-
Global information
- Generated on Tue Jun 17 12:00:49 2025
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2025-06-17_130000.log, ..., /home/postgres/pg_data/data/pg_log/postgresql-2025-06-17_134219.log
- Parsed 3,627,069 log entries in 1m48s
- Log start from 2025-06-17 13:00:00 to 2025-06-17 14:00:00
-
Overview
Global Stats
- 223 Number of unique normalized queries
- 208,006 Number of queries
- 2h56m35s Total query duration
- 2025-06-17 13:00:00 First query
- 2025-06-17 13:59:59 Last query
- 3,328 queries/s at 2025-06-17 13:45:04 Query peak
- 2h56m35s Total query duration
- 12s472ms Prepare/parse total duration
- 1m47s Bind total duration
- 2h54m34s 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
- 53 Total number of automatic vacuums
- 57 Total number of automatic analyzes
- 480 Number temporary file
- 163.62 MiB Max size of temporary file
- 7.53 MiB Average size of temporary file
- 4,651 Total number of sessions
- 11 sessions at 2025-06-17 13:41:15 Session peak
- 2d12h38m34s Total duration of sessions
- 46s939ms Average duration of sessions
- 44 Average queries per session
- 2s278ms Average queries duration per session
- 44s661ms Average idle time per session
- 4,652 Total number of connections
- 37 connections/s at 2025-06-17 13:18:48 Connection peak
- 2 Total number of databases
SQL Traffic
Key values
- 3,328 queries/s Query Peak
- 2025-06-17 13:45:04 Date
SELECT Traffic
Key values
- 3,259 queries/s Query Peak
- 2025-06-17 13:45:04 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 213 queries/s Query Peak
- 2025-06-17 13:00:58 Date
Queries duration
Key values
- 2h56m35s Total query duration
Prepared queries ratio
Key values
- 0.00 Ratio of bind vs prepare
- 0.00 % Ratio between prepared and "usual" statements
General Activity
↑ Back to the top of the General Activity tableDay Hour Count Min duration Max duration Avg duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jun 17 13 208,006 0ms 49s649ms 50ms 5m17s 6m 8m13s 14 0 0ms 0ms 0ms 0ms 0ms 0ms Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jun 17 13 158,734 26 2ms 5s158ms 17s55ms 36s347ms 14 0 0 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jun 17 13 32,471 3,829 16 96 1ms 815ms 1s503ms 3s384ms 14 0 0 0 0 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Jun 17 13 30,946 181,109 5.85 15.22% 14 0 0 0.00 0.00% Day Hour Count Average / Second Jun 17 13 4,652 1.29/s 14 0 0.00/s Day Hour Count Average Duration Average idle time Jun 17 13 4,651 46s939ms 44s687ms 14 0 0ms 0ms -
Connections
Established Connections
Key values
- 37 connections Connection Peak
- 2025-06-17 13:18:48 Date
Connections per database
Key values
- acaweb_fx Main Database
- 4,652 connections Total
Connections per user
Key values
- postgres Main User
- 4,652 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 1439 connections
- 4,652 Total connections
Host Count 127.0.0.1 125 192.168.0.114 2 192.168.0.216 97 192.168.0.74 536 192.168.1.145 282 192.168.1.15 836 192.168.1.20 314 192.168.1.231 20 192.168.1.239 14 192.168.1.90 52 192.168.2.126 62 192.168.2.182 12 192.168.2.205 12 192.168.2.82 48 192.168.3.199 63 192.168.4.142 1,439 192.168.4.150 10 192.168.4.226 1 192.168.4.238 16 192.168.4.249 10 192.168.4.33 93 192.168.4.5 4 192.168.4.98 330 [local] 274 -
Sessions
Simultaneous sessions
Key values
- 11 sessions Session Peak
- 2025-06-17 13:41:15 Date
Histogram of session times
Key values
- 3,513 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 4,651 sessions Total
Sessions per user
Key values
- postgres Main User
- 4,651 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 4,651 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 125 1h6s 28s848ms 192.168.0.114 2 10m 5m 192.168.0.216 97 2m34s 1s591ms 192.168.0.74 536 4h9m16s 27s904ms 192.168.1.145 282 5h3m38s 1m4s 192.168.1.15 835 4h50m37s 20s882ms 192.168.1.20 314 14h34m32s 2m47s 192.168.1.231 20 9h54m27s 29m43s 192.168.1.239 14 130ms 9ms 192.168.1.90 52 40s374ms 776ms 192.168.2.126 62 6s283ms 101ms 192.168.2.182 12 961ms 80ms 192.168.2.205 12 452ms 37ms 192.168.2.82 48 20s20ms 417ms 192.168.3.199 63 37s432ms 594ms 192.168.4.142 1,439 27m3s 1s128ms 192.168.4.150 10 20h11m54s 2h1m11s 192.168.4.226 1 166ms 166ms 192.168.4.238 16 28s258ms 1s766ms 192.168.4.249 10 5m23s 32s316ms 192.168.4.33 93 4m11s 2s699ms 192.168.4.5 4 32ms 8ms 192.168.4.98 330 13s48ms 39ms [local] 274 2m22s 518ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 16,011 buffers Checkpoint Peak
- 2025-06-17 13:07:33 Date
- 209.862 seconds Highest write time
- 0.011 seconds Sync time
Checkpoints Wal files
Key values
- 8 files Wal files usage Peak
- 2025-06-17 13:07:33 Date
Checkpoints distance
Key values
- 240.72 Mo Distance Peak
- 2025-06-17 13:07:33 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Jun 17 13 50,070 1,745.009s 0.044s 1,745.376s 14 0 0s 0s 0s Day Hour Added Removed Recycled Synced files Longest sync Average sync Jun 17 13 0 0 27 2,010 0.009s 0s 14 0 0 0 0 0s 0s Day Hour Count Avg time (sec) Jun 17 13 0 0s 14 0 0s Day Hour Mean distance Mean estimate Jun 17 13 39,358.45 kB 89,424.45 kB 14 0.00 kB 0.00 kB -
Temporary Files
Size of temporary files
Key values
- 159.93 MiB Temp Files size Peak
- 2025-06-17 13:30:11 Date
Number of temporary files
Key values
- 30 per second Temp Files Peak
- 2025-06-17 13:02:14 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Jun 17 13 480 3.53 GiB 7.53 MiB 14 0 0 0 Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 133 603.56 MiB 3.01 MiB 7.70 MiB 4.54 MiB with rar_max as ( ;-
WITH rar_max as ( ;
Date: 2025-06-17 13:42:20 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver
2 38 1.60 GiB 7.33 MiB 163.62 MiB 43.24 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-17 13:00:12 Duration: 9s290ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-17 13:30:11 Duration: 8s859ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-17 13:50:08 Duration: 5s299ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
3 16 371.45 MiB 23.21 MiB 23.22 MiB 23.22 MiB update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:41:13 Duration: 1s684ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:26:13 Duration: 1s247ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:01:13 Duration: 1s242ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
4 16 760.45 MiB 47.52 MiB 47.53 MiB 47.53 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:26:16 Duration: 3s288ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:31:16 Duration: 3s176ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:01:16 Duration: 3s145ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
5 4 217.60 MiB 54.31 MiB 54.50 MiB 54.40 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2025-06-17 13:02:16 Duration: 13s502ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-06-17 13:47:15 Duration: 12s988ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-06-17 13:17:15 Duration: 12s545ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
6 1 3.03 MiB 3.03 MiB 3.03 MiB 3.03 MiB jr.resultuid as resultuid, jr.direction as direction, jr.patternendtime as identified, jr.patternlengthbars as length, jr.patternstarttime as patternstarttime, case when jr.trendchangeid = ? then ? else ? end as trendchange, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, jp.patternname as pattern_name, dtt.timezone as timezone, ? as age, cps.pip, g.basegroupname from japsticks_results jr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = jr.symbolid inner join relevance_japsticks_results rar on rar.resultuid = jr.resultuid inner join symbols s on jr.symbolid = s.symbolid and s.nonliquid = ? inner join japsticks_patterns jp on jr.patternid = jp.id inner join downloadersymbolsettings dss on jr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? 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 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 jr.gmttimefound > now() - interval ? and s.deleted = ? and (jr.simulation = ? or jr.simulation is null) and (rar.relevant = ?) --and (semicolon_age = ? or rar.age <= semicolon_age) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or jp.patternname in (...)) and (? = ? or jr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results order by symbolid, resultuid ) select * from results order by identified desc, length desc ;-
jr.resultuid AS resultuid, jr.direction AS direction, jr.patternendtime AS identified, jr.patternlengthbars AS length, jr.patternstarttime AS patternstarttime, case when jr.trendchangeid = 1 then 'Continuation' else 'Reversal' end AS trendchange, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, jp.patternname AS pattern_name, dtt.timezone AS timezone, 0 AS age, cps.pip, g.basegroupname FROM japsticks_results jr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = jr.symbolid INNER JOIN relevance_japsticks_results rar ON rar.resultuid = jr.resultuid INNER JOIN symbols s ON jr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN japsticks_patterns jp ON jr.patternid = jp.id INNER JOIN downloadersymbolsettings dss ON jr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 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 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 jr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (jr.simulation = 0 OR jr.simulation IS NULL) AND (rar.relevant = 1) --AND (semicolon_age = 0 OR rar.age <= semicolon_age) AND ($2 = 0 OR s.timegranularity in ($3)) AND ($4 = 0 OR s.exchange in ($5)) AND ($6 = 0 OR coalesce(bim.code, s.symbol) in ($7)) AND ($8 = 0 OR jp.patternname in ($9)) AND ($10 = 0 OR jr.patternlengthbars <= $11)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:49:26 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver
7 1 3.20 MiB 3.20 MiB 3.20 MiB 3.20 MiB select distinct current_database() as database, s.symbolid, s.symbol, dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity, count(s.symbolid) filter (where s.symbol ilike ?) as symbol_match, count(s.symbolid) filter (where dss.downloadersymbol ilike ?) as downloadersymbol_match, count(s.symbolid) filter (where s.longname ilike ?) as longname_match, count(s.symbolid) filter (where dss.classname ilike ?) as classname_match, count(s.symbolid) filter (where s.exchange ilike ?) as exchange_match from symbols s join downloadersymbolsettings dss on s.symbolid = dss.symbolid where (s.symbol ilike ? or downloadersymbol ilike ? or s.shortname ilike ? or s.longname ilike ? or dss.classname ilike ? or s.exchange ilike ?) and s.deleted = ? group by s.symbolid, s.symbol, current_database(), dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity order by symbol_match desc, downloadersymbol_match desc, longname_match desc;-
select distinct current_database() as database, s.symbolid, s.symbol, dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity, count(s.symbolid) filter (where s.symbol ILIKE '%MASTERCARD%') as symbol_match, count(s.symbolid) filter (where dss.downloadersymbol ILIKE '%MASTERCARD%') as downloadersymbol_match, count(s.symbolid) filter (where s.longname ilike '%MASTERCARD%') as longname_match, count(s.symbolid) filter (where dss.classname ilike '%MASTERCARD%') as classname_match, count(s.symbolid) filter (where s.exchange ilike '%MASTERCARD%') as exchange_match from symbols s join downloadersymbolsettings dss on s.symbolid = dss.symbolid where (s.symbol ILIKE '%MASTERCARD%' or downloadersymbol ilike '%MASTERCARD%' or s.shortname ilike '%MASTERCARD%' or s.longname ilike '%MASTERCARD%' or dss.classname ilike '%MASTERCARD%' or s.exchange ilike '%MASTERCARD%') and s.deleted = 0 GROUP BY s.symbolid, s.symbol, current_database(), dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity ORDER BY symbol_match DESC, downloadersymbol_match DESC, longname_match DESC;
Date: 2025-06-17 13:42:03 Duration: 442ms Database: acaweb_fx User: postgres Remote: 192.168.1.231 Application: PostgreSQL JDBC Driver
-
select distinct current_database() as database, s.symbolid, s.symbol, dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity, count(s.symbolid) filter (where s.symbol ILIKE '%AIG%') as symbol_match, count(s.symbolid) filter (where dss.downloadersymbol ILIKE '%AIG%') as downloadersymbol_match, count(s.symbolid) filter (where s.longname ilike '%AIG%') as longname_match, count(s.symbolid) filter (where dss.classname ilike '%AIG%') as classname_match, count(s.symbolid) filter (where s.exchange ilike '%AIG%') as exchange_match from symbols s join downloadersymbolsettings dss on s.symbolid = dss.symbolid where (s.symbol ILIKE '%AIG%' or downloadersymbol ilike '%AIG%' or s.shortname ilike '%AIG%' or s.longname ilike '%AIG%' or dss.classname ilike '%AIG%' or s.exchange ilike '%AIG%') and s.deleted = 0 GROUP BY s.symbolid, s.symbol, current_database(), dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity ORDER BY symbol_match DESC, downloadersymbol_match DESC, longname_match DESC;
Date: 2025-06-17 13:25:46 Duration: 425ms Database: acaweb_fx User: postgres Remote: 192.168.1.231 Application: PostgreSQL JDBC Driver
-
select distinct current_database() as database, s.symbolid, s.symbol, dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity, count(s.symbolid) filter (where s.symbol ILIKE '%Citigroup%') as symbol_match, count(s.symbolid) filter (where dss.downloadersymbol ILIKE '%Citigroup%') as downloadersymbol_match, count(s.symbolid) filter (where s.longname ilike '%Citigroup%') as longname_match, count(s.symbolid) filter (where dss.classname ilike '%Citigroup%') as classname_match, count(s.symbolid) filter (where s.exchange ilike '%Citigroup%') as exchange_match from symbols s join downloadersymbolsettings dss on s.symbolid = dss.symbolid where (s.symbol ILIKE '%Citigroup%' or downloadersymbol ilike '%Citigroup%' or s.shortname ilike '%Citigroup%' or s.longname ilike '%Citigroup%' or dss.classname ilike '%Citigroup%' or s.exchange ilike '%Citigroup%') and s.deleted = 0 GROUP BY s.symbolid, s.symbol, current_database(), dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity ORDER BY symbol_match DESC, downloadersymbol_match DESC, longname_match DESC;
Date: 2025-06-17 13:36:51 Duration: 408ms Database: acaweb_fx User: postgres Remote: 192.168.1.231 Application: PostgreSQL JDBC Driver
8 1 4.26 MiB 4.26 MiB 4.26 MiB 4.26 MiB select resultuid from relevance_fibonacci_results order by resultuid desc limit ?), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp)))), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;-
SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4, $5, $6, $7, $8, $9, $10)) AND ($11 = 0 OR s.exchange in ($12)) AND ($13 = 0 OR coalesce(bim.code, s.symbol) in ($14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226)) AND ($227 = 0 OR fr.pattern in ($228)) AND ($229 = 0 OR fr.patternlengthbars <= $230) AND ($231 = 0 OR ($232 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($233 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $234 OR relevant = 1) AND ($235 = 0 OR age <= $236) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:57:37 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver
Queries generating the largest temporary files
Rank Size Query 1 163.62 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 13:50:04 ]
2 122.08 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 13:00:09 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
3 98.38 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 13:20:05 ]
4 91.62 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 13:30:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
5 84.47 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 13:40:04 ]
6 80.30 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 13:30:07 ]
7 73.56 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: 2025-06-17 13:10:06 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
8 70.15 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 13:20:04 ]
9 69.81 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 13:10:05 ]
10 67.70 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 13:40:04 ]
11 59.04 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 13:00:07 ]
12 58.56 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: 2025-06-17 13:00:07 ]
13 54.50 MiB select updateageforrelevantresults ();[ Date: 2025-06-17 13:02:07 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
14 54.44 MiB select updateageforrelevantresults ();[ Date: 2025-06-17 13:32:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
15 54.35 MiB select updateageforrelevantresults ();[ Date: 2025-06-17 13:47:07 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
16 54.31 MiB select updateageforrelevantresults ();[ Date: 2025-06-17 13:17:07 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
17 53.32 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 13:40:04 ]
18 50.16 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 13:20:05 ]
19 48.80 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-06-17 13:40:04 ]
