereceived = '2025-08-25 13:00:50.879';
Date: 2025-08-25 13:00:51 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-08-25 13:30:00', '109.08', '109.18', '108.52', '108.85', '2211', '515840247891126300', '0', '2025-08-25 13:00:52.909', '2025-08-25 13:00:52.827') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '109.08', high = '109.18', low = '108.52', close = '108.85', volume = '2211', bsf = '0', sastdatetimewritten = '2025-08-25 13:00:52.909', sastdatetimereceived = '2025-08-25 13:00:52.827';
Date: 2025-08-25 13:00:52 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-08-25 13:30:00', '6.38093', '6.38153', '6.37981', '6.38024', '179', '515840247894362300', '0', '2025-08-25 13:00:56.917', '2025-08-25 13:00:56.836') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '6.38093', high = '6.38153', low = '6.37981', close = '6.38024', volume = '179', bsf = '0', sastdatetimewritten = '2025-08-25 13:00:56.917', sastdatetimereceived = '2025-08-25 13:00:56.836';
Date: 2025-08-25 13:00:56 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
11 3,070 1s852ms 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 #11
Day Hour Count Duration Avg duration Aug 25 13 3,070 1s852ms 0ms [ User: postgres - Total duration: 1s852ms - Times executed: 3070 ]
[ Application: [unknown] - Total duration: 1s852ms - Times executed: 3070 ]
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INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (3.000000000000000000000000000000, 'ABCD', '2025-08-25 11:40:23'::timestamp without time zone, - 1, '2025-07-18 00:00:00'::timestamp without time zone, '2025-08-22 00:00:00'::timestamp without time zone, 17.019999999999999570000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 15.919999999999999930000000000000, '2025-08-05 00:00:00'::timestamp without time zone, 17.050000000000000710000000000000, '2025-08-12 00:00:00'::timestamp without time zone, 16.199999999999999290000000000000, '2025-08-18 00:00:00'::timestamp without time zone, 17.329999999999998300000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.617021276595744905200000000000, - 1.000000000000000000000000000000, 6.134221888600963624000000000000, 14, 16.199999999999999290000000000000, 16.631621592768997430000000000000, 15.501621592769000200000000000000, 16.441648943085997560000000000000, 15.892617796065000140000000000000, 16.765000000000000570000000000000, 16.898378407231000150000000000000, 515840221502785300, 0.765957446808510189500000000000, 'BC=0.786*AB (0.752) ', 0, 'ABCD|-1|2025-07-18 00:00:00|17.02|-1|4|14|BC=0.786*AB (0.752)|0|515840221502785300|1899-12-29 00:00:00|2025-08-05 00:00:00|2025-08-12 00:00:00|2025-08-18 00:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-08-25 13:45:26 Duration: 10ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (3.000000000000000000000000000000, 'ABCD', '2025-08-25 11:40:23'::timestamp without time zone, - 1, '2025-07-18 00:00:00'::timestamp without time zone, '2025-08-22 00:00:00'::timestamp without time zone, 17.019999999999999570000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 15.919999999999999930000000000000, '2025-08-05 00:00:00'::timestamp without time zone, 17.050000000000000710000000000000, '2025-08-12 00:00:00'::timestamp without time zone, 16.199999999999999290000000000000, '2025-08-18 00:00:00'::timestamp without time zone, 17.329999999999998300000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.617021276595744905200000000000, - 1.000000000000000000000000000000, 6.134221888600963624000000000000, 14, 16.199999999999999290000000000000, 16.631621592768997430000000000000, 15.501621592769000200000000000000, 16.441648943085997560000000000000, 15.892617796065000140000000000000, 16.765000000000000570000000000000, 16.898378407231000150000000000000, 515840221502785300, 0.765957446808510189500000000000, 'BC=0.786*AB (0.752) ', 0, 'ABCD|-1|2025-07-18 00:00:00|17.02|-1|4|14|BC=0.786*AB (0.752)|0|515840221502785300|1899-12-29 00:00:00|2025-08-05 00:00:00|2025-08-12 00:00:00|2025-08-18 00:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-08-25 13:45:26 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 (3.000000000000000000000000000000, 'ABCD', '2025-08-25 11:10:40'::timestamp without time zone, 1, '2025-08-18 09:00:00'::timestamp without time zone, '2025-08-25 06:00:00'::timestamp without time zone, 228.330000000000012500000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 231.719999999999998900000000000000, '2025-08-18 15:00:00'::timestamp without time zone, 220.500000000000000000000000000000, '2025-08-21 13:00:00'::timestamp without time zone, 229.000000000000000000000000000000, '2025-08-22 15:00:00'::timestamp without time zone, 217.780000000000001100000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.922351532076245206300000000000, - 1.000000000000000000000000000000, 64.200946706636912610000000000000, 82, 229.000000000000000000000000000000, 224.714341353213996000000000000000, 235.934341353213994800000000000000, 226.600618458915988600000000000000, 232.052060467389992500000000000000, 223.389999999999986400000000000000, 222.065658646786005200000000000000, 515840249513174300, 0.155296935847509587400000000000, 'BC=0.786*AB (0.758) ', 0, 'ABCD|1|2025-08-18 09:00:00|228.33|-1|4|82|BC=0.786*AB (0.758)|0|515840249513174300|1899-12-29 00:00:00|2025-08-18 15:00:00|2025-08-21 13:00:00|2025-08-22 15:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-08-25 13:15:42 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
12 2,508 147ms 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Aug 25 13 2,508 147ms 0ms [ User: postgres - Total duration: 147ms - Times executed: 2508 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 147ms - Times executed: 2508 ]
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select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = '601729875360207307' and category = lower('hourofday') union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = '601729875360207307' and category = lower('hourofday') order by correct desc) as summdata group by category, name having sum(total) > 0 ORDER BY name;
Date: 2025-08-25 13:58:52 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = '515852059309933307' and category = lower('hourofday') union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = '515852059309933307' and category = lower('hourofday') order by correct desc) as summdata group by category, name having sum(total) > 0 ORDER BY name;
Date: 2025-08-25 13:58:50 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = '515852059324253307' and category = lower('initialtrend') union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = '515852059324253307' and category = lower('initialtrend') order by correct desc) as summdata group by category, name having sum(total) > 0 ORDER BY name;
Date: 2025-08-25 13:58:48 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
13 2,222 1s198ms 0ms 8ms 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Aug 25 13 2,222 1s198ms 0ms [ User: postgres - Total duration: 1s198ms - Times executed: 2222 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s198ms - Times executed: 2222 ]
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-08-25 13:00:00', '34.9', '35.05', '34.9', '34.9', '124', '515840247893649300', '0', '2025-08-25 13:01:03.169', '2025-08-25 13:01:03.1') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '34.9', high = '35.05', low = '34.9', close = '34.9', volume = '124', bsf = '0', sastdatetimewritten = '2025-08-25 13:01:03.169', sastdatetimereceived = '2025-08-25 13:01:03.1';
Date: 2025-08-25 13:01:03 Duration: 8ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-08-25 13:00:00', '3938.25', '3938.25', '3859.35', '3882.79', '13989', '515840247911908300', '0', '2025-08-25 13:00:42.713', '2025-08-25 13:00:42.591') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '3938.25', high = '3938.25', low = '3859.35', close = '3882.79', volume = '13989', bsf = '0', sastdatetimewritten = '2025-08-25 13:00:42.713', sastdatetimereceived = '2025-08-25 13:00:42.591';
Date: 2025-08-25 13:00:42 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-08-25 13:00:00', '1.34943', '1.34958', '1.3483', '1.34899', '2792', '515840247885064300', '0', '2025-08-25 13:00:50.855', '2025-08-25 13:00:50.68') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '1.34943', high = '1.34958', low = '1.3483', close = '1.34899', volume = '2792', bsf = '0', sastdatetimewritten = '2025-08-25 13:00:50.855', sastdatetimereceived = '2025-08-25 13:00:50.68';
Date: 2025-08-25 13:00:50 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: PostgreSQL JDBC Driver Bind query: yes
14 1,972 1s238ms 0ms 17ms 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 #14
Day Hour Count Duration Avg duration Aug 25 13 1,972 1s238ms 0ms [ User: postgres - Total duration: 1s238ms - Times executed: 1972 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s238ms - Times executed: 1972 ]
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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 = '606683249256303303' 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 = '606683249256303303' OR a.resultuid = '606683249256303303') AND dtt.dayofweek = 3;
Date: 2025-08-25 13:57:45 Duration: 17ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '606696907419512303' 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 = '606696907419512303' OR a.resultuid = '606696907419512303') AND dtt.dayofweek = 3;
Date: 2025-08-25 13:54:52 Duration: 12ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '606682277940060303' 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 = '606682277940060303' OR a.resultuid = '606682277940060303') AND dtt.dayofweek = 3;
Date: 2025-08-25 13:48:10 Duration: 11ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
15 1,938 10s658ms 5ms 10ms 5ms select * from status_perbroker;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Aug 25 13 1,938 10s658ms 5ms [ User: postgres - Total duration: 10s658ms - Times executed: 1938 ]
[ Application: [unknown] - Total duration: 10s658ms - Times executed: 1938 ]
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select * from status_perbroker;
Date: 2025-08-25 13:31:25 Duration: 10ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
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select * from status_perbroker;
Date: 2025-08-25 13:31:28 Duration: 10ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
-
select * from status_perbroker;
Date: 2025-08-25 13:31:28 Duration: 10ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
16 1,699 2s897ms 0ms 9ms 1ms insert into keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errormargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestprice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) values (?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?, ?, ?.?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?.?, ?::timestamp without time zone, ?, ?.?, ?.?, ?, ?, ?.?, ?.?, ?::timestamp without time zone, ?, ?, ?.?, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Aug 25 13 1,699 2s897ms 1ms [ User: postgres - Total duration: 2s897ms - Times executed: 1699 ]
[ Application: [unknown] - Total duration: 2s897ms - Times executed: 1699 ]
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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 (2.000000000000000000000000000000, - 1, 2, '2025-08-25 10:55:43'::timestamp without time zone, '2025-08-25 13:00:00', 0.004885000000000052494000000000, 3, 105, 1.163859999999999895000000000000, '2025-08-21 03:00:00', '2025-08-19 21:00:00', '2025-08-19 04:00:00', '', '', '', '', '', '', '', 94, 1.163515499999999925000000000000, '2025-08-25 13:00:00'::timestamp without time zone, '2025-08-25 13:00:00', 1.168709999999999916000000000000, 0.000344500000000003007000000000, - 1, 500991628217369200, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|500991628217369200|1.16386|2|2025-08-25 13:00:00|2025-08-25 13:00:00|-1|-1', 1.170601299999999956000000000000, 0.006741300000000061132000000000, 2, '2025-08-19 04:00:00', 1.171999999999999931000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-08-25 13:00:45 Duration: 9ms 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 (5.000000000000000000000000000000, - 1, 1, '2025-08-25 11:40:36'::timestamp without time zone, '', 0.500000000000000000000000000000, 5, 95, 70.265000000000000570000000000000, '2025-08-22 17:30:00', '2025-08-22 14:30:00', '2025-08-19 18:00:00', '2025-08-19 15:00:00', '2025-08-19 13:00:00', '', '', '', '', '', 284, 70.341250000000002280000000000000, '2025-08-25 07:00:00'::timestamp without time zone, '2025-08-25 07:00:00', 0.000000000000000000000000000000, 0.109499999999999889100000000000, - 1, 515840249537406300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249537406300|70.265|1|2025-08-25 07:00:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-08-19 13:00:00', 71.704999999999998300000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-08-25 13:45:38 Duration: 8ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (10.000000000000000000000000000000, - 1, 2, '2025-08-25 11:40:36'::timestamp without time zone, '2025-08-25 14:30:00', 0.001665000000000020196000000000, 4, 386, 0.863774999999999959500000000000, '2025-08-22 16:45:00', '2025-08-19 20:45:00', '2025-08-19 15:00:00', '2025-08-19 13:00:00', '', '', '', '', '', '', 757, 0.863493500000000024900000000000, '2025-08-25 14:30:00'::timestamp without time zone, '2025-08-25 14:30:00', 0.865310000000000023600000000000, 0.000281500000000000987700000000, - 1, 515840230409512300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840230409512300|0.863775|2|2025-08-25 14:30:00|2025-08-25 14:30:00|-1|-1', 0.866072700000000028600000000000, 0.002297700000000069132000000000, 2, '2025-08-19 13:00:00', 0.866949999999999998400000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-08-25 13:45:38 Duration: 8ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
17 1,682 1s67ms 0ms 5ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Aug 25 13 1,682 1s67ms 0ms [ User: postgres - Total duration: 1s67ms - Times executed: 1682 ]
[ Application: [unknown] - Total duration: 1s67ms - Times executed: 1682 ]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-08-22 00:00:00', reason = 'Emerging pattern formed a completed pattern.' WHERE uniqueIndex = '515840249518179300-1|45831|45870|45839|45880|118.25|113.52|107.15|105.525' and relevant = 1;
Date: 2025-08-25 13:16:34 Duration: 5ms 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 = '2025-08-25 14:00:00', reason = 'Price has moved too far in the wrong direction' WHERE uniqueIndex = '|515840230538986300|86.2585|2|2025-08-25 12:00:00|2025-08-25 12:00:00|-1|-1' and relevant = 1;
Date: 2025-08-25 13:30:46 Duration: 4ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-08-25 14:15:00', reason = 'Emerging pattern broke out in the wrong direction.' WHERE uniqueIndex = '515840243213706300-1|45891.6667|45894.4688|45894|45894.5312|115.404|114.933|114.337|114.78' and relevant = 1;
Date: 2025-08-25 13:32:03 Duration: 3ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
18 1,483 15ms 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 Aug 25 13 1,483 15ms 0ms [ User: postgres - Total duration: 15ms - Times executed: 1483 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 15ms - Times executed: 1483 ]
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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: 2025-08-25 13:14:52 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.21 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: 2025-08-25 13:14:42 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.21 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: 2025-08-25 13:15:52 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.21 Application: PostgreSQL JDBC Driver Bind query: yes
19 1,368 48ms 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Aug 25 13 1,368 48ms 0ms [ User: postgres - Total duration: 48ms - Times executed: 1368 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 48ms - Times executed: 1368 ]
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select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = '515852059324736307' and category = lower('hourofday') order by correct desc) as summdata group by category, name having sum(total) > 0 order by name;
Date: 2025-08-25 13:58:48 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = '601729875360207307' and category = lower('hourofday') order by correct desc) as summdata group by category, name having sum(total) > 0 order by name;
Date: 2025-08-25 13:58:49 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * 100.0 as percentage, min("from") as "from", max("to") as "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = '601729875360207307' and category = lower('hourofday') order by correct desc) as summdata group by category, name having sum(total) > 0 order by name;
Date: 2025-08-25 13:09:32 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.11 Application: PostgreSQL JDBC Driver Bind query: yes
20 884 294ms 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 #20
Day Hour Count Duration Avg duration Aug 25 13 884 294ms 0ms [ User: postgres - Total duration: 294ms - Times executed: 884 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 294ms - Times executed: 884 ]
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SELECT CASE WHEN a.old_resultuid = '606696666079815301' 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 = '606696666079815301' OR a.resultuid = '606696666079815301') AND dtt.dayofweek = 3;
Date: 2025-08-25 13:40:00 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '606697853546455301' 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 = '606697853546455301' OR a.resultuid = '606697853546455301') AND dtt.dayofweek = 3;
Date: 2025-08-25 13:34:09 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '606697967287723301' 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 = '606697967287723301' OR a.resultuid = '606697967287723301') AND dtt.dayofweek = 3;
Date: 2025-08-25 13:54:22 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 11s349ms 11s793ms 11s499ms 4 45s996ms select updateageforrelevantresults ();Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Aug 25 13 4 45s996ms 11s499ms [ User: postgres - Total duration: 45s996ms - Times executed: 4 ]
[ Application: psql - Total duration: 45s996ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-08-25 13:32:14 Duration: 11s793ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-08-25 13:17:14 Duration: 11s479ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-08-25 13:02:14 Duration: 11s374ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
2 139ms 45s629ms 9s123ms 361 54m53s 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 Aug 25 13 361 54m53s 9s123ms [ User: postgres - Total duration: 54m53s - Times executed: 361 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 54m53s - Times executed: 361 ]
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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: 2025-08-25 13:01:06 Duration: 45s629ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-08-25 13:56:06 Duration: 39s592ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-08-25 13:00:17 Duration: 38s126ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
3 401ms 20s572ms 7s33ms 361 42m19s with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ), ar as ( select a.*, rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end ), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on sg.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Aug 25 13 361 42m19s 7s33ms [ User: postgres - Total duration: 42m19s - Times executed: 361 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 42m19s - Times executed: 361 ]
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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 ('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 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 ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-08-25 13:45:03 Duration: 20s572ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('700' = 0 OR ar.patternlengthbars <= '700') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-08-25 13:44:46 Duration: 20s11ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('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 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 ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-08-25 13:08:39 Duration: 17s876ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