20 47.53 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2025-06-17 13:20:15 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
-
Vacuums
Vacuums / Analyzes Distribution
Key values
- 0 sec Highest CPU-cost vacuum
Table
Database - Date
- 0 sec Highest CPU-cost analyze
Table
Database - Date
Analyzes per table
Key values
- public.solr_relevance_old (17) Main table analyzed (database acaweb_fx)
- 57 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 17 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.public.relevance_autochartist_results 4 acaweb_fx.pg_catalog.pg_type 3 acaweb_fx.public.autochartist_symbolupdates 2 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.pg_catalog.pg_index 1 socialmedia.public.processes 1 acaweb_fx.pg_catalog.pg_depend 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.relevance_consecutivecandles_results 1 acaweb_fx.public.symbollatestupdatetime 1 Total 57 Vacuums per table
Key values
- public.solr_relevance_old (30) Main table vacuumed on database acaweb_fx
- 53 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 30 20 22,311 0 94 0 282 10,457 793 4,564,758 acaweb_fx.public.datafeeds_latestrun 5 0 557 0 37 0 0 90 47 94,639 acaweb_fx.pg_toast.pg_toast_2619 2 2 294 0 65 0 0 209 58 211,988 acaweb_fx.pg_catalog.pg_attribute 2 2 1,630 0 360 0 134 770 298 1,764,859 acaweb_fx.public.relevance_keylevels_results 2 2 8,261 0 315 2 147 2,200 297 791,049 acaweb_fx.public.relevance_autochartist_results 2 2 7,393 0 252 0 395 1,786 238 558,897 acaweb_fx.public.relevance_fibonacci_results 2 2 2,608 0 58 2 96 431 43 139,738 acaweb_fx.pg_catalog.pg_index 1 1 87 0 12 0 0 25 9 67,064 acaweb_fx.pg_catalog.pg_type 1 1 139 0 27 0 0 56 20 111,481 acaweb_fx.public.autochartist_symbolupdates 1 1 24,891 0 2,124 8 37,779 7,615 2,089 999,325 acaweb_fx.pg_catalog.pg_statistic 1 1 902 0 260 0 668 509 225 912,710 acaweb_fx.public.relevance_consecutivecandles_results 1 1 82 0 7 0 0 20 6 29,771 acaweb_fx.public.symbollatestupdatetime 1 1 1,807 0 154 0 589 1,157 154 431,702 acaweb_fx.public.latest_t15_candle_view 1 1 64 0 1 0 0 6 1 9,049 acaweb_fx.pg_catalog.pg_class 1 1 359 0 31 0 40 127 26 133,139 Total 53 38 71,385 46,355 3,797 12 40,130 25,458 4,304 10,820,169 Tuples removed per table
Key values
- public.solr_relevance_old (66380) Main table with removed tuples on database acaweb_fx
- 98369 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 30 20 66,380 267,228 82,762 0 6,574 acaweb_fx.public.symbollatestupdatetime 1 1 18,542 88,553 20 0 1,714 acaweb_fx.public.autochartist_symbolupdates 1 1 5,282 45,930 385 0 40,691 acaweb_fx.pg_catalog.pg_attribute 2 2 2,790 18,746 0 0 500 acaweb_fx.public.relevance_autochartist_results 2 2 2,326 17,398 0 0 760 acaweb_fx.public.relevance_keylevels_results 2 2 1,374 25,251 0 0 558 acaweb_fx.pg_catalog.pg_statistic 1 1 579 4,383 0 0 1,194 acaweb_fx.public.datafeeds_latestrun 5 0 296 77 2 0 80 acaweb_fx.public.relevance_fibonacci_results 2 2 266 3,021 0 0 204 acaweb_fx.pg_catalog.pg_type 1 1 169 1,341 3 0 38 acaweb_fx.pg_toast.pg_toast_2619 2 2 154 352 10 3 103 acaweb_fx.pg_catalog.pg_class 1 1 127 1,947 0 0 150 acaweb_fx.public.latest_t15_candle_view 1 1 62 14 0 0 1 acaweb_fx.public.relevance_consecutivecandles_results 1 1 20 248 0 0 7 acaweb_fx.pg_catalog.pg_index 1 1 2 813 0 0 22 Total 53 38 98,369 475,302 83,182 3 52,596 Pages removed per table
Key values
- pg_toast.pg_toast_2619 (3) Main table with removed pages on database acaweb_fx
- 3 pages Total removed
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_toast.pg_toast_2619 2 2 154 3 acaweb_fx.pg_catalog.pg_index 1 1 2 0 acaweb_fx.pg_catalog.pg_type 1 1 169 0 acaweb_fx.public.autochartist_symbolupdates 1 1 5282 0 acaweb_fx.public.datafeeds_latestrun 5 0 296 0 acaweb_fx.pg_catalog.pg_attribute 2 2 2790 0 acaweb_fx.pg_catalog.pg_statistic 1 1 579 0 acaweb_fx.public.relevance_consecutivecandles_results 1 1 20 0 acaweb_fx.public.symbollatestupdatetime 1 1 18542 0 acaweb_fx.public.latest_t15_candle_view 1 1 62 0 acaweb_fx.public.relevance_keylevels_results 2 2 1374 0 acaweb_fx.pg_catalog.pg_class 1 1 127 0 acaweb_fx.public.solr_relevance_old 30 20 66380 0 acaweb_fx.public.relevance_autochartist_results 2 2 2326 0 acaweb_fx.public.relevance_fibonacci_results 2 2 266 0 Total 53 38 98,369 3 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Jun 17 13 53 57 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
- 158,734 Total read queries
- 44,637 Total write queries
Queries by database
Key values
- acaweb_fx Main database
- 200,358 Requests
- 2h54m26s (acaweb_fx)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 200,358 2h54m26s copy from 96 5s861ms copy to 26 4s705ms cte 7,519 2h47m41s ddl 16 545ms delete 16 25ms insert 25,317 26s825ms others 4,635 8s793ms select 158,348 5m37s tcl 664 204ms update 3,721 20s678ms socialmedia Total 7,648 8s764ms insert 7,154 8s262ms select 386 285ms update 108 215ms Queries by user
Key values
- postgres Main user
- 208,006 Requests
User Request type Count Duration postgres Total 208,006 2h54m34s copy from 96 5s861ms copy to 26 4s705ms cte 7,519 2h47m41s ddl 16 545ms delete 16 25ms insert 32,471 35s88ms others 4,635 8s793ms select 158,734 5m37s tcl 664 204ms update 3,829 20s894ms Duration by user
Key values
- 2h54m34s (postgres) Main time consuming user
User Request type Count Duration postgres Total 208,006 2h54m34s copy from 96 5s861ms copy to 26 4s705ms cte 7,519 2h47m41s ddl 16 545ms delete 16 25ms insert 32,471 35s88ms others 4,635 8s793ms select 158,734 5m37s tcl 664 204ms update 3,829 20s894ms Queries by host
Key values
- 192.168.1.20 Main host
- 58,023 Requests
- 46m16s (192.168.1.15)
- Main time consuming host
Host Request type Count Duration 127.0.0.1 Total 16,111 43s747ms copy to 26 4s705ms cte 25 297ms insert 12,009 13s676ms others 36 0ms select 834 22s800ms update 3,181 2s266ms 182.165.1.42 Total 180 8m28s cte 60 8m28s select 120 163ms 192.168.0.114 Total 10 144ms others 2 0ms select 4 144ms tcl 4 0ms 192.168.0.21 Total 4 5ms select 4 5ms 192.168.0.216 Total 388 371ms others 194 21ms select 187 231ms update 7 118ms 192.168.0.239 Total 785 678ms select 785 678ms 192.168.0.42 Total 1,807 1s178ms insert 506 48ms select 1,301 1s130ms 192.168.0.74 Total 10,078 42m36s cte 1,718 42m32s others 1,072 12ms select 7,288 4s470ms 192.168.1.135 Total 272 776ms cte 9 367ms select 263 409ms 192.168.1.145 Total 57,896 34m37s cte 1,239 33m3s others 564 15ms select 56,093 1m34s 192.168.1.15 Total 29,703 46m16s cte 2,465 45m50s others 1,672 25ms select 25,566 25s928ms 192.168.1.20 Total 58,023 37m32s cte 1,249 36m1s others 628 10ms select 56,146 1m31s 192.168.1.201 Total 1,841 2s97ms select 1,841 2s97ms 192.168.1.210 Total 16 0ms select 16 0ms 192.168.1.23 Total 2,293 2s40ms select 2,293 2s40ms 192.168.1.231 Total 71 7s568ms others 40 0ms select 31 7s567ms 192.168.1.239 Total 56 36ms others 28 2ms select 28 33ms 192.168.1.90 Total 60 38s162ms cte 6 38s114ms others 8 0ms select 46 47ms 192.168.2.126 Total 80 68ms others 18 0ms select 62 67ms 192.168.2.182 Total 48 304ms others 24 2ms select 12 11ms update 12 290ms 192.168.2.205 Total 138 99ms insert 90 10ms others 24 2ms select 20 20ms update 4 66ms 192.168.2.82 Total 1,064 2s13ms insert 670 1s187ms others 96 10ms select 177 106ms update 121 708ms 192.168.3.199 Total 252 326ms others 126 13ms select 114 150ms update 12 163ms 192.168.4.142 Total 13,684 13s450ms insert 12,042 11s903ms select 1,642 1s546ms 192.168.4.150 Total 22 1s206ms others 21 0ms select 1 1s206ms 192.168.4.226 Total 3 34ms cte 1 34ms others 2 0ms 192.168.4.238 Total 48 26s917ms cte 16 26s917ms others 32 0ms 192.168.4.249 Total 4,079 2s551ms cte 635 2s11ms others 30 0ms select 3,414 539ms 192.168.4.33 Total 7,648 8s764ms insert 7,154 8s262ms select 386 285ms update 108 215ms 192.168.4.5 Total 12 0ms others 8 0ms select 4 0ms 192.168.4.98 Total 996 9s277ms others 6 8s345ms select 6 30ms tcl 660 204ms update 324 696ms [local] Total 338 2m21s copy from 96 5s861ms cte 96 37s709ms ddl 16 545ms delete 16 25ms others 4 328ms select 50 1m20s update 60 16s369ms Queries by application
Key values
- PostgreSQL JDBC Driver Main application
- 164,972 Requests
- 2h41m48s (PostgreSQL JDBC Driver)
- Main time consuming application
Application Request type Count Duration PostgreSQL JDBC Driver Total 164,972 2h41m48s cte 7,332 2h37m56s insert 506 48ms others 2,052 37ms select 155,082 3m51s [unknown] Total 42,583 10m19s cte 66 9m6s insert 31,965 35s39ms others 2,579 8s427ms select 3,550 25s422ms tcl 664 204ms update 3,759 4s504ms psql Total 451 2m26s copy from 96 5s861ms copy to 26 4s705ms cte 121 38s7ms ddl 16 545ms delete 16 25ms others 4 328ms select 102 1m20s update 70 16s389ms Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2025-06-17 13:09:09 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 113,530 0-1ms duration
Slowest individual queries
Rank Duration Query 1 49s649ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:42:20 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
2 46s268ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:31:50 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
3 45s803ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:42:24 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
4 43s215ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:31:46 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
5 40s709ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:25:58 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
6 37s943ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:47:40 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
7 33s795ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:07:53 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
8 33s361ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:36:58 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
9 33s210ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:17:40 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
10 32s749ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:12:38 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
11 31s983ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:36:54 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
12 31s953ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:01:44 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
13 31s925ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:26:54 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
14 30s548ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:52:25 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
15 30s473ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:47:48 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
16 30s282ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-06-17 13:31:00 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
17 30s2ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:13:04 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
18 29s903ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:59:54 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
19 29s888ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:59:35 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.74 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
20 29s659ms WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;[ Date: 2025-06-17 13:54:51 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.15 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
Time consuming queries
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 1h12m6s 490 370ms 30s282ms 8s829ms with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ), ar as ( select a.*, rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end ), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on sg.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jun 17 13 490 1h12m6s 8s829ms [ User: postgres - Total duration: 1h12m6s - Times executed: 490 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h8m11s - Times executed: 478 ]
[ Application: [unknown] - Total duration: 3m55s - Times executed: 12 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:31:00 Duration: 30s282ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:26:13 Duration: 29s481ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), 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: 2025-06-17 13:47:10 Duration: 27s95ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
2 1h6m46s 490 156ms 49s649ms 8s176ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Jun 17 13 490 1h6m46s 8s176ms [ User: postgres - Total duration: 1h6m46s - Times executed: 490 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h3m54s - Times executed: 478 ]
[ Application: [unknown] - Total duration: 2m51s - Times executed: 12 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-06-17 13:42:20 Duration: 49s649ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-06-17 13:31:50 Duration: 46s268ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-06-17 13:42:24 Duration: 45s803ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
3 23m16s 470 562ms 10s720ms 2s971ms with rar_max as ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ? ), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end ), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp))) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jun 17 13 470 23m16s 2s971ms [ User: postgres - Total duration: 23m16s - Times executed: 470 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 21m50s - Times executed: 458 ]
[ Application: [unknown] - Total duration: 1m26s - Times executed: 12 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR fr.pattern in ('')) AND ('0' = 0 OR fr.patternlengthbars <= '0') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:31:03 Duration: 10s720ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:31:01 Duration: 10s350ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR fr.pattern in ('')) AND ('0' = 0 OR fr.patternlengthbars <= '0') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:31:03 Duration: 10s104ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
4 2m43s 321 84ms 2s178ms 508ms with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Jun 17 13 321 2m43s 508ms [ User: postgres - Total duration: 2m43s - Times executed: 321 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m28s - Times executed: 309 ]
[ Application: [unknown] - Total duration: 14s866ms - Times executed: 12 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR ccr.patternlengthbars <= '0') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:26:00 Duration: 2s178ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR ccr.patternlengthbars <= '0') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:36:55 Duration: 1s801ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:56:10 Duration: 1s661ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
5 2m14s 36,287 0ms 39ms 3ms select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Jun 17 13 36,287 2m14s 3ms [ User: postgres - Total duration: 2m14s - Times executed: 36287 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m14s - Times executed: 36287 ]
-
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 = 'MRNA.US' OR dss.downloadersymbol = 'MRNA.US') AND dss.enabled = 1;
Date: 2025-06-17 13:00:06 Duration: 39ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'GBPAUD' OR dss.downloadersymbol = 'GBPAUD') AND dss.enabled = 1;
Date: 2025-06-17 13:00:06 Duration: 39ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'EURGBP' OR dss.downloadersymbol = 'EURGBP') AND dss.enabled = 1;
Date: 2025-06-17 13:45:06 Duration: 36ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
6 1m13s 47,229 0ms 38ms 1ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Jun 17 13 47,229 1m13s 1ms [ User: postgres - Total duration: 1m13s - Times executed: 47229 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m13s - Times executed: 47229 ]
-
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 = '538' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '538' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840233429886300';
Date: 2025-06-17 13:30:06 Duration: 38ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840248226448300';
Date: 2025-06-17 13:30:04 Duration: 32ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840249443362300';
Date: 2025-06-17 13:00:05 Duration: 30ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