4 5s379ms 7s693ms 6s525ms 6 39s151ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Aug 25 13 6 39s151ms 6s525ms [ User: postgres - Total duration: 39s151ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 39s151ms - 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: 2025-08-25 13:00:10 Duration: 7s693ms 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: 2025-08-25 13:40:10 Duration: 7s621ms 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: 2025-08-25 13:30:09 Duration: 6s966ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
5 2s747ms 4s177ms 3s85ms 8 24s687ms select updateresultsmaterializedview ();Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Aug 25 13 8 24s687ms 3s85ms [ User: postgres - Total duration: 24s687ms - Times executed: 8 ]
[ Application: psql - Total duration: 24s687ms - Times executed: 8 ]
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select updateresultsmaterializedview ();
Date: 2025-08-25 13:35:37 Duration: 4s177ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-08-25 13:32:17 Duration: 3s137ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2025-08-25 13:17:17 Duration: 3s57ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
6 584ms 8s793ms 2s716ms 328 14m51s with rar_max as ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ? ), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end ), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp))) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Aug 25 13 328 14m51s 2s716ms [ User: postgres - Total duration: 14m51s - Times executed: 328 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14m51s - Times executed: 328 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('700' = 0 OR fr.patternlengthbars <= '700') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-08-25 13:44:55 Duration: 8s793ms 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 = '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 ('500' = 0 OR fr.patternlengthbars <= '500') 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: 2025-08-25 13:33:31 Duration: 6s817ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_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 = '529' 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 ('183' = 0 OR coalesce(bim.code, s.symbol) in ('AUDUSD', 'EURUSD', 'GBPUSD', 'USDCAD', 'USDCHF', 'USDJPY', 'XAGAUD', 'XAGEUR', 'XAGUSD', 'XAUAUD', 'XAUCHF', 'XAUEUR', 'XAUGBP', 'XAUJPY', 'XAUUSD', 'XPDUSD', 'XPTUSD', 'AUS200', 'CA60', 'CHINAH', 'CN50', 'EUSTX50', 'FRA40', 'GER40', 'GERTEC30', 'HK50', 'JPN225', 'MidDE50', 'NAS100', 'NETH25', 'NOR25', 'SA40', 'SCI25', 'SPA35', 'SWI20', 'UK100', 'US2000', 'US30', 'US500', 'VIX', 'AUDCAD', 'AUDCHF', 'AUDNZD', 'AUDSGD', 'EURAUD', 'EURCHF', 'EURGBP', 'GBPAUD', 'GBPCHF', 'NZDUSD', 'CHFSGD', 'EURCZK', 'EURHUF', 'EURMXN', 'EURNOK', 'EURPLN', 'EURSEK', 'EURSGD', 'EURTRY', 'EURZAR', 'GBPMXN', 'GBPNOK', 'GBPSEK', 'GBPSGD', 'GBPTRY', 'NOKJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'SEKJPY', 'SGDJPY', 'USDCNH', 'USDCZK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTHB', 'USDTRY', 'USDZAR', 'ZARJPY', 'ADAUSD', 'AVAXUSD', 'BCHUSD', 'BNBUSD', 'BTCUSD', 'Crypto10', 'Crypto20', 'Crypto30', 'DOGEUSD', 'DOTUSD', 'EOSUSD', 'ETHUSD', 'LINKUSD', 'LTCUSD', 'MATICUSD', 'SOLUSD', 'UNIUSD', 'XLMUSD', 'XRPUSD', 'XTZUSD', 'EURX', 'JPYX', 'USDX', 'Gasoline', 'NatGas', 'SpotBrent', 'SpotCrude', 'AAPL.US', 'ABNB.US', 'AMD.US', 'AMZN.US', 'AXP.US', 'BA.US', 'BABA.US', 'BIDU.US', 'BYND.US', 'C.US', 'COIN.US', 'CRM.US', 'DIS.US', 'EA.US', 'GOOG.US', 'GS.US', 'IBM.US', 'JPM.US', 'LMT.US', 'MA.US', 'MCD.US', 'META.US', 'MRNA.US', 'MSFT.US', 'NFLX.US', 'NKE.US', 'NVDA.US', 'ORCL.US', 'PFE.US', 'PG.US', 'PLTR.US', 'PTON.US', 'PYPL.US', 'QCOM.US', 'SNAP.US', 'SPCE.US', 'SPY.US', 'T.US', 'TMUS.US', 'TSLA.US', 'UBER.US', 'V.US', 'WMT.US', 'ZM.US', 'Cattle', 'Cocoa', 'Coffee', 'Corn', 'Cotton', 'LDSugar', 'LeanHogs', 'LondonSugar', 'Lumber', 'OJ', 'Oats', 'RghRice', 'SoyMeal', 'SoyOil', 'Soybeans', 'Sugar', 'Wheat', 'AUDJPY', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURCAD', 'EURJPY', 'EURNZD', 'GBPCAD', 'GBPJPY', 'GBPNZD', 'NZDJPY')) AND ('0' = 0 OR fr.pattern in ('')) AND ('500' = 0 OR fr.patternlengthbars <= '500') 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: 2025-08-25 13:35:25 Duration: 6s115ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
7 1s896ms 3s284ms 2s113ms 16 33s815ms with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Aug 25 13 16 33s815ms 2s113ms [ User: postgres - Total duration: 33s815ms - Times executed: 16 ]
[ Application: psql - Total duration: 33s815ms - 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: 2025-08-25 13:35:16 Duration: 3s284ms 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: 2025-08-25 13:26:16 Duration: 3s225ms 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: 2025-08-25 13:01:15 Duration: 2s23ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
8 1s324ms 2s274ms 1s729ms 12 20s751ms with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = ? left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bg.brokerid and bim.type = ? where bg.brokerid = ? and basegroupname = ? and g.designation = ? and s.nonliquid = ? ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= ? and patternquality >= ?.? and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, case when direction > ? then ? else ? end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (...) and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= ? and _tmp.qtycandlesapart <= ? and ((cpresultuid > ( select coalesce(max(cpresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?)) or (klresultuid > ( select coalesce(max(klresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = ? and cs.basegroupname = ? and date_trunc(?, cs.gmttimefound) = date_trunc(?, now()) and sent is true and filtered is false ) <= ( select case when coalesce(daily_max, ?) < ? then ? else coalesce(daily_max,?) end from corr_sigs_config_v where broker_id = ? limit ? ) and extract(epoch from age(current_timestamp at time zone ?, max_patternendtime - absolutetimezoneoffset * interval ?))/? < mint*? ), maxstats as ( select max(statsid) as maxid , st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = ? then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * ? as numeric), ?) as percent, round(cast((kl_correct) / (kl_total) * ? as numeric), ?) as klpercent, round(cast((cp_correct ) / (cp_total ) * ? as numeric), ?) as cppercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), ?) as openprice, round(cast(sig.forecastprice as numeric), ?) as forecastprice, cast(round(cast(abs(sig.forecastprice - sig.openprice)/pip as numeric), ?)as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname , si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = ? then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = ? and date_part(?, sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = ? and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = ? and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = ? and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = ? and date_part(?, sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = ? and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = ? and kl_sym.name ilike si.symbol ) as tmp order by tmp.gmttimefound desc;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Aug 25 13 12 20s751ms 1s729ms [ User: postgres - Total duration: 20s751ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 20s751ms - Times executed: 12 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '692' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '692'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '692' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '692' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-08-25 13:37:16 Duration: 2s274ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '617' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '617' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '617' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-08-25 13:36:55 Duration: 2s204ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '620' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '620' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '620' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-08-25 13:36:50 Duration: 2s169ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
9 53ms 7s161ms 1s246ms 13 16s202ms copy ( select array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ?) as broker_ids, string_to_array(coalesce(replace(broker_symbol_mappings, ?, ?), ?), ?) as broker_symbol_mappings, replace(exchange, ?, ?) as exchange, symbol_id, replace(symbol, ?, ?) as symbol, replace(short_name, ?, ?) as short_name, replace(long_name, ?, ?) as long_name, interval, replace(timezone, ?, ?) as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ?) as search_groups, string_to_array(pattern_basegroupnames, ?) as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results (?::character varying, current_timestamp::timestamp without time zone)) t) to ?;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Aug 25 13 13 16s202ms 1s246ms [ User: postgres - Total duration: 16s202ms - Times executed: 13 ]
[ Application: psql - Total duration: 16s202ms - Times executed: 13 ]
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COPY ( select /*_solr_fetch_results__*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_acaweb_fx.json';
Date: 2025-08-25 13:33:09 Duration: 7s161ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results__*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_acaweb_fx.json';
Date: 2025-08-25 13:18:06 Duration: 4s143ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results__*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation, signal_levels_entry_level, signal_levels_stop_level, signal_levels_target_level, signal_levels_target_period, signal_levels_filtered from solr_fetch_results ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_acaweb_fx.json';
Date: 2025-08-25 13:48:05 Duration: 2s301ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