7 53s884ms 135 90ms 1s34ms 399ms with last_candle as ( select acs.symbolid as symbolid, acs.latestpricedatetime as latest_candle_time, bsl.brokerid as broker_id, coalesce(bim.code, s.symbol) as symbol, bim.code as symbol_mapping, s.exchange as exchange, s.timegranularity as timegranularity from autochartist_symbolupdates acs inner join brokersymbollist bsl on acs.symbolid = bsl.symbolid inner join symbols s on acs.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bsl.brokerid = ? and s.deleted = ? and s.nonliquid = ? and acs.latestpricedatetime is not null ) select * from ( select lc.broker_id as brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / ?) + ? as sast_hh, mod(cast(psp.fromtime as int), ?) as sast_mm, current_timestamp as datetime, (powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice as closingprice, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / ?.?) as low_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / ?.?) as high_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / ?.?) as low_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / ?.?) as high_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / ?.?) as low_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / ?.?) as high_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / ?.?) as low_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / ?.?) as high_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / ?.?) as low_1440, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / ?.?) as high_1440, dtt.absolutetimezoneoffset as datafeedtimezoneoffset, dtt.timezone as datafeedtimezonename, (round((cast(? as float) - rank) / ? * ?)) as rank_rounded, ((cast(? as float) - rank) / ? * ?) as rank from last_candle lc inner join downloadersymbolsettings dss on lc.symbolid = dss.symbolid inner join datafeedstimetable dtt on trim(dss.classname) = trim(dtt.classname) and dtt.dayofweek = ? -- assuming timezone is same for whole week. inner join powerstats_symboldata psd on psd.symbolid = lc.symbolid left outer join powerstats_trumpet psp on psd.trumpetsymbolid = psp.symbolid and psp.dayofweek = extract(dow from lc.latest_candle_time) and psp.fromtime = cast(extract(? from lc.latest_candle_time) as integer) * ? + extract(? from (cast(extract(? from lc.latest_candle_time) as integer) / ?) * ? * interval ?) inner join prfsymboltree prf on psd.symbolid = prf.symbolid and date_trunc(?, prf.enddate) = date_trunc(?, psp.enddate) left join lateral ( select ph.hour, (ave + stddev) as volatility, rank() over (order by (ave + stddev) desc) as rank from powerstats_hourly ph where ph.symbolid = psd.hourlysymbolid and date_trunc(?,ph.enddate) = date_trunc(?, prf.enddate) ) rank_query on true where prf.brokerid = ? and rank_query.hour = floor((psp.fromtime) / ?) and volatility > ? order by rank desc, rank_rounded desc, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Jun 17 13 135 53s884ms 399ms [ User: postgres - Total duration: 53s884ms - Times executed: 135 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 53s884ms - Times executed: 135 ]
-
WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-06-17 13:36:10 Duration: 1s34ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-06-17 13:52:05 Duration: 1s21ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-06-17 13:36:10 Duration: 905ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
8 48s89ms 4 9s52ms 13s502ms 12s22ms select updateageforrelevantresults ();Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Jun 17 13 4 48s89ms 12s22ms [ User: postgres - Total duration: 48s89ms - Times executed: 4 ]
[ Application: psql - Total duration: 48s89ms - Times executed: 4 ]
-
select updateageforrelevantresults ();
Date: 2025-06-17 13:02:16 Duration: 13s502ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-06-17 13:47:15 Duration: 12s988ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-06-17 13:17:15 Duration: 12s545ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
9 38s114ms 6 4s665ms 9s290ms 6s352ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jun 17 13 6 38s114ms 6s352ms [ User: postgres - Total duration: 38s114ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 38s114ms - Times executed: 6 ]
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-17 13:00:12 Duration: 9s290ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-17 13:30:11 Duration: 8s859ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-17 13:50:08 Duration: 5s299ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
10 35s333ms 16 1s826ms 3s288ms 2s208ms with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Jun 17 13 16 35s333ms 2s208ms [ User: postgres - Total duration: 35s333ms - Times executed: 16 ]
[ Application: psql - Total duration: 35s333ms - Times executed: 16 ]
-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:26:16 Duration: 3s288ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:31:16 Duration: 3s176ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:01:16 Duration: 3s145ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 26s917ms 16 1s295ms 2s635ms 1s682ms with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = ? left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bg.brokerid and bim.type = ? where bg.brokerid = ? and basegroupname = ? and g.designation = ? and s.nonliquid = ? ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= ? and patternquality >= ?.? and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, case when direction > ? then ? else ? end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (...) and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= ? and _tmp.qtycandlesapart <= ? and ((cpresultuid > ( select coalesce(max(cpresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?)) or (klresultuid > ( select coalesce(max(klresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = ? and cs.basegroupname = ? and date_trunc(?, cs.gmttimefound) = date_trunc(?, now()) and sent is true and filtered is false ) <= ( select case when coalesce(daily_max, ?) < ? then ? else coalesce(daily_max,?) end from corr_sigs_config_v where broker_id = ? limit ? ) and extract(epoch from age(current_timestamp at time zone ?, max_patternendtime - absolutetimezoneoffset * interval ?))/? < mint*? ), maxstats as ( select max(statsid) as maxid , st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = ? then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * ? as numeric), ?) as percent, round(cast((kl_correct) / (kl_total) * ? as numeric), ?) as klpercent, round(cast((cp_correct ) / (cp_total ) * ? as numeric), ?) as cppercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), ?) as openprice, round(cast(sig.forecastprice as numeric), ?) as forecastprice, cast(round(cast(abs(sig.forecastprice - sig.openprice)/pip as numeric), ?)as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname , si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = ? then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = ? and date_part(?, sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = ? and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = ? and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = ? and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = ? and date_part(?, sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = ? and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = ? and kl_sym.name ilike si.symbol ) as tmp order by tmp.gmttimefound desc;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jun 17 13 16 26s917ms 1s682ms [ User: postgres - Total duration: 26s917ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 26s917ms - Times executed: 16 ]
-
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: 2025-06-17 13:22:15 Duration: 2s635ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
-
with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '617' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '617' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '617' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-06-17 13:21:56 Duration: 2s223ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
-
with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '627' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '627' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '627' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-06-17 13:22:07 Duration: 2s186ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
12 15s850ms 16 668ms 1s684ms 990ms update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jun 17 13 16 15s850ms 990ms [ User: postgres - Total duration: 15s850ms - Times executed: 16 ]
[ Application: psql - Total duration: 15s850ms - Times executed: 16 ]
-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:41:13 Duration: 1s684ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:26:13 Duration: 1s247ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:01:13 Duration: 1s242ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
13 14s797ms 194 16ms 327ms 76ms 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 #13
Day Hour Count Duration Avg duration Jun 17 13 194 14s797ms 76ms [ User: postgres - Total duration: 14s797ms - Times executed: 194 ]
[ Application: [unknown] - Total duration: 14s797ms - Times executed: 194 ]
-
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 'FPMARKETS - 1';
Date: 2025-06-17 13:30:46 Duration: 327ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-06-17 13:46:29 Duration: 307ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2025-06-17 13:30:56 Duration: 268ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
14 14s374ms 8 1s234ms 2s242ms 1s796ms select updateresultsmaterializedview ();Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Jun 17 13 8 14s374ms 1s796ms [ User: postgres - Total duration: 14s374ms - Times executed: 8 ]
[ Application: psql - Total duration: 14s374ms - Times executed: 8 ]
-
select updateresultsmaterializedview ();
Date: 2025-06-17 13:50:35 Duration: 2s242ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateresultsmaterializedview ();
Date: 2025-06-17 13:35:34 Duration: 2s218ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateresultsmaterializedview ();
Date: 2025-06-17 13:20:35 Duration: 2s212ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
15 14s306ms 34 12ms 5s232ms 420ms select fixcandlegaps (?, false);Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Jun 17 13 34 14s306ms 420ms [ User: postgres - Total duration: 14s306ms - Times executed: 34 ]
[ Application: psql - Total duration: 14s306ms - Times executed: 34 ]
-
select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-06-17 13:06:15 Duration: 5s232ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select fixcandlegaps ('ATFX', false);
Date: 2025-06-17 13:06:05 Duration: 1s700ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select fixcandlegaps ('PEPPERSTONE', false);
Date: 2025-06-17 13:06:08 Duration: 1s294ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
16 8s345ms 6 1s89ms 2s66ms 1s390ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Jun 17 13 6 8s345ms 1s390ms [ User: postgres - Total duration: 8s345ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 8s345ms - Times executed: 6 ]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-17 13:31:18 Duration: 2s66ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-17 13:01:18 Duration: 1s756ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-17 13:46:17 Duration: 1s168ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
17 8s162ms 6,193 0ms 27ms 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 #17
Day Hour Count Duration Avg duration Jun 17 13 6,193 8s162ms 1ms [ User: postgres - Total duration: 8s162ms - Times executed: 6193 ]
[ Application: [unknown] - Total duration: 8s162ms - Times executed: 6193 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 14:30:00', '2.14205', '2.14725', '2.13845', '2.13845', '623', '515840248032953300', '0', '2025-06-17 13:45:06.072', '2025-06-17 13:45:05.931') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '2.14205', high = '2.14725', low = '2.13845', close = '2.13845', volume = '623', bsf = '0', sastdatetimewritten = '2025-06-17 13:45:06.072', sastdatetimereceived = '2025-06-17 13:45:05.931';
Date: 2025-06-17 13:45:06 Duration: 27ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 13:45:00', '5197.89', '5199.55', '5193.32', '5198.96', '2018', '515840217486263300', '0', '2025-06-17 13:00:05.723', '2025-06-17 13:00:05.632') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '5197.89', high = '5199.55', low = '5193.32', close = '5198.96', volume = '2018', bsf = '0', sastdatetimewritten = '2025-06-17 13:00:05.723', sastdatetimereceived = '2025-06-17 13:00:05.632';
Date: 2025-06-17 13:00:05 Duration: 22ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 13:45:00', '3.278', '3.278', '3.274', '3.276', '14', '515840233365636300', '0', '2025-06-17 13:01:58.689', '2025-06-17 13:01:58.643') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '3.278', high = '3.278', low = '3.274', close = '3.276', volume = '14', bsf = '0', sastdatetimewritten = '2025-06-17 13:01:58.689', sastdatetimereceived = '2025-06-17 13:01:58.643';
Date: 2025-06-17 13:01:58 Duration: 22ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
18 7s725ms 194 16ms 199ms 39ms select distinct k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid from relevance_keylevels_results p inner join keylevels_results k on p.resultuid = k.resultuid inner join autochartist_stocklist asl on k.symbolid = asl.symbolid where k.patternclassid in (...) and asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Jun 17 13 194 7s725ms 39ms [ User: postgres - Total duration: 7s725ms - Times executed: 194 ]
[ Application: [unknown] - Total duration: 7s725ms - Times executed: 194 ]
-
SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'Alpari - 1';
Date: 2025-06-17 13:31:06 Duration: 199ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'GLOBALGTMT5 - 1';
Date: 2025-06-17 13:30:07 Duration: 179ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'GLOBALGTMT5 - 1';
Date: 2025-06-17 13:31:05 Duration: 147ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
19 7s696ms 6,786 0ms 12ms 1ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Jun 17 13 6,786 7s696ms 1ms [ User: postgres - Total duration: 7s696ms - Times executed: 6786 ]
[ Application: [unknown] - Total duration: 7s696ms - Times executed: 6786 ]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 52, schedule: 0 14 * * 1 Africa/Johannesburg', NULL, NULL);
Date: 2025-06-17 13:41:49 Duration: 12ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 38, schedule: 0 12 * * 1 Africa/Johannesburg', NULL, NULL);
Date: 2025-06-17 13:30:49 Duration: 9ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 95, schedule: 0 1 * * * Africa/Johannesburg', NULL, NULL);
Date: 2025-06-17 13:46:49 Duration: 8ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
20 7s567ms 31 122ms 442ms 244ms select distinct current_database() as database, s.symbolid, s.symbol, dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity, count(s.symbolid) filter (where s.symbol ilike ?) as symbol_match, count(s.symbolid) filter (where dss.downloadersymbol ilike ?) as downloadersymbol_match, count(s.symbolid) filter (where s.longname ilike ?) as longname_match, count(s.symbolid) filter (where dss.classname ilike ?) as classname_match, count(s.symbolid) filter (where s.exchange ilike ?) as exchange_match from symbols s join downloadersymbolsettings dss on s.symbolid = dss.symbolid where (s.symbol ilike ? or downloadersymbol ilike ? or s.shortname ilike ? or s.longname ilike ? or dss.classname ilike ? or s.exchange ilike ?) and s.deleted = ? group by s.symbolid, s.symbol, current_database(), dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity order by symbol_match desc, downloadersymbol_match desc, longname_match desc;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Jun 17 13 31 7s567ms 244ms [ User: postgres - Total duration: 7s567ms - Times executed: 31 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 7s567ms - Times executed: 31 ]
-
select distinct current_database() as database, s.symbolid, s.symbol, dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity, count(s.symbolid) filter (where s.symbol ILIKE '%MASTERCARD%') as symbol_match, count(s.symbolid) filter (where dss.downloadersymbol ILIKE '%MASTERCARD%') as downloadersymbol_match, count(s.symbolid) filter (where s.longname ilike '%MASTERCARD%') as longname_match, count(s.symbolid) filter (where dss.classname ilike '%MASTERCARD%') as classname_match, count(s.symbolid) filter (where s.exchange ilike '%MASTERCARD%') as exchange_match from symbols s join downloadersymbolsettings dss on s.symbolid = dss.symbolid where (s.symbol ILIKE '%MASTERCARD%' or downloadersymbol ilike '%MASTERCARD%' or s.shortname ilike '%MASTERCARD%' or s.longname ilike '%MASTERCARD%' or dss.classname ilike '%MASTERCARD%' or s.exchange ilike '%MASTERCARD%') and s.deleted = 0 GROUP BY s.symbolid, s.symbol, current_database(), dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity ORDER BY symbol_match DESC, downloadersymbol_match DESC, longname_match DESC;
Date: 2025-06-17 13:42:03 Duration: 442ms Database: acaweb_fx User: postgres Remote: 192.168.1.231 Application: PostgreSQL JDBC Driver Bind query: yes
-
select distinct current_database() as database, s.symbolid, s.symbol, dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity, count(s.symbolid) filter (where s.symbol ILIKE '%AIG%') as symbol_match, count(s.symbolid) filter (where dss.downloadersymbol ILIKE '%AIG%') as downloadersymbol_match, count(s.symbolid) filter (where s.longname ilike '%AIG%') as longname_match, count(s.symbolid) filter (where dss.classname ilike '%AIG%') as classname_match, count(s.symbolid) filter (where s.exchange ilike '%AIG%') as exchange_match from symbols s join downloadersymbolsettings dss on s.symbolid = dss.symbolid where (s.symbol ILIKE '%AIG%' or downloadersymbol ilike '%AIG%' or s.shortname ilike '%AIG%' or s.longname ilike '%AIG%' or dss.classname ilike '%AIG%' or s.exchange ilike '%AIG%') and s.deleted = 0 GROUP BY s.symbolid, s.symbol, current_database(), dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity ORDER BY symbol_match DESC, downloadersymbol_match DESC, longname_match DESC;
Date: 2025-06-17 13:25:46 Duration: 425ms Database: acaweb_fx User: postgres Remote: 192.168.1.231 Application: PostgreSQL JDBC Driver Bind query: yes
-
select distinct current_database() as database, s.symbolid, s.symbol, dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity, count(s.symbolid) filter (where s.symbol ILIKE '%Citigroup%') as symbol_match, count(s.symbolid) filter (where dss.downloadersymbol ILIKE '%Citigroup%') as downloadersymbol_match, count(s.symbolid) filter (where s.longname ilike '%Citigroup%') as longname_match, count(s.symbolid) filter (where dss.classname ilike '%Citigroup%') as classname_match, count(s.symbolid) filter (where s.exchange ilike '%Citigroup%') as exchange_match from symbols s join downloadersymbolsettings dss on s.symbolid = dss.symbolid where (s.symbol ILIKE '%Citigroup%' or downloadersymbol ilike '%Citigroup%' or s.shortname ilike '%Citigroup%' or s.longname ilike '%Citigroup%' or dss.classname ilike '%Citigroup%' or s.exchange ilike '%Citigroup%') and s.deleted = 0 GROUP BY s.symbolid, s.symbol, current_database(), dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity ORDER BY symbol_match DESC, downloadersymbol_match DESC, longname_match DESC;
Date: 2025-06-17 13:36:51 Duration: 408ms Database: acaweb_fx User: postgres Remote: 192.168.1.231 Application: PostgreSQL JDBC Driver Bind query: yes
Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 61,189 295ms 0ms 16ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jun 17 13 61,189 295ms 0ms [ User: postgres - Total duration: 295ms - Times executed: 61189 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 283ms - Times executed: 60953 ]
[ Application: [unknown] - Total duration: 12ms - Times executed: 236 ]
-
select 1;
Date: 2025-06-17 13:00:04 Duration: 16ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-06-17 13:45:05 Duration: 11ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2025-06-17 13:45:04 Duration: 8ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
2 47,229 1m13s 0ms 38ms 1ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Jun 17 13 47,229 1m13s 1ms [ User: postgres - Total duration: 1m13s - Times executed: 47229 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m13s - Times executed: 47229 ]
-
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 = '538' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '538' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840233429886300';
Date: 2025-06-17 13:30:06 Duration: 38ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840248226448300';
Date: 2025-06-17 13:30:04 Duration: 32ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840249443362300';
Date: 2025-06-17 13:00:05 Duration: 30ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
3 36,287 2m14s 0ms 39ms 3ms select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jun 17 13 36,287 2m14s 3ms [ User: postgres - Total duration: 2m14s - Times executed: 36287 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m14s - Times executed: 36287 ]
-
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 = 'MRNA.US' OR dss.downloadersymbol = 'MRNA.US') AND dss.enabled = 1;
Date: 2025-06-17 13:00:06 Duration: 39ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'GBPAUD' OR dss.downloadersymbol = 'GBPAUD') AND dss.enabled = 1;
Date: 2025-06-17 13:00:06 Duration: 39ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'EURGBP' OR dss.downloadersymbol = 'EURGBP') AND dss.enabled = 1;
Date: 2025-06-17 13:45:06 Duration: 36ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
4 6,786 7s696ms 0ms 12ms 1ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Jun 17 13 6,786 7s696ms 1ms [ User: postgres - Total duration: 7s696ms - Times executed: 6786 ]
[ Application: [unknown] - Total duration: 7s696ms - Times executed: 6786 ]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 52, schedule: 0 14 * * 1 Africa/Johannesburg', NULL, NULL);
Date: 2025-06-17 13:41:49 Duration: 12ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 38, schedule: 0 12 * * 1 Africa/Johannesburg', NULL, NULL);
Date: 2025-06-17 13:30:49 Duration: 9ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
-
INSERT INTO executionlogs (executionid, status, message, details, detailtype) VALUES (NULL, 'info', 'evaluating processid: 95, schedule: 0 1 * * * Africa/Johannesburg', NULL, NULL);
Date: 2025-06-17 13:46:49 Duration: 8ms Database: socialmedia User: postgres Remote: 192.168.4.33 Application: [unknown]
5 6,525 7s460ms 0ms 15ms 1ms insert into autochartist_results (resultid, symbolid, bandwidth, pattern, qtytp, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, relevancestartdistance, simulation, writtendatetime) values (?, ?, ?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Jun 17 13 6,525 7s460ms 1ms [ User: postgres - Total duration: 7s460ms - Times executed: 6525 ]
[ Application: [unknown] - Total duration: 7s460ms - Times executed: 6525 ]
-
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 ('515840246022907300-1|45820.7396|45824.7396|45821.4167|45825.4688|560.26|562.86|550.06|551.94', 515840246022907300, 3.000000000000000000000000000000, 'Channel Up', 4, '2025-06-17 11:13:14'::timestamp without time zone, 1, 0.462382903756393459600000000000, - 1.000000000000000000000000000000, 0.115497855275514510500000000000, 0.783963771501643980000000000000, 0.329790801169150549200000000000, 558.773956886820542400000000000000, 561.173496528369469200000000000000, '2025-06-17 14:00:00'::timestamp without time zone, '2025-06-20 00:07:30'::timestamp without time zone, '2025-06-12 13:15:00'::timestamp without time zone, '2025-06-17 14:00:00'::timestamp without time zone, 550.740000000000009100000000000000, 557.059999999999945400000000000000, '2025-06-12 17:45:00'::timestamp without time zone, '2025-06-16 17:45:00'::timestamp without time zone, '2025-06-13 10:00:00'::timestamp without time zone, '2025-06-17 11:15:00'::timestamp without time zone, 560.259999999999990900000000000000, 562.860000000000013600000000000000, 550.059999999999945400000000000000, 551.940000000000054600000000000000, 0.025753424657535741590000000000, 0.038235294117647394830000000000, 1.506182830380823790000000000000, 0.336069977807966657800000000000, 'Continuation', 0.000000000000000000000000000000, '2025-06-17 14:00:00'::timestamp without time zone, 557.059999999999945400000000000000, 87, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 13:17:39 Duration: 15ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('5158402439495203000.1753|45825.1458|45825.5208|45825|45825.4792|18.9371|18.9604|18.8849|18.9198', 515840243949520300, 2.000000000000000000000000000000, 'Channel Up', 4, '2025-06-17 11:26:22'::timestamp without time zone, - 1, 0.449411535380986826300000000000, 0.175345432948592727700000000000, 0.736138084381772639400000000000, 0.093563484758009962670000000000, 0.389945134387587766200000000000, 18.896011915579343560000000000000, 18.913574964824729110000000000000, '2025-06-17 14:00:00'::timestamp without time zone, '2025-06-17 21:00:00'::timestamp without time zone, '2025-06-16 23:00:00'::timestamp without time zone, '2025-06-17 14:00:00'::timestamp without time zone, 18.922019999999999840000000000000, 18.927366956521741060000000000000, '2025-06-17 03:30:00'::timestamp without time zone, '2025-06-17 12:30:00'::timestamp without time zone, '2025-06-17 00:00:00'::timestamp without time zone, '2025-06-17 11:30:00'::timestamp without time zone, 18.937120000000000180000000000000, 18.960409999999999540000000000000, 18.884879999999999000000000000000, 18.919779999999999380000000000000, 0.001517391304347842380000000000, 0.001293888888888853781000000000, 1.924130215970991431000000000000, 0.480284654489789353200000000000, 'Continuation', - 0.001246956521740116841000000000, '2025-06-17 14:00:00'::timestamp without time zone, 18.926120000000000940000000000000, 28, 0, 0.018368333333333691090000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 13:30:47 Duration: 14ms 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 ('515840233451602300-1|45824.7083|45825.3958|45825.125|45825.5417|0.8872|0.8881|0.8829|0.8852', 515840233451602300, 2.000000000000000000000000000000, 'Rising Wedge', 4, '2025-06-17 10:57:43'::timestamp without time zone, 1, 0.429031885955442116000000000000, - 1.000000000000000000000000000000, 0.423553810370291827800000000000, 0.215310454193834960300000000000, 0.560846943886891824400000000000, 0.887675434914223293600000000000, 0.889489043794136069400000000000, '2025-06-17 13:30:00'::timestamp without time zone, '2025-06-17 23:45:00'::timestamp without time zone, '2025-06-16 06:00:00'::timestamp without time zone, '2025-06-17 13:30:00'::timestamp without time zone, 0.879600000000000048500000000000, 0.886419999999999985700000000000, '2025-06-16 17:00:00'::timestamp without time zone, '2025-06-17 09:30:00'::timestamp without time zone, '2025-06-17 03:00:00'::timestamp without time zone, '2025-06-17 13:00:00'::timestamp without time zone, 0.887249999999999983100000000000, 0.888100000000000000600000000000, 0.882870000000000043600000000000, 0.885179999999999966800000000000, 0.000115499999999996166700000000, 0.000025757575757576283660000000, 2.448117006599695778000000000000, 0.591522791882832965600000000000, 'Continuation', 0.000000000000000000000000000000, '2025-06-17 13:30:00'::timestamp without time zone, 0.886379999999999945700000000000, 41, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 13:02:08 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
6 6,193 8s162ms 0ms 27ms 1ms insert into t15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Jun 17 13 6,193 8s162ms 1ms [ User: postgres - Total duration: 8s162ms - Times executed: 6193 ]
[ Application: [unknown] - Total duration: 8s162ms - Times executed: 6193 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 14:30:00', '2.14205', '2.14725', '2.13845', '2.13845', '623', '515840248032953300', '0', '2025-06-17 13:45:06.072', '2025-06-17 13:45:05.931') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '2.14205', high = '2.14725', low = '2.13845', close = '2.13845', volume = '623', bsf = '0', sastdatetimewritten = '2025-06-17 13:45:06.072', sastdatetimereceived = '2025-06-17 13:45:05.931';
Date: 2025-06-17 13:45:06 Duration: 27ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 13:45:00', '5197.89', '5199.55', '5193.32', '5198.96', '2018', '515840217486263300', '0', '2025-06-17 13:00:05.723', '2025-06-17 13:00:05.632') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '5197.89', high = '5199.55', low = '5193.32', close = '5198.96', volume = '2018', bsf = '0', sastdatetimewritten = '2025-06-17 13:00:05.723', sastdatetimereceived = '2025-06-17 13:00:05.632';
Date: 2025-06-17 13:00:05 Duration: 22ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 13:45:00', '3.278', '3.278', '3.274', '3.276', '14', '515840233365636300', '0', '2025-06-17 13:01:58.689', '2025-06-17 13:01:58.643') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '3.278', high = '3.278', low = '3.274', close = '3.276', volume = '14', bsf = '0', sastdatetimewritten = '2025-06-17 13:01:58.689', sastdatetimereceived = '2025-06-17 13:01:58.643';
Date: 2025-06-17 13:01:58 Duration: 22ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
7 3,558 2s431ms 0ms 29ms 0ms insert into t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Jun 17 13 3,558 2s431ms 0ms [ User: postgres - Total duration: 2s431ms - Times executed: 3558 ]
[ Application: [unknown] - Total duration: 2s431ms - Times executed: 3558 ]
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 13:30:00', '3393.56', '3398.54', '3392.58', '3398.31', '3122', '515840247906722300', '0', '2025-06-17 13:00:04.315', '2025-06-17 13:00:04.245') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '3393.56', high = '3398.54', low = '3392.58', close = '3398.31', volume = '3122', bsf = '0', sastdatetimewritten = '2025-06-17 13:00:04.315', sastdatetimereceived = '2025-06-17 13:00:04.245';
Date: 2025-06-17 13:00:04 Duration: 29ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 13:30:00', '16.41', '16.44', '16.41', '16.44', '12', '515840233428002300', '0', '2025-06-17 13:02:00.929', '2025-06-17 13:02:00.875') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '16.41', high = '16.44', low = '16.41', close = '16.44', volume = '12', bsf = '0', sastdatetimewritten = '2025-06-17 13:02:00.929', sastdatetimereceived = '2025-06-17 13:02:00.875';
Date: 2025-06-17 13:02:00 Duration: 11ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 14:00:00', '167.372', '167.396', '167.268', '167.292', '3769', '515840248011048300', '0', '2025-06-17 13:30:52.259', '2025-06-17 13:30:52.105') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '167.372', high = '167.396', low = '167.268', close = '167.292', volume = '3769', bsf = '0', sastdatetimewritten = '2025-06-17 13:30:52.259', sastdatetimereceived = '2025-06-17 13:30:52.105';
Date: 2025-06-17 13:30:52 Duration: 10ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
8 3,171 2s245ms 0ms 20ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Jun 17 13 3,171 2s245ms 0ms [ User: postgres - Total duration: 2s245ms - Times executed: 3171 ]
[ Application: [unknown] - Total duration: 2s245ms - Times executed: 3171 ]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-06-17 14:00:00', reason = 'Emerging pattern broke out in the wrong direction.' WHERE uniqueIndex = '500991627552434200-1|45820.75|45825.4167|45821.1667|45825.4583|93.906|94.831|92.304|94.442' and relevant = 1;
Date: 2025-06-17 13:30:58 Duration: 20ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-06-17 13:00:00', reason = 'Emerging pattern broke out in the wrong direction.' WHERE uniqueIndex = '605679104922063300-1|45824.125|45825.3333|45821.375|45824.6667|3451.255|3394.935|3408.6|3382.815' and relevant = 1;
Date: 2025-06-17 13:02:10 Duration: 8ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-06-17 13:00:00', reason = 'Approaching pattern wick broke through price level.' WHERE uniqueIndex = '|605679104925887300|1276.105|1|2025-06-17 12:00:00|2025-06-17 12:00:00|1|-1' and relevant = 1;
Date: 2025-06-17 13:02:07 Duration: 4ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
9 2,836 4s532ms 0ms 27ms 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 #9
Day Hour Count Duration Avg duration Jun 17 13 2,836 4s532ms 1ms [ User: postgres - Total duration: 4s532ms - Times executed: 2836 ]
[ Application: [unknown] - Total duration: 4s532ms - Times executed: 2836 ]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (7.000000000000000000000000000000, - 1, 1, '2025-06-17 11:26:33'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 208, 94.831000000000003070000000000000, '2025-06-17 10:00:00', '2025-06-11 15:00:00', '2025-06-11 02:00:00', '', '', '', '', '', '', '', 416, 94.954149999999998500000000000000, '2025-06-17 14:00:00'::timestamp without time zone, '2025-06-17 14:00:00', 0.000000000000000000000000000000, 0.123150000000000411900000000000, - 1, 500991627552434200, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|500991627552434200|94.831|1|2025-06-17 14:00:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-06-11 02:00:00', 94.831000000000003070000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 13:30:58 Duration: 27ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (3.000000000000000000000000000000, - 1, 1, '2025-06-17 11:26:31'::timestamp without time zone, '2025-06-17 14:00:00', 106.600000000000733300000000000000, 4, 98, 23573.150000000001460000000000000000, '2025-06-17 09:00:00', '2025-06-17 04:00:00', '2025-06-13 19:00:00', '2025-06-13 11:00:00', '', '', '', '', '', '', 220, 23591.380000000001020000000000000000, '2025-06-17 14:00:00'::timestamp without time zone, '2025-06-17 14:00:00', 23494.950000000000730000000000000000, 21.611499999999999490000000000000, 1, 604529010225161300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|604529010225161300|23573.15|1|2025-06-17 14:00:00|2025-06-17 14:00:00|1|-1', 23426.042000000001280000000000000000, 147.108000000000174600000000000000, 2, '2025-06-13 11:00:00', 23318.950000000000730000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 13:30:56 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (8.000000000000000000000000000000, - 1, 2, '2025-06-17 11:26:09'::timestamp without time zone, '', 0.500000000000000000000000000000, 4, 287, 5984.000000000000000000000000000000, '2025-06-17 13:45:00', '2025-06-17 10:15:00', '2025-06-12 14:45:00', '2025-06-12 11:00:00', '', '', '', '', '', '', 717, 5977.970999999999549000000000000000, '2025-06-17 14:15:00'::timestamp without time zone, '2025-06-17 14:15:00', 0.000000000000000000000000000000, 6.028999999999996362000000000000, 1, 515840238283769300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840238283769300|5984|2|2025-06-17 14:15:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-06-12 11:00:00', 5923.510000000000218000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 13:30:34 Duration: 9ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