10 1s34ms 1s643ms 1s162ms 6 6s976ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Aug 25 13 6 6s976ms 1s162ms [ User: postgres - Total duration: 6s976ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 6s976ms - Times executed: 6 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-08-25 13:49:18 Duration: 1s643ms 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: 2025-08-25 13:01:17 Duration: 1s117ms 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: 2025-08-25 13:16:17 Duration: 1s92ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
11 722ms 1s515ms 1s58ms 16 16s941ms update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Aug 25 13 16 16s941ms 1s58ms [ User: postgres - Total duration: 16s941ms - Times executed: 16 ]
[ Application: psql - Total duration: 16s941ms - 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: 2025-08-25 13:26:13 Duration: 1s515ms 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: 2025-08-25 13:48:13 Duration: 1s358ms 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: 2025-08-25 13:35:13 Duration: 1s265ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
12 142ms 864ms 361ms 136 49s103ms with last_candle as ( select acs.symbolid as symbolid, acs.latestpricedatetime as latest_candle_time, bsl.brokerid as broker_id, coalesce(bim.code, s.symbol) as symbol, bim.code as symbol_mapping, s.exchange as exchange, s.timegranularity as timegranularity from autochartist_symbolupdates acs inner join brokersymbollist bsl on acs.symbolid = bsl.symbolid inner join symbols s on acs.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bsl.brokerid = ? and s.deleted = ? and s.nonliquid = ? and acs.latestpricedatetime is not null ) select * from ( select lc.broker_id as brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / ?) + ? as sast_hh, mod(cast(psp.fromtime as int), ?) as sast_mm, current_timestamp as datetime, (powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice as closingprice, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / ?.?) as low_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / ?.?) as high_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / ?.?) as low_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / ?.?) as high_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / ?.?) as low_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / ?.?) as high_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / ?.?) as low_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / ?.?) as high_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / ?.?) as low_1440, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / ?.?) as high_1440, dtt.absolutetimezoneoffset as datafeedtimezoneoffset, dtt.timezone as datafeedtimezonename, (round((cast(? as float) - rank) / ? * ?)) as rank_rounded, ((cast(? as float) - rank) / ? * ?) as rank from last_candle lc inner join downloadersymbolsettings dss on lc.symbolid = dss.symbolid inner join datafeedstimetable dtt on trim(dss.classname) = trim(dtt.classname) and dtt.dayofweek = ? -- assuming timezone is same for whole week. inner join powerstats_symboldata psd on psd.symbolid = lc.symbolid left outer join powerstats_trumpet psp on psd.trumpetsymbolid = psp.symbolid and psp.dayofweek = extract(dow from lc.latest_candle_time) and psp.fromtime = cast(extract(? from lc.latest_candle_time) as integer) * ? + extract(? from (cast(extract(? from lc.latest_candle_time) as integer) / ?) * ? * interval ?) inner join prfsymboltree prf on psd.symbolid = prf.symbolid and date_trunc(?, prf.enddate) = date_trunc(?, psp.enddate) left join lateral ( select ph.hour, (ave + stddev) as volatility, rank() over (order by (ave + stddev) desc) as rank from powerstats_hourly ph where ph.symbolid = psd.hourlysymbolid and date_trunc(?,ph.enddate) = date_trunc(?, prf.enddate) ) rank_query on true where prf.brokerid = ? and rank_query.hour = floor((psp.fromtime) / ?) and volatility > ? order by rank desc, rank_rounded desc, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Aug 25 13 136 49s103ms 361ms [ User: postgres - Total duration: 49s103ms - Times executed: 136 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 49s103ms - Times executed: 136 ]
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-08-25 13:48:09 Duration: 864ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-08-25 13:48:08 Duration: 857ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-08-25 13:28:06 Duration: 851ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
13 59ms 1s2ms 296ms 197 58s399ms 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 #13
Day Hour Count Duration Avg duration Aug 25 13 197 58s399ms 296ms [ User: postgres - Total duration: 58s399ms - Times executed: 197 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 58s399ms - Times executed: 197 ]
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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 ('500' = 0 OR ccr.patternlengthbars <= '500') ), 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: 2025-08-25 13:44:13 Duration: 1s2ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_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 ('500' = 0 OR ccr.patternlengthbars <= '500') ), 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: 2025-08-25 13:49:47 Duration: 983ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_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 ('500' = 0 OR ccr.patternlengthbars <= '500') ), 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: 2025-08-25 13:54:52 Duration: 979ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
14 12ms 3s414ms 296ms 34 10s72ms select fixcandlegaps (?, false);Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Aug 25 13 34 10s72ms 296ms [ User: postgres - Total duration: 10s72ms - Times executed: 34 ]
[ Application: psql - Total duration: 10s72ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-08-25 13:06:11 Duration: 3s414ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-08-25 13:06:03 Duration: 1s199ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('PEPPERSTONE', false);
Date: 2025-08-25 13:06:06 Duration: 1s30ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
15 16ms 164ms 39ms 192 7s641ms select distinct a.symbolid, p.resultuid, case when a.breakout >= ? then ? else ? end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient from relevance_autochartist_results p inner join autochartist_results a on p.resultuid = a.resultuid inner join autochartist_stocklist asl on a.symbolid = asl.symbolid where asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Aug 25 13 192 7s641ms 39ms [ User: postgres - Total duration: 7s641ms - Times executed: 192 ]
[ Application: [unknown] - Total duration: 7s641ms - Times executed: 192 ]
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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: 2025-08-25 13:32:04 Duration: 164ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-08-25 13:45:55 Duration: 158ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-08-25 13:45:04 Duration: 155ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
16 5ms 10ms 5ms 1,938 10s658ms select * from status_perbroker;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Aug 25 13 1,938 10s658ms 5ms [ User: postgres - Total duration: 10s658ms - Times executed: 1938 ]
[ Application: [unknown] - Total duration: 10s658ms - Times executed: 1938 ]
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select * from status_perbroker;
Date: 2025-08-25 13:31:25 Duration: 10ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
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select * from status_perbroker;
Date: 2025-08-25 13:31:28 Duration: 10ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
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select * from status_perbroker;
Date: 2025-08-25 13:31:28 Duration: 10ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
17 0ms 21ms 2ms 27,816 1m7s select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Aug 25 13 27,816 1m7s 2ms [ User: postgres - Total duration: 1m7s - Times executed: 27816 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m7s - Times executed: 27816 ]
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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 = '667' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'USDJPY' OR dss.downloadersymbol = 'USDJPY') AND dss.enabled = 1;
Date: 2025-08-25 13:15:05 Duration: 21ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 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 = 'XPDUSD' OR dss.downloadersymbol = 'XPDUSD') AND dss.enabled = 1;
Date: 2025-08-25 13:30:04 Duration: 21ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT 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 = 'MidDE50' OR dss.downloadersymbol = 'MidDE50') AND dss.enabled = 1;
Date: 2025-08-25 13:45:04 Duration: 20ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
18 0ms 9ms 1ms 1,699 2s897ms insert into keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errormargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestprice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) values (?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?, ?, ?.?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?.?, ?::timestamp without time zone, ?, ?.?, ?.?, ?, ?, ?.?, ?.?, ?::timestamp without time zone, ?, ?, ?.?, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Aug 25 13 1,699 2s897ms 1ms [ User: postgres - Total duration: 2s897ms - Times executed: 1699 ]
[ Application: [unknown] - Total duration: 2s897ms - Times executed: 1699 ]