10 2,579 1s492ms 0ms 7ms 0ms insert into fibonacci_results (bandwidth, pattern, gmttimefound, direction, patternstarttime, patternendtime, patternstartprice, patternendprice, qtytp, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, patternlengthbars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) values (?.?, ?, ?::timestamp without time zone, ?, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?, ?, ?, ?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Jun 17 13 2,579 1s492ms 0ms [ User: postgres - Total duration: 1s492ms - Times executed: 2579 ]
[ Application: [unknown] - Total duration: 1s492ms - Times executed: 2579 ]
-
INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, 'Gartley', '2025-06-17 11:41:46'::timestamp without time zone, - 1, '2025-06-17 00:00:00'::timestamp without time zone, '2025-06-17 11:30:00'::timestamp without time zone, 2.085195000000000132000000000000, - 1.000000000000000000000000000000, 5, 2.085195000000000132000000000000, '2025-06-17 00:00:00'::timestamp without time zone, 2.072979999999999823000000000000, '2025-06-17 08:30:00'::timestamp without time zone, 2.075584999999999791000000000000, '2025-06-17 09:00:00'::timestamp without time zone, 2.073545000000000194000000000000, '2025-06-17 11:30:00'::timestamp without time zone, 2.077645714828029622000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.674733331728113894200000000000, - 1.000000000000000000000000000000, 14.574521184110412980000000000000, 49, 2.073545000000000194000000000000, 2.075111333686341375000000000000, 2.071010618858311947000000000000, 2.074421932216009346000000000000, 2.072429524989780170000000000000, 2.075595357414014686000000000000, 2.076079381141688440000000000000, 515840249741960300, 0.650533336543772100500000000000, 'BC=0.786*AB (0.783) ', 0, 'Gartley|-1|2025-06-17 00:00:00|2.085195|-1|5|49|BC=0.786*AB (0.783)|0|515840249741960300|2025-06-17 00:00:00|2025-06-17 08:30:00|2025-06-17 09:00:00|2025-06-17 11:30:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 13:46:11 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (3.000000000000000000000000000000, '3 Point Extension', '2025-06-17 10:56:09'::timestamp without time zone, - 1, '2025-06-12 18:00:00'::timestamp without time zone, '2025-06-17 13:00:00'::timestamp without time zone, 8.090999999999999304000000000000, 8.105000000000000426000000000000, 3, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 8.090999999999999304000000000000, '2025-06-12 18:00:00'::timestamp without time zone, 7.940999999999999836000000000000, '2025-06-13 09:00:00'::timestamp without time zone, 8.130000000000000782000000000000, '2025-06-17 12:00:00'::timestamp without time zone, 0.310751038931176615200000000000, - 1.000000000000000000000000000000, 0.188985280293647500700000000000, 66, 7.940999999999999836000000000000, 8.013191576135699990000000000000, 7.824191576135699044000000000000, 7.981417389595799605000000000000, 7.889588286244499926000000000000, 8.035500000000000753000000000000, 8.057808423864299740000000000000, 515840217488541300, 0.567483202431294242400000000000, 'CD=1.272*BC (1.26) ', 0, '3 Point Extension|-1|2025-06-12 18:00:00|8.091|8.105|3|66|CD=1.272*BC (1.26)|0|515840217488541300|1899-12-29 00:00:00|1899-12-29 00:00:00|2025-06-12 18:00:00|2025-06-13 09:00:00|2025-06-17 12:00:00', 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 13:00:34 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (3.000000000000000000000000000000, 'ABCD', '2025-06-17 10:57:11'::timestamp without time zone, - 1, '2025-06-17 01:15:00'::timestamp without time zone, '2025-06-17 13:45:00'::timestamp without time zone, 0.531050000000000022000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.529259999999999952700000000000, '2025-06-17 03:00:00'::timestamp without time zone, 0.531789999999999985000000000000, '2025-06-17 10:00:00'::timestamp without time zone, 0.530240000000000044600000000000, '2025-06-17 12:45:00'::timestamp without time zone, 0.532770000000000076800000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.803391053391051213000000000000, - 1.000000000000000000000000000000, 25.738837897962145720000000000000, 67, 0.530240000000000044600000000000, 0.531206374008589055100000000000, 0.528676374008589022800000000000, 0.530781037014166012800000000000, 0.529551790286765022800000000000, 0.531505000000000116200000000000, 0.531803625991411066400000000000, 515840245860501300, 0.393217893217897573900000000000, 'BC=0.618*AB (0.613) ', 0, 'ABCD|-1|2025-06-17 01:15:00|0.53105|-1|4|67|BC=0.618*AB (0.613)|0|515840245860501300|1899-12-29 00:00:00|2025-06-17 03:00:00|2025-06-17 10:00:00|2025-06-17 12:45:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 13:01:36 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
11 2,467 3s452ms 0ms 23ms 1ms with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ) select a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, s.exchange, s.symbol, s.longname, s.shortname, breakout, dtt.timezone, patternstartprice, patternendprice, qtytp, newlevels.profit, newlevels.stop, newlevels.filtered, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern inner join rar_max rm on ? = ? left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid left join lateral calc_cp_signal (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jun 17 13 2,467 3s452ms 1ms [ User: postgres - Total duration: 3s452ms - Times executed: 2467 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s452ms - Times executed: 2467 ]
-
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 = '606306680155542301' 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 = '606306680155542301' OR a.resultuid = '606306680155542301') AND dtt.dayofweek = 3;
Date: 2025-06-17 13:15:05 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_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 = '606306914915549301' 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 = '606306914915549301' OR a.resultuid = '606306914915549301') AND dtt.dayofweek = 3;
Date: 2025-06-17 13:46:45 Duration: 20ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ) SELECT a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, CASE WHEN a.old_resultuid = '606307267039506301' 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 = '606307267039506301' OR a.resultuid = '606307267039506301') AND dtt.dayofweek = 3;
Date: 2025-06-17 13:56:26 Duration: 20ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
12 2,285 1s297ms 0ms 10ms 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 #12
Day Hour Count Duration Avg duration Jun 17 13 2,285 1s297ms 0ms [ User: postgres - Total duration: 1s297ms - Times executed: 2285 ]
[ Application: [unknown] - Total duration: 1s297ms - Times executed: 2285 ]
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 13:00:00', '2929.49', '2938.7', '2929.25', '2937.69', '11482', '515840247937295300', '0', '2025-06-17 13:00:04.502', '2025-06-17 13:00:04.407') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '2929.49', high = '2938.7', low = '2929.25', close = '2937.69', volume = '11482', bsf = '0', sastdatetimewritten = '2025-06-17 13:00:04.502', sastdatetimereceived = '2025-06-17 13:00:04.407';
Date: 2025-06-17 13:00:04 Duration: 10ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 13:00:00', '3385.6', '3398.54', '3385.14', '3398.31', '6691', '515840247906886300', '0', '2025-06-17 13:00:04.502', '2025-06-17 13:00:04.407') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '3385.6', high = '3398.54', low = '3385.14', close = '3398.31', volume = '6691', bsf = '0', sastdatetimewritten = '2025-06-17 13:00:04.502', sastdatetimereceived = '2025-06-17 13:00:04.407';
Date: 2025-06-17 13:00:04 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-06-17 13:00:00', '1.56729', '1.56898', '1.5672', '1.56897', '6251', '515840247897424300', '0', '2025-06-17 13:00:49.1', '2025-06-17 13:00:48.982') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '1.56729', high = '1.56898', low = '1.5672', close = '1.56897', volume = '6251', bsf = '0', sastdatetimewritten = '2025-06-17 13:00:49.1', sastdatetimereceived = '2025-06-17 13:00:48.982';
Date: 2025-06-17 13:00:49 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
13 2,067 27ms 0ms 5ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jun 17 13 2,067 27ms 0ms [ User: postgres - Total duration: 27ms - Times executed: 2067 ]
[ Application: [unknown] - Total duration: 27ms - Times executed: 2067 ]
-
SET extra_float_digits = 3;
Date: 2025-06-17 13:15:30 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2025-06-17 13:43:53 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2025-06-17 13:15:57 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: [unknown] Bind query: yes
14 2,041 37ms 0ms 6ms 0ms set application_name = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Jun 17 13 2,041 37ms 0ms [ User: postgres - Total duration: 37ms - Times executed: 2041 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 37ms - Times executed: 2041 ]
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-17 13:26:52 Duration: 6ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-17 13:26:55 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-17 13:27:46 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
15 1,982 1s747ms 0ms 18ms 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ) select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as ruid, s.symbolid as sid, s.symbol as sym, longname, shortname, exchange as e, timegranularity as tg, a.patternid as pid, a.direction as d, a.patternprice as pp, atbaridentified as pet, case when (x9 != ?) then x9 when (x8 != ?) then x8 when (x7 != ?) then x7 when (x6 != ?) then x6 when (x5 != ?) then x5 when (x4 != ?) then x4 when (x3 != ?) then x3 when (x2 != ?) then x2 end as pst, patternprice as patp, x0, x1, x2, case when (x3 != ?) then x3 else ? end as x3, case when (x4 != ?) then x4 else ? end as x4, case when (x5 != ?) then x5 else ? end as x5, case when (x6 != ?) then x6 else ? end as x6, case when (x7 != ?) then x7 else ? end as x7, case when (x8 != ?) then x8 else ? end as x8, errormargin as erm, breakoutprice as pe, breakoutbars as be, breakout, atbaridentified as atbar, atpriceidentified as atprice, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzos, dtt.timezone as timezone, approachingtimestamp as apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, furthestprice as fp, newlevels.filtered, a.uniquepointsvalue as upv, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from keylevels_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join hrspatterns p on a.patternid = p.patternid inner join rar_max rm on ? = ? left outer join relevance_keylevels_results rar on a.resultuid = rar.resultuid left join lateral calc_kl_signal_filter (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Jun 17 13 1,982 1s747ms 0ms [ User: postgres - Total duration: 1s747ms - Times executed: 1982 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s747ms - Times executed: 1982 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '606307024893296303' 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 = '606307024893296303' OR a.resultuid = '606307024893296303') AND dtt.dayofweek = 3;
Date: 2025-06-17 13:41:39 Duration: 18ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '606307144628025303' 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 = '606307144628025303' OR a.resultuid = '606307144628025303') AND dtt.dayofweek = 3;
Date: 2025-06-17 13:47:04 Duration: 18ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '606307153079440303' 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 = '606307153079440303' OR a.resultuid = '606307153079440303') AND dtt.dayofweek = 3;
Date: 2025-06-17 13:31:02 Duration: 18ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
16 1,548 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 #16
Day Hour Count Duration Avg duration Jun 17 13 1,548 15ms 0ms [ User: postgres - Total duration: 15ms - Times executed: 1548 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 15ms - Times executed: 1548 ]
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-06-17 13:13:59 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.249 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-06-17 13:14:17 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.249 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-06-17 13:14:45 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.249 Application: PostgreSQL JDBC Driver Bind query: yes
17 1,024 468ms 0ms 17ms 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars as length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternstartprice, resy1, supporty1, dtt.timezone, cps.pip, newlevels.profit from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern left join currencypips cps on cps.symbol = s.symbol left join lateral calc_cp_signal (a.resultuid) newlevels on true where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Jun 17 13 1,024 468ms 0ms [ User: postgres - Total duration: 468ms - Times executed: 1024 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 468ms - Times executed: 1024 ]
-
SELECT CASE WHEN a.old_resultuid = '606306917650345301' 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 = '606306917650345301' OR a.resultuid = '606306917650345301') AND dtt.dayofweek = 3;
Date: 2025-06-17 13:26:09 Duration: 17ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT CASE WHEN a.old_resultuid = '606307262370223301' 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 = '606307262370223301' OR a.resultuid = '606307262370223301') AND dtt.dayofweek = 3;
Date: 2025-06-17 13:36:00 Duration: 8ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT CASE WHEN a.old_resultuid = '606307149339198301' 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 = '606307149339198301' OR a.resultuid = '606307149339198301') AND dtt.dayofweek = 3;
Date: 2025-06-17 13:15:44 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
18 804 1s378ms 0ms 11ms 1ms select s.symbolid, dss.downloadfrequency, dss.downloadersymbol from downloadersymbolsettings dss inner join symbols s on dss.symbolid = s.symbolid where dss.classname = ? and s.deleted = ? and dss.enabled = ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Jun 17 13 804 1s378ms 1ms [ User: postgres - Total duration: 1s378ms - Times executed: 804 ]
[ Application: [unknown] - Total duration: 1s378ms - Times executed: 804 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'MILLENNIUMPF' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-17 13:30:56 Duration: 11ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'PEPPERSTONE' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-17 13:45:05 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'GLOBALGTMT5' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-17 13:30:03 Duration: 6ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
19 804 163ms 0ms 0ms 0ms select downloadersymbol, spike_threshold from price_datafeed_spike_threshold where classname = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Jun 17 13 804 163ms 0ms [ User: postgres - Total duration: 163ms - Times executed: 804 ]
[ Application: [unknown] - Total duration: 163ms - Times executed: 804 ]
-
SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'MILLENNIUMPF';
Date: 2025-06-17 13:00:49 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'PEPPERSTONE';
Date: 2025-06-17 13:46:02 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'PEPPERSTONE';
Date: 2025-06-17 13:45:54 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
20 700 24ms 0ms 0ms 0ms select df.absolutetimezoneoffset from datafeedstimetable df inner join downloadersymbolsettings dss on df.classname = dss.classname where dss.symbolid = ? group by df.absolutetimezoneoffset limit ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Jun 17 13 700 24ms 0ms [ User: postgres - Total duration: 24ms - Times executed: 700 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 24ms - Times executed: 700 ]
-
SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '515840243281880300' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-06-17 13:48:45 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '515840248626964300' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-06-17 13:49:41 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '500991628230657200' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-06-17 13:02:31 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.239 Application: PostgreSQL JDBC Driver Bind query: yes
Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 9s52ms 13s502ms 12s22ms 4 48s89ms select updateageforrelevantresults ();Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jun 17 13 4 48s89ms 12s22ms [ User: postgres - Total duration: 48s89ms - Times executed: 4 ]
[ Application: psql - Total duration: 48s89ms - Times executed: 4 ]
-
select updateageforrelevantresults ();
Date: 2025-06-17 13:02:16 Duration: 13s502ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-06-17 13:47:15 Duration: 12s988ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-06-17 13:17:15 Duration: 12s545ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
2 370ms 30s282ms 8s829ms 490 1h12m6s with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ), ar as ( select a.*, rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end ), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on sg.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Jun 17 13 490 1h12m6s 8s829ms [ User: postgres - Total duration: 1h12m6s - Times executed: 490 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h8m11s - Times executed: 478 ]
[ Application: [unknown] - Total duration: 3m55s - Times executed: 12 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:31:00 Duration: 30s282ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:26:13 Duration: 29s481ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), 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: 2025-06-17 13:47:10 Duration: 27s95ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
3 156ms 49s649ms 8s176ms 490 1h6m46s with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jun 17 13 490 1h6m46s 8s176ms [ User: postgres - Total duration: 1h6m46s - Times executed: 490 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h3m54s - Times executed: 478 ]
[ Application: [unknown] - Total duration: 2m51s - Times executed: 12 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-06-17 13:42:20 Duration: 49s649ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-06-17 13:31:50 Duration: 46s268ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-06-17 13:42:24 Duration: 45s803ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
4 4s665ms 9s290ms 6s352ms 6 38s114ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Jun 17 13 6 38s114ms 6s352ms [ User: postgres - Total duration: 38s114ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 38s114ms - Times executed: 6 ]
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-17 13:00:12 Duration: 9s290ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-17 13:30:11 Duration: 8s859ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-17 13:50:08 Duration: 5s299ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
5 562ms 10s720ms 2s971ms 470 23m16s with rar_max as ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ? ), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end ), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp))) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Jun 17 13 470 23m16s 2s971ms [ User: postgres - Total duration: 23m16s - Times executed: 470 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 21m50s - Times executed: 458 ]
[ Application: [unknown] - Total duration: 1m26s - Times executed: 12 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR fr.pattern in ('')) AND ('0' = 0 OR fr.patternlengthbars <= '0') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:31:03 Duration: 10s720ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:31:01 Duration: 10s350ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR fr.pattern in ('')) AND ('0' = 0 OR fr.patternlengthbars <= '0') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:31:03 Duration: 10s104ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
6 1s826ms 3s288ms 2s208ms 16 35s333ms with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Jun 17 13 16 35s333ms 2s208ms [ User: postgres - Total duration: 35s333ms - Times executed: 16 ]
[ Application: psql - Total duration: 35s333ms - Times executed: 16 ]
-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:26:16 Duration: 3s288ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:31:16 Duration: 3s176ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:01:16 Duration: 3s145ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
7 1s234ms 2s242ms 1s796ms 8 14s374ms select updateresultsmaterializedview ();Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Jun 17 13 8 14s374ms 1s796ms [ User: postgres - Total duration: 14s374ms - Times executed: 8 ]
[ Application: psql - Total duration: 14s374ms - Times executed: 8 ]
-
select updateresultsmaterializedview ();
Date: 2025-06-17 13:50:35 Duration: 2s242ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateresultsmaterializedview ();
Date: 2025-06-17 13:35:34 Duration: 2s218ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateresultsmaterializedview ();
Date: 2025-06-17 13:20:35 Duration: 2s212ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
8 1s295ms 2s635ms 1s682ms 16 26s917ms with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = ? left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bg.brokerid and bim.type = ? where bg.brokerid = ? and basegroupname = ? and g.designation = ? and s.nonliquid = ? ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = ? and cp.direction > ? and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = ? and cp.direction < ? and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= ? and patternquality >= ?.? and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval ?) as predictiontimefrom, predictionpricefrom, case when direction > ? then ? else ? end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (...) and patternendtime >= current_timestamp - interval ? and patternlengthbars < ?) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= ? and _tmp.qtycandlesapart <= ? and ((cpresultuid > ( select coalesce(max(cpresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?)) or (klresultuid > ( select coalesce(max(klresultuid), ?) from correlating_signals acs where acs.basegroupname = ? and acs.brokerid = ?))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = ? and cs.basegroupname = ? and date_trunc(?, cs.gmttimefound) = date_trunc(?, now()) and sent is true and filtered is false ) <= ( select case when coalesce(daily_max, ?) < ? then ? else coalesce(daily_max,?) end from corr_sigs_config_v where broker_id = ? limit ? ) and extract(epoch from age(current_timestamp at time zone ?, max_patternendtime - absolutetimezoneoffset * interval ?))/? < mint*? ), maxstats as ( select max(statsid) as maxid , st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = ? then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * ? as numeric), ?) as percent, round(cast((kl_correct) / (kl_total) * ? as numeric), ?) as klpercent, round(cast((cp_correct ) / (cp_total ) * ? as numeric), ?) as cppercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), ?) as openprice, round(cast(sig.forecastprice as numeric), ?) as forecastprice, cast(round(cast(abs(sig.forecastprice - sig.openprice)/pip as numeric), ?)as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname , si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = ? then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = ? and date_part(?, sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = ? and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = ? and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = ? and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = ? and date_part(?, sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = ? and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = ? and kl_sym.name ilike si.symbol ) as tmp order by tmp.gmttimefound desc;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Jun 17 13 16 26s917ms 1s682ms [ User: postgres - Total duration: 26s917ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 26s917ms - Times executed: 16 ]
-
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: 2025-06-17 13:22:15 Duration: 2s635ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
-
with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '617' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '617' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '617' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-06-17 13:21:56 Duration: 2s223ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
-
with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '627' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '627'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '627' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '627' limit 1) and extract(epoch from age(current_timestamp at TIME ZONE 'utc', max_patternendtime - absolutetimezoneoffset * INTERVAL '1 hour')) / 60 < mint * 3 ), maxstats as ( select MAX(statsid) as maxid, st.brokerid, st.groupingname, st.groupingtype from stats st inner join sym_info si on st.brokerid = si.brokerid and case when st.groupingtype = 'exchange' then st.groupingname ilike si.exchange else st.groupingname ilike si.basegroupname end group by st.groupingname, st.brokerid, st.groupingtype ) select *, round(cast((cp_correct + kl_correct) / (cp_total + kl_total) * 100 as numeric), 2) as percent, round(cast((kl_correct) / (kl_total) * 100 as numeric), 2) as klPercent, round(cast((cp_correct) / (cp_total) * 100 as numeric), 2) as cpPercent from ( select sig.cpresultuid, sig.klresultuid, sig.cpsymbolid, si.symbol, sig.cpt, sig.klt, sig.direction, sig.cppatternname, sig.klpatternname, round(cast(sig.openprice as numeric), 5) as openprice, round(cast(sig.forecastprice as numeric), 5) as forecastprice, CAST(round(cast(abs(sig.forecastprice - sig.openprice) / pip as numeric), 0) as int) as forecastpips, sig.predictiontimefrom, sig.gmttimefound, si.brokerid, ms.groupingname, si.basegroupname, si.symbolname, cast(cp_sym.correct + cp_patt.correct + cp_interval.correct + cp_hod.correct as float) as cp_correct, cast(cp_hod.total + cp_sym.total + cp_patt.total + cp_interval.total as float) as cp_total, cast(kl_sym.correct + kl_interval.correct + kl_hod.correct as float) as kl_correct, cast(kl_hod.total + kl_sym.total + kl_interval.total as float) as kl_total from signals sig inner join sym_info si on sig.cpsymbolid = si.symbolid inner join maxstats ms on case when ms.groupingtype = 'exchange' then ms.groupingname ilike si.exchange else ms.groupingname ilike si.basegroupname end -- cp stats inner join stats_summary cp_hod on cp_hod.statsid = ms.maxid and cp_hod.category = 'hourofday' and date_part('hour', sig.cppet) = cast(cp_hod.name as int) inner join stats_summary cp_interval on cp_interval.statsid = ms.maxid and cp_interval.category = 'interval' and sig.cpt = cast(cp_interval.name as int) inner join stats_summary cp_patt on cp_patt.statsid = ms.maxid and cp_patt.category = 'pattern' and cp_patt.name ilike sig.cppatternname inner join stats_summary cp_sym on cp_sym.statsid = ms.maxid and cp_sym.category = 'symbol' and cp_sym.name ilike si.symbol -- kl stats inner join stats_hrs_summary kl_hod on kl_hod.statsid = ms.maxid and kl_hod.category = 'hourofday' and date_part('hour', sig.klpet) = cast(kl_hod.name as int) inner join stats_hrs_summary kl_interval on kl_interval.statsid = ms.maxid and kl_interval.category = 'interval' and sig.klt = cast(kl_interval.name as int) inner join stats_hrs_summary kl_sym on kl_sym.statsid = ms.maxid and kl_sym.category = 'symbol' and kl_sym.name ilike si.symbol) AS tmp order by tmp.gmttimefound desc;
Date: 2025-06-17 13:22:07 Duration: 2s186ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
9 1s89ms 2s66ms 1s390ms 6 8s345ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jun 17 13 6 8s345ms 1s390ms [ User: postgres - Total duration: 8s345ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 8s345ms - Times executed: 6 ]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-17 13:31:18 Duration: 2s66ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-17 13:01:18 Duration: 1s756ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-06-17 13:46:17 Duration: 1s168ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
10 668ms 1s684ms 990ms 16 15s850ms update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Jun 17 13 16 15s850ms 990ms [ User: postgres - Total duration: 15s850ms - Times executed: 16 ]
[ Application: psql - Total duration: 15s850ms - Times executed: 16 ]
-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:41:13 Duration: 1s684ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:26:13 Duration: 1s247ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-06-17 13:01:13 Duration: 1s242ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 84ms 2s178ms 508ms 321 2m43s 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 #11
Day Hour Count Duration Avg duration Jun 17 13 321 2m43s 508ms [ User: postgres - Total duration: 2m43s - Times executed: 321 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m28s - Times executed: 309 ]
[ Application: [unknown] - Total duration: 14s866ms - Times executed: 12 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR ccr.patternlengthbars <= '0') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:26:00 Duration: 2s178ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR ccr.patternlengthbars <= '0') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:36:55 Duration: 1s801ms Database: acaweb_fx User: postgres Remote: 192.168.0.74 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-06-17 13:56:10 Duration: 1s661ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
12 12ms 5s232ms 420ms 34 14s306ms select fixcandlegaps (?, false);Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jun 17 13 34 14s306ms 420ms [ User: postgres - Total duration: 14s306ms - Times executed: 34 ]
[ Application: psql - Total duration: 14s306ms - Times executed: 34 ]
-
select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-06-17 13:06:15 Duration: 5s232ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select fixcandlegaps ('ATFX', false);
Date: 2025-06-17 13:06:05 Duration: 1s700ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select fixcandlegaps ('PEPPERSTONE', false);
Date: 2025-06-17 13:06:08 Duration: 1s294ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
13 90ms 1s34ms 399ms 135 53s884ms with last_candle as ( select acs.symbolid as symbolid, acs.latestpricedatetime as latest_candle_time, bsl.brokerid as broker_id, coalesce(bim.code, s.symbol) as symbol, bim.code as symbol_mapping, s.exchange as exchange, s.timegranularity as timegranularity from autochartist_symbolupdates acs inner join brokersymbollist bsl on acs.symbolid = bsl.symbolid inner join symbols s on acs.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bsl.brokerid = ? and s.deleted = ? and s.nonliquid = ? and acs.latestpricedatetime is not null ) select * from ( select lc.broker_id as brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / ?) + ? as sast_hh, mod(cast(psp.fromtime as int), ?) as sast_mm, current_timestamp as datetime, (powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice as closingprice, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / ?.?) as low_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / ?.?) as high_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / ?.?) as low_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / ?.?) as high_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / ?.?) as low_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / ?.?) as high_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / ?.?) as low_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / ?.?) as high_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / ?.?) as low_1440, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / ?.?) as high_1440, dtt.absolutetimezoneoffset as datafeedtimezoneoffset, dtt.timezone as datafeedtimezonename, (round((cast(? as float) - rank) / ? * ?)) as rank_rounded, ((cast(? as float) - rank) / ? * ?) as rank from last_candle lc inner join downloadersymbolsettings dss on lc.symbolid = dss.symbolid inner join datafeedstimetable dtt on trim(dss.classname) = trim(dtt.classname) and dtt.dayofweek = ? -- assuming timezone is same for whole week. inner join powerstats_symboldata psd on psd.symbolid = lc.symbolid left outer join powerstats_trumpet psp on psd.trumpetsymbolid = psp.symbolid and psp.dayofweek = extract(dow from lc.latest_candle_time) and psp.fromtime = cast(extract(? from lc.latest_candle_time) as integer) * ? + extract(? from (cast(extract(? from lc.latest_candle_time) as integer) / ?) * ? * interval ?) inner join prfsymboltree prf on psd.symbolid = prf.symbolid and date_trunc(?, prf.enddate) = date_trunc(?, psp.enddate) left join lateral ( select ph.hour, (ave + stddev) as volatility, rank() over (order by (ave + stddev) desc) as rank from powerstats_hourly ph where ph.symbolid = psd.hourlysymbolid and date_trunc(?,ph.enddate) = date_trunc(?, prf.enddate) ) rank_query on true where prf.brokerid = ? and rank_query.hour = floor((psp.fromtime) / ?) and volatility > ? order by rank desc, rank_rounded desc, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jun 17 13 135 53s884ms 399ms [ User: postgres - Total duration: 53s884ms - Times executed: 135 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 53s884ms - Times executed: 135 ]
-
WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-06-17 13:36:10 Duration: 1s34ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-06-17 13:52:05 Duration: 1s21ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-06-17 13:36:10 Duration: 905ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
14 122ms 442ms 244ms 31 7s567ms select distinct current_database() as database, s.symbolid, s.symbol, dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity, count(s.symbolid) filter (where s.symbol ilike ?) as symbol_match, count(s.symbolid) filter (where dss.downloadersymbol ilike ?) as downloadersymbol_match, count(s.symbolid) filter (where s.longname ilike ?) as longname_match, count(s.symbolid) filter (where dss.classname ilike ?) as classname_match, count(s.symbolid) filter (where s.exchange ilike ?) as exchange_match from symbols s join downloadersymbolsettings dss on s.symbolid = dss.symbolid where (s.symbol ilike ? or downloadersymbol ilike ? or s.shortname ilike ? or s.longname ilike ? or dss.classname ilike ? or s.exchange ilike ?) and s.deleted = ? group by s.symbolid, s.symbol, current_database(), dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity order by symbol_match desc, downloadersymbol_match desc, longname_match desc;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Jun 17 13 31 7s567ms 244ms [ User: postgres - Total duration: 7s567ms - Times executed: 31 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 7s567ms - Times executed: 31 ]
-
select distinct current_database() as database, s.symbolid, s.symbol, dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity, count(s.symbolid) filter (where s.symbol ILIKE '%MASTERCARD%') as symbol_match, count(s.symbolid) filter (where dss.downloadersymbol ILIKE '%MASTERCARD%') as downloadersymbol_match, count(s.symbolid) filter (where s.longname ilike '%MASTERCARD%') as longname_match, count(s.symbolid) filter (where dss.classname ilike '%MASTERCARD%') as classname_match, count(s.symbolid) filter (where s.exchange ilike '%MASTERCARD%') as exchange_match from symbols s join downloadersymbolsettings dss on s.symbolid = dss.symbolid where (s.symbol ILIKE '%MASTERCARD%' or downloadersymbol ilike '%MASTERCARD%' or s.shortname ilike '%MASTERCARD%' or s.longname ilike '%MASTERCARD%' or dss.classname ilike '%MASTERCARD%' or s.exchange ilike '%MASTERCARD%') and s.deleted = 0 GROUP BY s.symbolid, s.symbol, current_database(), dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity ORDER BY symbol_match DESC, downloadersymbol_match DESC, longname_match DESC;
Date: 2025-06-17 13:42:03 Duration: 442ms Database: acaweb_fx User: postgres Remote: 192.168.1.231 Application: PostgreSQL JDBC Driver Bind query: yes
-
select distinct current_database() as database, s.symbolid, s.symbol, dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity, count(s.symbolid) filter (where s.symbol ILIKE '%AIG%') as symbol_match, count(s.symbolid) filter (where dss.downloadersymbol ILIKE '%AIG%') as downloadersymbol_match, count(s.symbolid) filter (where s.longname ilike '%AIG%') as longname_match, count(s.symbolid) filter (where dss.classname ilike '%AIG%') as classname_match, count(s.symbolid) filter (where s.exchange ilike '%AIG%') as exchange_match from symbols s join downloadersymbolsettings dss on s.symbolid = dss.symbolid where (s.symbol ILIKE '%AIG%' or downloadersymbol ilike '%AIG%' or s.shortname ilike '%AIG%' or s.longname ilike '%AIG%' or dss.classname ilike '%AIG%' or s.exchange ilike '%AIG%') and s.deleted = 0 GROUP BY s.symbolid, s.symbol, current_database(), dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity ORDER BY symbol_match DESC, downloadersymbol_match DESC, longname_match DESC;
Date: 2025-06-17 13:25:46 Duration: 425ms Database: acaweb_fx User: postgres Remote: 192.168.1.231 Application: PostgreSQL JDBC Driver Bind query: yes
-
select distinct current_database() as database, s.symbolid, s.symbol, dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity, count(s.symbolid) filter (where s.symbol ILIKE '%Citigroup%') as symbol_match, count(s.symbolid) filter (where dss.downloadersymbol ILIKE '%Citigroup%') as downloadersymbol_match, count(s.symbolid) filter (where s.longname ilike '%Citigroup%') as longname_match, count(s.symbolid) filter (where dss.classname ilike '%Citigroup%') as classname_match, count(s.symbolid) filter (where s.exchange ilike '%Citigroup%') as exchange_match from symbols s join downloadersymbolsettings dss on s.symbolid = dss.symbolid where (s.symbol ILIKE '%Citigroup%' or downloadersymbol ilike '%Citigroup%' or s.shortname ilike '%Citigroup%' or s.longname ilike '%Citigroup%' or dss.classname ilike '%Citigroup%' or s.exchange ilike '%Citigroup%') and s.deleted = 0 GROUP BY s.symbolid, s.symbol, current_database(), dss.downloadersymbol, s.shortname, s.longname, s.exchange, dss.classname, dss.enabled, s.nonliquid, s.timegranularity ORDER BY symbol_match DESC, downloadersymbol_match DESC, longname_match DESC;
Date: 2025-06-17 13:36:51 Duration: 408ms Database: acaweb_fx User: postgres Remote: 192.168.1.231 Application: PostgreSQL JDBC Driver Bind query: yes
15 16ms 327ms 76ms 194 14s797ms select distinct a.symbolid, p.resultuid, case when a.breakout >= ? then ? else ? end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient from relevance_autochartist_results p inner join autochartist_results a on p.resultuid = a.resultuid inner join autochartist_stocklist asl on a.symbolid = asl.symbolid where asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Jun 17 13 194 14s797ms 76ms [ User: postgres - Total duration: 14s797ms - Times executed: 194 ]
[ Application: [unknown] - Total duration: 14s797ms - Times executed: 194 ]
-
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 'FPMARKETS - 1';
Date: 2025-06-17 13:30:46 Duration: 327ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'AXIORY - 1';
Date: 2025-06-17 13:46:29 Duration: 307ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2025-06-17 13:30:56 Duration: 268ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
16 16ms 199ms 39ms 194 7s725ms select distinct k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid from relevance_keylevels_results p inner join keylevels_results k on p.resultuid = k.resultuid inner join autochartist_stocklist asl on k.symbolid = asl.symbolid where k.patternclassid in (...) and asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Jun 17 13 194 7s725ms 39ms [ User: postgres - Total duration: 7s725ms - Times executed: 194 ]
[ Application: [unknown] - Total duration: 7s725ms - Times executed: 194 ]
-
SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'Alpari - 1';
Date: 2025-06-17 13:31:06 Duration: 199ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'GLOBALGTMT5 - 1';
Date: 2025-06-17 13:30:07 Duration: 179ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'GLOBALGTMT5 - 1';
Date: 2025-06-17 13:31:05 Duration: 147ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
17 0ms 39ms 3ms 36,287 2m14s select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Jun 17 13 36,287 2m14s 3ms [ User: postgres - Total duration: 2m14s - Times executed: 36287 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m14s - Times executed: 36287 ]
-
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 = 'MRNA.US' OR dss.downloadersymbol = 'MRNA.US') AND dss.enabled = 1;
Date: 2025-06-17 13:00:06 Duration: 39ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'GBPAUD' OR dss.downloadersymbol = 'GBPAUD') AND dss.enabled = 1;
Date: 2025-06-17 13:00:06 Duration: 39ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'EURGBP' OR dss.downloadersymbol = 'EURGBP') AND dss.enabled = 1;
Date: 2025-06-17 13:45:06 Duration: 36ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
18 0ms 11ms 1ms 804 1s378ms select s.symbolid, dss.downloadfrequency, dss.downloadersymbol from downloadersymbolsettings dss inner join symbols s on dss.symbolid = s.symbolid where dss.classname = ? and s.deleted = ? and dss.enabled = ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Jun 17 13 804 1s378ms 1ms [ User: postgres - Total duration: 1s378ms - Times executed: 804 ]
[ Application: [unknown] - Total duration: 1s378ms - Times executed: 804 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'MILLENNIUMPF' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-17 13:30:56 Duration: 11ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'PEPPERSTONE' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-17 13:45:05 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'GLOBALGTMT5' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2025-06-17 13:30:03 Duration: 6ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
19 0ms 27ms 1ms 2,836 4s532ms insert into keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errormargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestprice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) values (?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?, ?, ?.?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?.?, ?::timestamp without time zone, ?, ?.?, ?.?, ?, ?, ?.?, ?.?, ?::timestamp without time zone, ?, ?, ?.?, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Jun 17 13 2,836 4s532ms 1ms [ User: postgres - Total duration: 4s532ms - Times executed: 2836 ]
[ Application: [unknown] - Total duration: 4s532ms - Times executed: 2836 ]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (7.000000000000000000000000000000, - 1, 1, '2025-06-17 11:26:33'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 208, 94.831000000000003070000000000000, '2025-06-17 10:00:00', '2025-06-11 15:00:00', '2025-06-11 02:00:00', '', '', '', '', '', '', '', 416, 94.954149999999998500000000000000, '2025-06-17 14:00:00'::timestamp without time zone, '2025-06-17 14:00:00', 0.000000000000000000000000000000, 0.123150000000000411900000000000, - 1, 500991627552434200, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|500991627552434200|94.831|1|2025-06-17 14:00:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-06-11 02:00:00', 94.831000000000003070000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 13:30:58 Duration: 27ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (3.000000000000000000000000000000, - 1, 1, '2025-06-17 11:26:31'::timestamp without time zone, '2025-06-17 14:00:00', 106.600000000000733300000000000000, 4, 98, 23573.150000000001460000000000000000, '2025-06-17 09:00:00', '2025-06-17 04:00:00', '2025-06-13 19:00:00', '2025-06-13 11:00:00', '', '', '', '', '', '', 220, 23591.380000000001020000000000000000, '2025-06-17 14:00:00'::timestamp without time zone, '2025-06-17 14:00:00', 23494.950000000000730000000000000000, 21.611499999999999490000000000000, 1, 604529010225161300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|604529010225161300|23573.15|1|2025-06-17 14:00:00|2025-06-17 14:00:00|1|-1', 23426.042000000001280000000000000000, 147.108000000000174600000000000000, 2, '2025-06-13 11:00:00', 23318.950000000000730000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 13:30:56 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (8.000000000000000000000000000000, - 1, 2, '2025-06-17 11:26:09'::timestamp without time zone, '', 0.500000000000000000000000000000, 4, 287, 5984.000000000000000000000000000000, '2025-06-17 13:45:00', '2025-06-17 10:15:00', '2025-06-12 14:45:00', '2025-06-12 11:00:00', '', '', '', '', '', '', 717, 5977.970999999999549000000000000000, '2025-06-17 14:15:00'::timestamp without time zone, '2025-06-17 14:15:00', 0.000000000000000000000000000000, 6.028999999999996362000000000000, 1, 515840238283769300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840238283769300|5984|2|2025-06-17 14:15:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-06-12 11:00:00', 5923.510000000000218000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-06-17 13:30:34 Duration: 9ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
20 0ms 38ms 1ms 47,229 1m13s 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 #20
Day Hour Count Duration Avg duration Jun 17 13 47,229 1m13s 1ms [ User: postgres - Total duration: 1m13s - Times executed: 47229 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m13s - Times executed: 47229 ]
-
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 = '538' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '538' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840233429886300';
Date: 2025-06-17 13:30:06 Duration: 38ms Database: acaweb_fx User: postgres Remote: 192.168.1.15 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840248226448300';
Date: 2025-06-17 13:30:04 Duration: 32ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840249443362300';
Date: 2025-06-17 13:00:05 Duration: 30ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 4s998ms 4,499 0ms 21ms 1ms WITH rar_max as ( ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Jun 17 13 4,499 4s998ms 1ms [ User: postgres - Total duration: 2h23m22s - Times executed: 4499 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2h23m22s - Times executed: 4499 ]
-
WITH rar_max as ( ;
Date: 2025-06-17 13:07:28 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
WITH rar_max as ( ;
Date: 2025-06-17 13:31:45 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
WITH rar_max as ( ;
Date: 2025-06-17 13:31:45 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
2 3s535ms 7,209 0ms 25ms 0ms SELECT ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 13 7,209 3s535ms 0ms [ User: postgres - Total duration: 13s547ms - Times executed: 7209 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 13s379ms - Times executed: 6371 ]
[ Application: [unknown] - Total duration: 167ms - Times executed: 838 ]
-
SELECT ;
Date: 2025-06-17 13:30:05 Duration: 25ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
SELECT ;
Date: 2025-06-17 13:25:59 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
SELECT ;
Date: 2025-06-17 13:25:59 Duration: 16ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
3 1s151ms 804 0ms 15ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 13 804 1s151ms 1ms [ User: postgres - Total duration: 1s378ms - Times executed: 804 ]
[ Application: [unknown] - Total duration: 1s378ms - Times executed: 804 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-17 13:30:52 Duration: 15ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-17 13:30:41 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-17 13:01:58 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
4 681ms 2,287 0ms 3ms 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 2,287 681ms 0ms [ User: postgres - Total duration: 5s990ms - Times executed: 2287 ]
[ Application: [unknown] - Total duration: 5s990ms - Times executed: 2287 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:30:38 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:30:07 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:46:59 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
5 385ms 3,371 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 13 3,371 385ms 0ms [ User: postgres - Total duration: 2s275ms - Times executed: 3371 ]
[ Application: [unknown] - Total duration: 2s275ms - Times executed: 3371 ]
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:00:57 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:11:57 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:42:01 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
6 307ms 4,322 0ms 20ms 0ms select 1;Times Reported Time consuming prepare #6
Day Hour Count Duration Avg duration 13 4,322 307ms 0ms [ User: postgres - Total duration: 33ms - Times executed: 4322 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 33ms - Times executed: 4322 ]
-
select 1;
Date: 2025-06-17 13:00:05 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
select 1;
Date: 2025-06-17 13:15:04 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
select 1;
Date: 2025-06-17 13:42:15 Duration: 9ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
7 296ms 2,067 0ms 3ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 13 2,067 296ms 0ms [ User: postgres - Total duration: 27ms - Times executed: 2067 ]