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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 (2.000000000000000000000000000000, - 1, 2, '2025-08-25 10:55:43'::timestamp without time zone, '2025-08-25 13:00:00', 0.004885000000000052494000000000, 3, 105, 1.163859999999999895000000000000, '2025-08-21 03:00:00', '2025-08-19 21:00:00', '2025-08-19 04:00:00', '', '', '', '', '', '', '', 94, 1.163515499999999925000000000000, '2025-08-25 13:00:00'::timestamp without time zone, '2025-08-25 13:00:00', 1.168709999999999916000000000000, 0.000344500000000003007000000000, - 1, 500991628217369200, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|500991628217369200|1.16386|2|2025-08-25 13:00:00|2025-08-25 13:00:00|-1|-1', 1.170601299999999956000000000000, 0.006741300000000061132000000000, 2, '2025-08-19 04:00:00', 1.171999999999999931000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-08-25 13:00:45 Duration: 9ms 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 (5.000000000000000000000000000000, - 1, 1, '2025-08-25 11:40:36'::timestamp without time zone, '', 0.500000000000000000000000000000, 5, 95, 70.265000000000000570000000000000, '2025-08-22 17:30:00', '2025-08-22 14:30:00', '2025-08-19 18:00:00', '2025-08-19 15:00:00', '2025-08-19 13:00:00', '', '', '', '', '', 284, 70.341250000000002280000000000000, '2025-08-25 07:00:00'::timestamp without time zone, '2025-08-25 07:00:00', 0.000000000000000000000000000000, 0.109499999999999889100000000000, - 1, 515840249537406300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249537406300|70.265|1|2025-08-25 07:00:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-08-19 13:00:00', 71.704999999999998300000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-08-25 13:45:38 Duration: 8ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (10.000000000000000000000000000000, - 1, 2, '2025-08-25 11:40:36'::timestamp without time zone, '2025-08-25 14:30:00', 0.001665000000000020196000000000, 4, 386, 0.863774999999999959500000000000, '2025-08-22 16:45:00', '2025-08-19 20:45:00', '2025-08-19 15:00:00', '2025-08-19 13:00:00', '', '', '', '', '', '', 757, 0.863493500000000024900000000000, '2025-08-25 14:30:00'::timestamp without time zone, '2025-08-25 14:30:00', 0.865310000000000023600000000000, 0.000281500000000000987700000000, - 1, 515840230409512300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840230409512300|0.863775|2|2025-08-25 14:30:00|2025-08-25 14:30:00|-1|-1', 0.866072700000000028600000000000, 0.002297700000000069132000000000, 2, '2025-08-19 13:00:00', 0.866949999999999998400000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-08-25 13:45:38 Duration: 8ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
19 0ms 29ms 1ms 40,616 54s240ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Aug 25 13 40,616 54s240ms 1ms [ User: postgres - Total duration: 54s240ms - Times executed: 40616 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 54s240ms - Times executed: 40616 ]
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '958' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '958' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243162375300';
Date: 2025-08-25 13:49:16 Duration: 29ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '958' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '958' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840248627808300';
Date: 2025-08-25 13:19:27 Duration: 25ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '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 = '515840243238020300';
Date: 2025-08-25 13:15:04 Duration: 22ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
20 0ms 49ms 1ms 3,456 4s443ms 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 #20
Day Hour Count Duration Avg duration Aug 25 13 3,456 4s443ms 1ms [ User: postgres - Total duration: 4s443ms - Times executed: 3456 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 4s427ms - Times executed: 3422 ]
[ Application: [unknown] - Total duration: 15ms - Times executed: 34 ]
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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 = '606694542424101301' 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 = '606694542424101301' OR a.resultuid = '606694542424101301') AND dtt.dayofweek = 3;
Date: 2025-08-25 13:57:45 Duration: 49ms 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 = '606682284542831301' 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 = '606682284542831301' OR a.resultuid = '606682284542831301') AND dtt.dayofweek = 3;
Date: 2025-08-25 13:49:16 Duration: 24ms 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 = '606682284309376301' 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 = '606682284309376301' OR a.resultuid = '606682284309376301') AND dtt.dayofweek = 3;
Date: 2025-08-25 13:19:27 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 4s102ms 7,624 0ms 14ms 0ms SELECT ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Aug 25 13 7,624 4s102ms 0ms [ User: postgres - Total duration: 14s158ms - Times executed: 7624 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14s153ms - Times executed: 7612 ]
[ Application: [unknown] - Total duration: 4ms - Times executed: 12 ]
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SELECT ;
Date: 2025-08-25 13:55:14 Duration: 14ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
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SELECT ;
Date: 2025-08-25 13:50:29 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
SELECT ;
Date: 2025-08-25 13:57:45 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
2 4s51ms 3,702 0ms 19ms 1ms WITH rar_max as ( ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 13 3,702 4s51ms 1ms [ User: postgres - Total duration: 1h29m20s - Times executed: 3702 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h29m20s - Times executed: 3700 ]
[ Application: [unknown] - Total duration: 2ms - Times executed: 2 ]
-
WITH rar_max as ( ;
Date: 2025-08-25 13:57:45 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
WITH rar_max as ( ;
Date: 2025-08-25 13:53:59 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
WITH rar_max as ( ;
Date: 2025-08-25 13:48:10 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
3 867ms 733 0ms 2ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 13 733 867ms 1ms [ User: postgres - Total duration: 1s152ms - Times executed: 733 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s152ms - Times executed: 733 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-08-25 13:00:38 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: 2025-08-25 13:46:41 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-08-25 13:45:39 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
4 549ms 1,318 0ms 5ms 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 13 1,318 549ms 0ms [ User: postgres - Total duration: 4s469ms - Times executed: 1318 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 4s469ms - Times executed: 1318 ]
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-08-25 13:30:04 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-08-25 13:47:42 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-08-25 13:47:46 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
5 524ms 3,801 0ms 5ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 13 3,801 524ms 0ms [ User: postgres - Total duration: 36ms - Times executed: 3801 ]
[ Application: [unknown] - Total duration: 36ms - Times executed: 3801 ]
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SET extra_float_digits = 3;
Date: 2025-08-25 13:19:39 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
SET extra_float_digits = 3;
Date: 2025-08-25 13:57:45 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
SET extra_float_digits = 3;
Date: 2025-08-25 13:53:59 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
6 303ms 2,982 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 #6
Day Hour Count Duration Avg duration 13 2,982 303ms 0ms [ User: postgres - Total duration: 1s877ms - Times executed: 2982 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s877ms - Times executed: 2982 ]
-
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: 2025-08-25 13:41:51 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-08-25 13:40:57 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-08-25 13:41:57 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
7 284ms 4,833 0ms 5ms 0ms select 1;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 13 4,833 284ms 0ms [ User: postgres - Total duration: 25ms - Times executed: 4833 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 25ms - Times executed: 4833 ]
-
select 1;
Date: 2025-08-25 13:34:09 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
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select 1;
Date: 2025-08-25 13:30:04 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
select 1;
Date: 2025-08-25 13:09:15 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
8 251ms 1,483 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 #8
Day Hour Count Duration Avg duration 13 1,483 251ms 0ms [ User: postgres - Total duration: 15ms - Times executed: 1483 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 15ms - Times executed: 1483 ]
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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: 2025-08-25 13:16:52 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.21
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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: 2025-08-25 13:17:22 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.21
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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: 2025-08-25 13:14:52 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.21
9 207ms 1,767 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 #9
Day Hour Count Duration Avg duration 13 1,767 207ms 0ms [ User: postgres - Total duration: 1s79ms - Times executed: 1767 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s79ms - Times executed: 1767 ]
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-08-25 13:11:35 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-08-25 13:00:40 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-08-25 13:00:02 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
10 112ms 91 0ms 4ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 13 91 112ms 1ms [ User: postgres - Total duration: 34s591ms - Times executed: 91 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 34s591ms - Times executed: 91 ]
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WITH last_candle AS ( ;
Date: 2025-08-25 13:59:07 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
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WITH last_candle AS ( ;
Date: 2025-08-25 13:32:22 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
WITH last_candle AS ( ;
Date: 2025-08-25 13:08:54 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
11 68ms 116 0ms 3ms 0ms WITH pre_symbols AS ( /* find relevant symbols */ ;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 13 116 68ms 0ms [ User: postgres - Total duration: 2s546ms - Times executed: 116 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s546ms - Times executed: 116 ]
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WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-08-25 13:15:00 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.21
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WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-08-25 13:15:41 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.21
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WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-08-25 13:18:16 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.21
12 59ms 12 4ms 5ms 4ms with sym_info as ( ;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 13 12 59ms 4ms [ User: postgres - Total duration: 20s751ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 20s751ms - Times executed: 12 ]
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with sym_info as ( ;
Date: 2025-08-25 13:07:02 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
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with sym_info as ( ;
Date: 2025-08-25 13:21:48 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
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with sym_info as ( ;
Date: 2025-08-25 13:36:48 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
13 45ms 3,776 0ms 1ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 13 3,776 45ms 0ms [ User: postgres - Total duration: 51ms - Times executed: 3776 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 51ms - Times executed: 3776 ]
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-08-25 13:19:39 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-08-25 13:57:45 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-08-25 13:55:42 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
14 45ms 342 0ms 0ms 0ms select category, ;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 13 342 45ms 0ms [ User: postgres - Total duration: 32ms - Times executed: 342 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 32ms - Times executed: 342 ]
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select category, ;
Date: 2025-08-25 13:58:42 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
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select category, ;
Date: 2025-08-25 13:58:46 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
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select category, ;
Date: 2025-08-25 13:09:20 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.11
15 45ms 18 2ms 3ms 2ms select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;Times Reported Time consuming prepare #15
Day Hour Count Duration Avg duration 13 18 45ms 2ms [ User: postgres - Total duration: 29ms - Times executed: 18 ]
[ Application: [unknown] - Total duration: 29ms - Times executed: 18 ]
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select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-08-25 13:50:03 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
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select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-08-25 13:51:09 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-08-25 13:51:00 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
16 42ms 33 1ms 1ms 1ms select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 13 33 42ms 1ms [ User: postgres - Total duration: 109ms - Times executed: 33 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 109ms - Times executed: 33 ]
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select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2025-08-25 13:38:15 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2025-08-25 13:23:12 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2025-08-25 13:19:09 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
17 28ms 33 0ms 1ms 0ms select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 13 33 28ms 0ms [ User: postgres - Total duration: 39ms - Times executed: 33 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 39ms - Times executed: 33 ]
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select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2025-08-25 13:38:15 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2025-08-25 13:19:09 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2025-08-25 13:33:14 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
18 22ms 47 0ms 1ms 0ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 13 47 22ms 0ms [ User: postgres - Total duration: 0ms - Times executed: 47 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 0ms - Times executed: 47 ]
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WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-08-25 13:44:59 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
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WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-08-25 13:23:47 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
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WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-08-25 13:30:22 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
19 19ms 6 2ms 3ms 3ms select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 13 6 19ms 3ms [ User: postgres - Total duration: 12ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 12ms - Times executed: 6 ]
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select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2025-08-25 13:30:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
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select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2025-08-25 13:20:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
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select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2025-08-25 13:50:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
20 18ms 6 2ms 3ms 3ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 13 6 18ms 3ms [ User: postgres - Total duration: 39s151ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 39s151ms - 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: 2025-08-25 13:40:02 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-08-25 13:50:02 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-08-25 13:00:02 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 37s902ms 7,326 0ms 53ms 5ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Aug 25 13 7,326 37s902ms 5ms [ User: postgres - Total duration: 1h52m5s - Times executed: 7326 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h52m5s - Times executed: 7290 ]
[ Application: [unknown] - Total duration: 17ms - Times executed: 36 ]
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WITH rar_max as ( ;
Date: 2025-08-25 13:49:14 Duration: 53ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = 't', $2 = '621', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '1', $14 = 'EURUSD', $15 = '0', $16 = '', $17 = '0', $18 = '0', $19 = '0', $20 = '0', $21 = '0', $22 = 't', $23 = '10', $24 = '10'
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WITH rar_max as ( ;
Date: 2025-08-25 13:15:04 Duration: 47ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '0', $10 = 't', $11 = '0', $12 = '0'
-
WITH rar_max as ( ;
Date: 2025-08-25 13:19:27 Duration: 44ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '606697381805979301', $2 = '606697381805979301', $3 = '606697381805979301'
2 32s7ms 74,029 0ms 33ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 13 74,029 32s7ms 0ms [ User: postgres - Total duration: 2m7s - Times executed: 74029 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m7s - Times executed: 73922 ]
[ Application: [unknown] - Total duration: 57ms - Times executed: 107 ]
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SELECT ;
Date: 2025-08-25 13:49:16 Duration: 33ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '958', $2 = '958', $3 = '515840218033677300'
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SELECT ;
Date: 2025-08-25 13:19:27 Duration: 30ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '958', $2 = '958', $3 = '515840248625039300'
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SELECT ;
Date: 2025-08-25 13:56:57 Duration: 27ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '958', $2 = '958', $3 = '515840217496618300'
3 1s309ms 733 1ms 4ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 13 733 1s309ms 1ms [ User: postgres - Total duration: 1s152ms - Times executed: 733 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s152ms - Times executed: 733 ]
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-08-25 13:01:33 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'BDSWISS'
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-08-25 13:30:36 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'PEPPERSTONE'
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-08-25 13:46:09 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'GLOBALGTMT5'
4 1s20ms 136 4ms 18ms 7ms WITH last_candle AS ( ;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 13 136 1s20ms 7ms [ User: postgres - Total duration: 49s103ms - Times executed: 136 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 49s103ms - Times executed: 136 ]
-
WITH last_candle AS ( ;
Date: 2025-08-25 13:28:05 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558'
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WITH last_candle AS ( ;
Date: 2025-08-25 13:44:06 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558'
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WITH last_candle AS ( ;
Date: 2025-08-25 13:12:51 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558'
5 944ms 59,122 0ms 11ms 0ms select 1;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 13 59,121 944ms 0ms 14 1 0ms 0ms [ User: postgres - Total duration: 232ms - Times executed: 59122 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 232ms - Times executed: 58953 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 169 ]
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select 1;
Date: 2025-08-25 13:50:29 Duration: 11ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
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select 1;
Date: 2025-08-25 13:45:04 Duration: 11ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
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select 1;
Date: 2025-08-25 13:15:04 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
6 815ms 36 0ms 48ms 22ms with wh_patitioned as ( ;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 13 36 815ms 22ms [ User: postgres - Total duration: 1s241ms - Times executed: 36 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s241ms - Times executed: 36 ]
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with wh_patitioned as ( ;
Date: 2025-08-25 13:50:01 Duration: 48ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
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with wh_patitioned as ( ;
Date: 2025-08-25 13:50:02 Duration: 48ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
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with wh_patitioned as ( ;
Date: 2025-08-25 13:42:56 Duration: 48ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
7 714ms 57 9ms 32ms 12ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 13 57 714ms 12ms [ User: postgres - Total duration: 1ms - Times executed: 57 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1ms - Times executed: 57 ]
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WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-08-25 13:15:04 Duration: 32ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
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WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-08-25 13:44:59 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
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WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-08-25 13:23:47 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
8 640ms 1,483 0ms 2ms 0ms SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 13 1,483 640ms 0ms [ User: postgres - Total duration: 15ms - Times executed: 1483 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 15ms - Times executed: 1483 ]
-
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: 2025-08-25 13:14:23 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.21
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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: 2025-08-25 13:15:52 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.21
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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: 2025-08-25 13:18:22 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.21
9 569ms 6,010 0ms 2ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 13 6,010 569ms 0ms [ User: postgres - Total duration: 7s292ms - Times executed: 6010 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 7s292ms - Times executed: 6010 ]
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-08-25 13:30:04 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-08-25 14:15:00', $2 = '20.99395', $3 = '20.99465', $4 = '20.98715', $5 = '20.9892', $6 = '694', $7 = '605679104092484300', $8 = '0', $9 = '2025-08-25 13:30:04.47', $10 = '2025-08-25 13:30:04.425', $11 = '20.99395', $12 = '20.99465', $13 = '20.98715', $14 = '20.9892', $15 = '694', $16 = '0', $17 = '2025-08-25 13:30:04.47', $18 = '2025-08-25 13:30:04.425'
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-08-25 13:30:05 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-08-25 14:00:00', $2 = '17.5422', $3 = '17.54875', $4 = '17.538515', $5 = '17.547195', $6 = '615', $7 = '515840249465587300', $8 = '0', $9 = '2025-08-25 13:30:05.968', $10 = '2025-08-25 13:30:05.828', $11 = '17.5422', $12 = '17.54875', $13 = '17.538515', $14 = '17.547195', $15 = '615', $16 = '0', $17 = '2025-08-25 13:30:05.968', $18 = '2025-08-25 13:30:05.828'
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-08-25 13:30:07 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-08-25 14:00:00', $2 = '0.938225', $3 = '0.938335', $4 = '0.938175', $5 = '0.938325', $6 = '828', $7 = '515840230468413300', $8 = '0', $9 = '2025-08-25 13:30:07.001', $10 = '2025-08-25 13:30:06.963', $11 = '0.938225', $12 = '0.938335', $13 = '0.938175', $14 = '0.938325', $15 = '828', $16 = '0', $17 = '2025-08-25 13:30:07.001', $18 = '2025-08-25 13:30:06.963'
10 440ms 90 0ms 21ms 4ms select distinct s.statsid as statsid, sy.exchange as name;Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 13 90 440ms 4ms [ User: postgres - Total duration: 264ms - Times executed: 90 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 264ms - Times executed: 90 ]
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select distinct s.statsid as statsid, sy.exchange as name;
Date: 2025-08-25 13:09:20 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.11 parameters: $1 = '489', $2 = '489'
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select distinct s.statsid as statsid, sy.exchange as name;
Date: 2025-08-25 13:58:52 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '619', $2 = '619'
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select distinct s.statsid as statsid, sy.exchange as name;
Date: 2025-08-25 13:58:47 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '510', $2 = '510'
11 404ms 116 0ms 34ms 3ms WITH pre_symbols AS ( /* find relevant symbols */ ;Times Reported Time consuming bind #11
Day Hour Count Duration Avg duration 13 116 404ms 3ms [ User: postgres - Total duration: 2s546ms - Times executed: 116 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s546ms - Times executed: 116 ]
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WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-08-25 13:18:37 Duration: 34ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.21 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: 2025-08-25 13:18:37 Duration: 22ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.21 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: 2025-08-25 13:18:36 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.21 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'
12 350ms 12 28ms 37ms 29ms with sym_info as ( ;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 13 12 350ms 29ms [ User: postgres - Total duration: 20s751ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 20s751ms - Times executed: 12 ]
-
with sym_info as ( ;
Date: 2025-08-25 13:21:59 Duration: 37ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '627', $2 = 'Forex', $3 = 'Forex', $4 = '627', $5 = 'Forex', $6 = '627', $7 = '627', $8 = 'Forex', $9 = '627'
-
with sym_info as ( ;
Date: 2025-08-25 13:21:48 Duration: 29ms 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: 2025-08-25 13:07:18 Duration: 28ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '627', $2 = 'Forex', $3 = 'Forex', $4 = '627', $5 = 'Forex', $6 = '627', $7 = '627', $8 = 'Forex', $9 = '627'
13 276ms 4,332 0ms 1ms 0ms select category, ;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 13 4,332 276ms 0ms [ User: postgres - Total duration: 276ms - Times executed: 4332 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 276ms - Times executed: 4332 ]
-
select category, ;
Date: 2025-08-25 13:58:48 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '515852059305993307', $2 = 'symbol', $3 = 'XBRUSD', $4 = 'JP225', $5 = 'XTIUSD', $6 = 'UK100', $7 = 'US2000', $8 = 'XNGUSD', $9 = 'XAGEUR', $10 = 'USTEC', $11 = 'US500', $12 = 'AUS200', $13 = 'XAGUSD', $14 = 'F40', $15 = 'XAUUSD', $16 = 'XPTUSD', $17 = 'XPDUSD', $18 = 'US30', $19 = 'XAUEUR', $20 = 'STOXX50', $21 = 'CHINA50', $22 = 'HK50', $23 = 'US2000', $24 = 'XNGUSD', $25 = 'XPDUSD', $26 = 'XAGEUR', $27 = 'XTIUSD', $28 = 'XAUEUR', $29 = 'IT40', $30 = 'XAGUSD', $31 = 'XBRUSD', $32 = 'JP225', $33 = 'UK100', $34 = 'US500', $35 = 'XPTUSD', $36 = 'USTEC', $37 = 'XAUUSD', $38 = 'US30', $39 = 'AUS200', $40 = 'CHINA50', $41 = 'F40', $42 = 'STOXX50', $43 = 'ES35', $44 = 'HK50', $45 = 'IT40', $46 = 'ES35', $47 = '515852059305993307', $48 = 'symbol', $49 = 'XBRUSD', $50 = 'JP225', $51 = 'XTIUSD', $52 = 'UK100', $53 = 'US2000', $54 = 'XNGUSD', $55 = 'XAGEUR', $56 = 'USTEC', $57 = 'US500', $58 = 'AUS200', $59 = 'XAGUSD', $60 = 'F40', $61 = 'XAUUSD', $62 = 'XPTUSD', $63 = 'XPDUSD', $64 = 'US30', $65 = 'XAUEUR', $66 = 'STOXX50', $67 = 'CHINA50', $68 = 'HK50', $69 = 'US2000', $70 = 'XNGUSD', $71 = 'XPDUSD', $72 = 'XAGEUR', $73 = 'XTIUSD', $74 = 'XAUEUR', $75 = 'IT40', $76 = 'XAGUSD', $77 = 'XBRUSD', $78 = 'JP225', $79 = 'UK100', $80 = 'US500', $81 = 'XPTUSD', $82 = 'USTEC', $83 = 'XAUUSD', $84 = 'US30', $85 = 'AUS200', $86 = 'CHINA50', $87 = 'F40', $88 = 'STOXX50', $89 = 'ES35', $90 = 'HK50', $91 = 'IT40', $92 = 'ES35'
-
select category, ;
Date: 2025-08-25 13:58:48 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '515852059324253307', $2 = 'symbol', $3 = 'USDMXN', $4 = 'CHFZAR', $5 = 'CADJPY', $6 = 'USDZAR', $7 = 'GBPZAR', $8 = 'ZARJPY', $9 = 'CHFHUF', $10 = 'NZDJPY', $11 = 'CHFJPY', $12 = 'EURJPY', $13 = 'SGDJPY', $14 = 'AUDJPY', $15 = 'USDNOK', $16 = 'GBPJPY', $17 = 'USDSEK', $18 = 'USDHUF', $19 = 'EURMXN', $20 = 'USDJPY', $21 = 'EURZAR', $22 = 'AUDZAR', $23 = 'EURNOK', $24 = 'USDDKK', $25 = 'NZDSEK', $26 = 'EURHKD', $27 = 'EURCNH', $28 = 'USDCZK', $29 = 'TRYJPY', $30 = 'EURSEK', $31 = 'USDCNH', $32 = 'EURTRY', $33 = 'USDPLN', $34 = 'EURHUF', $35 = 'EURCZK', $36 = 'USDILS', $37 = 'TRYJPY', $38 = 'EURPLN', $39 = 'EURHUF', $40 = 'GBPNZD', $41 = 'EURNZD', $42 = 'EURCZK', $43 = 'ZARJPY', $44 = 'EURGBP', $45 = 'CHFHUF', $46 = 'EURSEK', $47 = 'GBPAUD', $48 = 'NOKSEK', $49 = 'USDMXN', $50 = 'EURTRY', $51 = 'EURDKK', $52 = 'GBPCAD', $53 = '515852059324253307', $54 = 'symbol', $55 = 'USDMXN', $56 = 'CHFZAR', $57 = 'CADJPY', $58 = 'USDZAR', $59 = 'GBPZAR', $60 = 'ZARJPY', $61 = 'CHFHUF', $62 = 'NZDJPY', $63 = 'CHFJPY', $64 = 'EURJPY', $65 = 'SGDJPY', $66 = 'AUDJPY', $67 = 'USDNOK', $68 = 'GBPJPY', $69 = 'USDSEK', $70 = 'USDHUF', $71 = 'EURMXN', $72 = 'USDJPY', $73 = 'EURZAR', $74 = 'AUDZAR', $75 = 'EURNOK', $76 = 'USDDKK', $77 = 'NZDSEK', $78 = 'EURHKD', $79 = 'EURCNH', $80 = 'USDCZK', $81 = 'TRYJPY', $82 = 'EURSEK', $83 = 'USDCNH', $84 = 'EURTRY', $85 = 'USDPLN', $86 = 'EURHUF', $87 = 'EURCZK', $88 = 'USDILS', $89 = 'TRYJPY', $90 = 'EURPLN', $91 = 'EURHUF', $92 = 'GBPNZD', $93 = 'EURNZD', $94 = 'EURCZK', $95 = 'ZARJPY', $96 = 'EURGBP', $97 = 'CHFHUF', $98 = 'EURSEK', $99 = 'GBPAUD', $100 = 'NOKSEK', $101 = 'USDMXN', $102 = 'EURTRY', $103 = 'EURDKK', $104 = 'GBPCAD'
-
select category, ;
Date: 2025-08-25 13:58:52 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '515852059324253307', $2 = 'symbol', $3 = 'USDMXN', $4 = 'CHFZAR', $5 = 'CADJPY', $6 = 'USDZAR', $7 = 'GBPZAR', $8 = 'ZARJPY', $9 = 'CHFHUF', $10 = 'NZDJPY', $11 = 'CHFJPY', $12 = 'EURJPY', $13 = 'SGDJPY', $14 = 'AUDJPY', $15 = 'USDNOK', $16 = 'GBPJPY', $17 = 'USDSEK', $18 = 'USDHUF', $19 = 'EURMXN', $20 = 'USDJPY', $21 = 'EURZAR', $22 = 'AUDZAR', $23 = 'EURNOK', $24 = 'USDDKK', $25 = 'NZDSEK', $26 = 'EURHKD', $27 = 'EURCNH', $28 = 'USDCZK', $29 = 'TRYJPY', $30 = 'EURSEK', $31 = 'USDCNH', $32 = 'EURTRY', $33 = 'USDPLN', $34 = 'EURHUF', $35 = 'EURCZK', $36 = 'USDILS', $37 = 'TRYJPY', $38 = 'EURPLN', $39 = 'EURHUF', $40 = 'GBPNZD', $41 = 'EURNZD', $42 = 'EURCZK', $43 = 'ZARJPY', $44 = 'EURGBP', $45 = 'CHFHUF', $46 = 'EURSEK', $47 = 'GBPAUD', $48 = 'NOKSEK', $49 = 'USDMXN', $50 = 'EURTRY', $51 = 'EURDKK', $52 = 'GBPCAD', $53 = '515852059324253307', $54 = 'symbol', $55 = 'USDMXN', $56 = 'CHFZAR', $57 = 'CADJPY', $58 = 'USDZAR', $59 = 'GBPZAR', $60 = 'ZARJPY', $61 = 'CHFHUF', $62 = 'NZDJPY', $63 = 'CHFJPY', $64 = 'EURJPY', $65 = 'SGDJPY', $66 = 'AUDJPY', $67 = 'USDNOK', $68 = 'GBPJPY', $69 = 'USDSEK', $70 = 'USDHUF', $71 = 'EURMXN', $72 = 'USDJPY', $73 = 'EURZAR', $74 = 'AUDZAR', $75 = 'EURNOK', $76 = 'USDDKK', $77 = 'NZDSEK', $78 = 'EURHKD', $79 = 'EURCNH', $80 = 'USDCZK', $81 = 'TRYJPY', $82 = 'EURSEK', $83 = 'USDCNH', $84 = 'EURTRY', $85 = 'USDPLN', $86 = 'EURHUF', $87 = 'EURCZK', $88 = 'USDILS', $89 = 'TRYJPY', $90 = 'EURPLN', $91 = 'EURHUF', $92 = 'GBPNZD', $93 = 'EURNZD', $94 = 'EURCZK', $95 = 'ZARJPY', $96 = 'EURGBP', $97 = 'CHFHUF', $98 = 'EURSEK', $99 = 'GBPAUD', $100 = 'NOKSEK', $101 = 'USDMXN', $102 = 'EURTRY', $103 = 'EURDKK', $104 = 'GBPCAD'
14 269ms 3,427 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 13 3,427 269ms 0ms [ User: postgres - Total duration: 2s31ms - Times executed: 3427 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s31ms - Times executed: 3427 ]
-
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: 2025-08-25 13:00:43 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-08-25 13:30:00', $2 = '26459.5', $3 = '26482.3', $4 = '26374.8', $5 = '26422.6', $6 = '2279', $7 = '515840248267105300', $8 = '0', $9 = '2025-08-25 13:00:43.392', $10 = '2025-08-25 13:00:43.337', $11 = '26459.5', $12 = '26482.3', $13 = '26374.8', $14 = '26422.6', $15 = '2279', $16 = '0', $17 = '2025-08-25 13:00:43.392', $18 = '2025-08-25 13:00:43.337'
-
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: 2025-08-25 13:00:43 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-08-25 13:30:00', $2 = '111193.93', $3 = '111383.5', $4 = '110904.53', $5 = '110939.46', $6 = '20429', $7 = '515840245930272300', $8 = '0', $9 = '2025-08-25 13:00:43.844', $10 = '2025-08-25 13:00:43.824', $11 = '111193.93', $12 = '111383.5', $13 = '110904.53', $14 = '110939.46', $15 = '20429', $16 = '0', $17 = '2025-08-25 13:00:43.844', $18 = '2025-08-25 13:00:43.824'
-
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: 2025-08-25 13:41:57 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-08-25 14:00:00', $2 = '45536.45', $3 = '45558.55', $4 = '45534.05', $5 = '45544.05', $6 = '576', $7 = '515840248000726300', $8 = '0', $9 = '2025-08-25 13:41:57.734', $10 = '2025-08-25 13:41:57.686', $11 = '45536.45', $12 = '45558.55', $13 = '45534.05', $14 = '45544.05', $15 = '576', $16 = '0', $17 = '2025-08-25 13:41:57.734', $18 = '2025-08-25 13:41:57.686'
15 189ms 2,222 0ms 0ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 13 2,222 189ms 0ms [ User: postgres - Total duration: 1s198ms - Times executed: 2222 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s198ms - Times executed: 2222 ]
-
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: 2025-08-25 13:00:50 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-08-25 13:00:00', $2 = '1.34943', $3 = '1.34958', $4 = '1.3483', $5 = '1.34899', $6 = '2792', $7 = '515840247885064300', $8 = '0', $9 = '2025-08-25 13:00:50.855', $10 = '2025-08-25 13:00:50.68', $11 = '1.34943', $12 = '1.34958', $13 = '1.3483', $14 = '1.34899', $15 = '2792', $16 = '0', $17 = '2025-08-25 13:00:50.855', $18 = '2025-08-25 13:00:50.68'
-
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: 2025-08-25 13:01:01 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-08-25 13:00:00', $2 = '3367.3', $3 = '3368.27', $4 = '3364.88', $5 = '3365.8', $6 = '4935', $7 = '515840247906886300', $8 = '0', $9 = '2025-08-25 13:01:01.235', $10 = '2025-08-25 13:01:01.134', $11 = '3367.3', $12 = '3368.27', $13 = '3364.88', $14 = '3365.8', $15 = '4935', $16 = '0', $17 = '2025-08-25 13:01:01.235', $18 = '2025-08-25 13:01:01.134'
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-08-25 13:00:40 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-08-25 13:00:00', $2 = '106.523', $3 = '106.581', $4 = '106.499', $5 = '106.561', $6 = '3474', $7 = '515840247880591300', $8 = '0', $9 = '2025-08-25 13:00:40.827', $10 = '2025-08-25 13:00:40.67', $11 = '106.523', $12 = '106.581', $13 = '106.499', $14 = '106.561', $15 = '3474', $16 = '0', $17 = '2025-08-25 13:00:40.827', $18 = '2025-08-25 13:00:40.67'
16 142ms 228 0ms 1ms 0ms SELECT absolutetimezoneoffset;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 13 228 142ms 0ms [ User: postgres - Total duration: 560ms - Times executed: 228 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 560ms - Times executed: 228 ]
-
SELECT absolutetimezoneoffset;
Date: 2025-08-25 13:58:48 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '538', $2 = 'Forex Majors'
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SELECT absolutetimezoneoffset;
Date: 2025-08-25 13:09:20 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.11 parameters: $1 = '489', $2 = 'BROKER'
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SELECT absolutetimezoneoffset;
Date: 2025-08-25 13:58:44 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '538', $2 = 'Forex Majors'
17 109ms 122 0ms 1ms 0ms SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 13 122 109ms 0ms [ User: postgres - Total duration: 765ms - Times executed: 122 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 718ms - Times executed: 116 ]
[ Application: [unknown] - Total duration: 46ms - Times executed: 6 ]
-
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: 2025-08-25 13:49:27 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '529', $2 = 'NAS100_SB', $3 = '529'
-
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2025-08-25 13:34:37 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '529', $2 = 'SpotCrude', $3 = '529'
-
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2025-08-25 13:45:37 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.42 parameters: $1 = '689', $2 = 'XAUUSD', $3 = '689'
18 78ms 15 3ms 9ms 5ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 13 15 78ms 5ms [ User: postgres - Total duration: 1s845ms - Times executed: 15 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s845ms - Times executed: 15 ]
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-08-25 13:58:57 Duration: 9ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '958', $2 = '958'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-08-25 13:58:51 Duration: 9ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '958', $2 = '958'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-08-25 13:54:47 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '958', $2 = '958'
19 32ms 427 0ms 0ms 0ms /*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 13 427 32ms 0ms [ User: postgres - Total duration: 36ms - Times executed: 427 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 36ms - Times executed: 427 ]
-
/*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: 2025-08-25 13:33:10 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '606697728956595301'
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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: 2025-08-25 13:47:45 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '606697905998004301'
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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: 2025-08-25 13:00:39 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '606660592715037301'
20 31ms 47 0ms 1ms 0ms WITH tr_max AS ( ;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 13 47 31ms 0ms [ User: postgres - Total duration: 155ms - Times executed: 47 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 155ms - Times executed: 47 ]
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WITH tr_max AS ( ;
Date: 2025-08-25 13:15:00 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.21 parameters: $1 = '500991628259001200', $2 = '500991628259001200', $3 = '500991628259001200', $4 = '1', $5 = '1', $6 = '780', $7 = 't', $8 = '780'
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WITH tr_max AS ( ;
Date: 2025-08-25 13:15:41 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.21 parameters: $1 = '515840243155469300', $2 = '515840243155469300', $3 = '515840243155469300', $4 = '1', $5 = '1', $6 = '780', $7 = 't', $8 = '780'
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WITH tr_max AS ( ;
Date: 2025-08-25 13:18:38 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.21 parameters: $1 = '605679104119514300', $2 = '605679104119514300', $3 = '605679104119514300', $4 = '1', $5 = '1', $6 = '780', $7 = 't', $8 = '780'
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Events
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- 624,232 Log entries
Events distribution
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Rank Times reported Error NO DATASET