[ Application: [unknown] - Total duration: 27ms - Times executed: 2067 ]
-
SET extra_float_digits = 3;
Date: 2025-06-17 13:26:28 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
SET extra_float_digits = 3;
Date: 2025-06-17 13:49:04 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
SET extra_float_digits = 3;
Date: 2025-06-17 13:37:51 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
8 270ms 1,548 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 1,548 270ms 0ms [ User: postgres - Total duration: 15ms - Times executed: 1548 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 15ms - Times executed: 1548 ]
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-06-17 13:13:59 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.249
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-06-17 13:13:59 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.249
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-06-17 13:14:29 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.249
9 267ms 2,152 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 2,152 267ms 0ms [ User: postgres - Total duration: 1s207ms - Times executed: 2152 ]
[ Application: [unknown] - Total duration: 1s207ms - Times executed: 2152 ]
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:11:01 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:00:43 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:01:31 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
10 96ms 16 4ms 7ms 6ms with sym_info as ( ;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 13 16 96ms 6ms [ User: postgres - Total duration: 26s917ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 26s917ms - Times executed: 16 ]
-
with sym_info as ( ;
Date: 2025-06-17 13:51:44 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
-
with sym_info as ( ;
Date: 2025-06-17 13:51:47 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
-
with sym_info as ( ;
Date: 2025-06-17 13:36:58 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
11 84ms 70 0ms 3ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 13 70 84ms 1ms [ User: postgres - Total duration: 32s672ms - Times executed: 70 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 32s672ms - Times executed: 70 ]
-
WITH last_candle AS ( ;
Date: 2025-06-17 13:56:02 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
WITH last_candle AS ( ;
Date: 2025-06-17 13:04:08 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
WITH last_candle AS ( ;
Date: 2025-06-17 13:00:07 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
12 51ms 18 1ms 4ms 2ms select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 13 18 51ms 2ms [ User: postgres - Total duration: 33ms - Times executed: 18 ]
[ Application: [unknown] - Total duration: 33ms - Times executed: 18 ]
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-06-17 13:01:02 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-06-17 13:41:09 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-06-17 13:51:01 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
13 51ms 116 0ms 4ms 0ms WITH pre_symbols AS ( /* find relevant symbols */ ;Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 13 116 51ms 0ms [ User: postgres - Total duration: 1s744ms - Times executed: 116 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s744ms - Times executed: 116 ]
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-06-17 13:13:29 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.249
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-06-17 13:13:29 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.249
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-06-17 13:14:44 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.249
14 48ms 30 0ms 3ms 1ms with wh_patitioned as ( ;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 13 30 48ms 1ms [ User: postgres - Total duration: 1s302ms - Times executed: 30 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s302ms - Times executed: 30 ]
-
with wh_patitioned as ( ;
Date: 2025-06-17 13:54:44 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
with wh_patitioned as ( ;
Date: 2025-06-17 13:50:06 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15
-
with wh_patitioned as ( ;
Date: 2025-06-17 13:02:58 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
15 32ms 59 0ms 1ms 0ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming prepare #15
Day Hour Count Duration Avg duration 13 59 32ms 0ms [ User: postgres - Total duration: 1ms - Times executed: 59 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1ms - Times executed: 59 ]
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-17 13:42:20 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-17 13:28:29 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-17 13:26:54 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
16 25ms 2,041 0ms 0ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 13 2,041 25ms 0ms [ User: postgres - Total duration: 37ms - Times executed: 2041 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 37ms - Times executed: 2041 ]
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-17 13:17:00 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-17 13:42:00 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-06-17 13:17:30 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74
17 18ms 6 2ms 3ms 3ms select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 13 6 18ms 3ms [ User: postgres - Total duration: 12ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 12ms - Times executed: 6 ]
-
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2025-06-17 13:00:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2025-06-17 13:30:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2025-06-17 13:40:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
18 17ms 24 0ms 0ms 0ms select count(*) from datafeed_restarter_events where is_current_entry = 1;Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 13 24 17ms 0ms [ User: postgres - Total duration: 62ms - Times executed: 24 ]
[ Application: [unknown] - Total duration: 62ms - Times executed: 24 ]
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-06-17 13:30:06 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-06-17 13:00:03 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-06-17 13:50:04 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
19 16ms 6 2ms 3ms 2ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 13 6 16ms 2ms [ User: postgres - Total duration: 38s114ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 38s114ms - Times executed: 6 ]
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-17 13:30:03 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-17 13:00:02 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-06-17 13:50:02 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
20 16ms 12 1ms 1ms 1ms select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 13 12 16ms 1ms [ User: postgres - Total duration: 42ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 42ms - Times executed: 12 ]
-
select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2025-06-17 13:52:43 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 127.0.0.1
-
select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2025-06-17 13:02:35 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 127.0.0.1
-
select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2025-06-17 13:07:36 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 127.0.0.1
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 52s179ms 6,946 0ms 66ms 7ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Jun 17 13 6,946 52s179ms 7ms [ User: postgres - Total duration: 2h42m48s - Times executed: 6946 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2h34m20s - Times executed: 6886 ]
[ Application: [unknown] - Total duration: 8m28s - Times executed: 60 ]
-
WITH rar_max as ( ;
Date: 2025-06-17 13:46:34 Duration: 66ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '558', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '80', $13 = 'AUDSGD', $14 = 'CHFSGD', $15 = 'EURDKK', $16 = 'EURHKD', $17 = 'EURNOK', $18 = 'EURPLN', $19 = 'EURSEK', $20 = 'EURSGD', $21 = 'EURTRY', $22 = 'EURZAR', $23 = 'GBPDKK', $24 = 'GBPNOK', $25 = 'GBPSEK', $26 = 'GBPSGD', $27 = 'NOKJPY', $28 = 'NOKSEK', $29 = 'SEKJPY', $30 = 'SGDJPY', $31 = 'USDCNH', $32 = 'USDCZK', $33 = 'USDDKK', $34 = 'USDHKD', $35 = 'USDHUF', $36 = 'USDMXN', $37 = 'USDNOK', $38 = 'USDPLN', $39 = 'USDRUB', $40 = 'USDSEK', $41 = 'USDTHB', $42 = 'USDTRY', $43 = 'USDZAR', $44 = 'AUDUSD', $45 = 'EURUSD', $46 = 'GBPUSD', $47 = 'USDCAD', $48 = 'USDCHF', $49 = 'USDJPY', $50 = 'AUDCAD', $51 = 'AUDCHF', $52 = 'AUDJPY', $53 = 'AUDNZD', $54 = 'CADCHF', $55 = 'CADJPY', $56 = 'CHFJPY', $57 = 'EURAUD', $58 = 'EURCAD', $59 = 'EURCHF', $60 = 'EURGBP', $61 = 'EURJPY', $62 = 'EURNZD', $63 = 'GBPAUD', $64 = 'GBPCAD', $65 = 'GBPCHF', $66 = 'GBPJPY', $67 = 'GBPNZD', $68 = 'NZDCAD', $69 = 'NZDCHF', $70 = 'NZDJPY', $71 = 'NZDUSD', $72 = 'USDSGD', $73 = 'AUS200', $74 = 'DE30', $75 = 'ES35', $76 = 'F40', $77 = 'HK50', $78 = 'IT40', $79 = 'JP225', $80 = 'STOXX50', $81 = 'UK100', $82 = 'US2000', $83 = 'US30', $84 = 'US500', $85 = 'CHINA50', $86 = 'USTEC', $87 = 'XAGEUR', $88 = 'XAGUSD', $89 = 'XAUUSD', $90 = 'XAUEUR', $91 = 'XPDUSD', $92 = 'XPTUSD', $93 = '400', $94 = '400', $95 = 't', $96 = '10', $97 = '10'
-
WITH rar_max as ( ;
Date: 2025-06-17 13:30:04 Duration: 64ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 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'
-
WITH rar_max as ( ;
Date: 2025-06-17 13:30:04 Duration: 63ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = 't', $2 = '558', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '80', $14 = 'AUDSGD', $15 = 'CHFSGD', $16 = 'EURDKK', $17 = 'EURHKD', $18 = 'EURNOK', $19 = 'EURPLN', $20 = 'EURSEK', $21 = 'EURSGD', $22 = 'EURTRY', $23 = 'EURZAR', $24 = 'GBPDKK', $25 = 'GBPNOK', $26 = 'GBPSEK', $27 = 'GBPSGD', $28 = 'NOKJPY', $29 = 'NOKSEK', $30 = 'SEKJPY', $31 = 'SGDJPY', $32 = 'USDCNH', $33 = 'USDCZK', $34 = 'USDDKK', $35 = 'USDHKD', $36 = 'USDHUF', $37 = 'USDMXN', $38 = 'USDNOK', $39 = 'USDPLN', $40 = 'USDRUB', $41 = 'USDSEK', $42 = 'USDTHB', $43 = 'USDTRY', $44 = 'USDZAR', $45 = 'AUDUSD', $46 = 'EURUSD', $47 = 'GBPUSD', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDJPY', $51 = 'AUDCAD', $52 = 'AUDCHF', $53 = 'AUDJPY', $54 = 'AUDNZD', $55 = 'CADCHF', $56 = 'CADJPY', $57 = 'CHFJPY', $58 = 'EURAUD', $59 = 'EURCAD', $60 = 'EURCHF', $61 = 'EURGBP', $62 = 'EURJPY', $63 = 'EURNZD', $64 = 'GBPAUD', $65 = 'GBPCAD', $66 = 'GBPCHF', $67 = 'GBPJPY', $68 = 'GBPNZD', $69 = 'NZDCAD', $70 = 'NZDCHF', $71 = 'NZDJPY', $72 = 'NZDUSD', $73 = 'USDSGD', $74 = 'AUS200', $75 = 'DE30', $76 = 'ES35', $77 = 'F40', $78 = 'HK50', $79 = 'IT40', $80 = 'JP225', $81 = 'STOXX50', $82 = 'UK100', $83 = 'US2000', $84 = 'US30', $85 = 'US500', $86 = 'CHINA50', $87 = 'USTEC', $88 = 'XAGEUR', $89 = 'XAGUSD', $90 = 'XAUUSD', $91 = 'XAUEUR', $92 = 'XPDUSD', $93 = 'XPTUSD', $94 = '0', $95 = '', $96 = '0', $97 = '0', $98 = '0', $99 = '400', $100 = '400', $101 = 't', $102 = '10', $103 = '10'
2 45s643ms 89,962 0ms 27ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 13 89,962 45s643ms 0ms [ User: postgres - Total duration: 3m33s - Times executed: 89962 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3m33s - Times executed: 89124 ]
[ Application: [unknown] - Total duration: 167ms - Times executed: 838 ]
-
SELECT ;
Date: 2025-06-17 13:00:06 Duration: 27ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '500991628230657200'
-
SELECT ;
Date: 2025-06-17 13:00:07 Duration: 25ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '529', $2 = '0', $3 = '0', $4 = 'CHFJPY', $5 = 'CHFJPY'
-
SELECT ;
Date: 2025-06-17 13:30:05 Duration: 25ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '0', $3 = '0', $4 = 'USDTRY', $5 = 'USDTRY'
3 1s738ms 63 0ms 83ms 27ms with wh_patitioned as ( ;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 13 63 1s738ms 27ms [ User: postgres - Total duration: 3s64ms - Times executed: 63 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s64ms - Times executed: 63 ]
-
with wh_patitioned as ( ;
Date: 2025-06-17 13:40:56 Duration: 83ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529', $3 = '529', $4 = '529', $5 = '529', $6 = '529', $7 = '529', $8 = '529', $9 = '529'
-
with wh_patitioned as ( ;
Date: 2025-06-17 13:54:44 Duration: 50ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '529', $2 = '529', $3 = '529', $4 = '529', $5 = '529', $6 = '529', $7 = '529', $8 = '529', $9 = '529'
-
with wh_patitioned as ( ;
Date: 2025-06-17 13:00:35 Duration: 47ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529', $3 = '529', $4 = '529', $5 = '529', $6 = '529', $7 = '529', $8 = '529', $9 = '529'
4 1s596ms 804 1ms 10ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 13 804 1s596ms 1ms [ User: postgres - Total duration: 1s378ms - Times executed: 804 ]
[ Application: [unknown] - Total duration: 1s378ms - Times executed: 804 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-17 13:00:32 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'BDSWISS'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-17 13:30:03 Duration: 8ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'GLOBALGTMT5'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-06-17 13:45:32 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'ATFX'
5 1s215ms 61,043 0ms 20ms 0ms select 1;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 13 61,043 1s215ms 0ms [ User: postgres - Total duration: 283ms - Times executed: 61043 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 283ms - Times executed: 60953 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 90 ]
-
select 1;
Date: 2025-06-17 13:00:08 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
select 1;
Date: 2025-06-17 13:00:06 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
select 1;
Date: 2025-06-17 13:45:05 Duration: 16ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
6 1s29ms 135 4ms 30ms 7ms WITH last_candle AS ( ;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 13 135 1s29ms 7ms [ User: postgres - Total duration: 53s884ms - Times executed: 135 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 53s884ms - Times executed: 135 ]
-
WITH last_candle AS ( ;
Date: 2025-06-17 13:00:05 Duration: 30ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '958', $2 = '958'
-
WITH last_candle AS ( ;
Date: 2025-06-17 13:00:07 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '621', $2 = '621'
-
WITH last_candle AS ( ;
Date: 2025-06-17 13:56:02 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558'
7 808ms 61 9ms 33ms 13ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 13 61 808ms 13ms [ User: postgres - Total duration: 1ms - Times executed: 61 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1ms - Times executed: 61 ]
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-17 13:25:58 Duration: 33ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-17 13:42:20 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.74 parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-06-17 13:39:05 Duration: 19ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
8 694ms 1,548 0ms 4ms 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 1,548 694ms 0ms [ User: postgres - Total duration: 15ms - Times executed: 1548 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 15ms - Times executed: 1548 ]
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-06-17 13:13:29 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.249
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-06-17 13:13:59 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.249
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-06-17 13:13:59 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.249
9 638ms 16 28ms 93ms 39ms with sym_info as ( ;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 13 16 638ms 39ms [ User: postgres - Total duration: 26s917ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 26s917ms - Times executed: 16 ]
-
with sym_info as ( ;
Date: 2025-06-17 13:36:51 Duration: 93ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '617', $2 = 'Forex', $3 = 'Forex', $4 = '617', $5 = 'Forex', $6 = '617', $7 = '617', $8 = 'Forex', $9 = '617'
-
with sym_info as ( ;
Date: 2025-06-17 13:51:47 Duration: 45ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '617', $2 = 'Forex', $3 = 'Forex', $4 = '617', $5 = 'Forex', $6 = '617', $7 = '617', $8 = 'Forex', $9 = '617'
-
with sym_info as ( ;
Date: 2025-06-17 13:36:58 Duration: 45ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '627', $2 = 'Forex', $3 = 'Forex', $4 = '627', $5 = 'Forex', $6 = '627', $7 = '627', $8 = 'Forex', $9 = '627'
10 616ms 6,193 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 #10
Day Hour Count Duration Avg duration 13 6,193 616ms 0ms [ User: postgres - Total duration: 8s162ms - Times executed: 6193 ]
[ Application: [unknown] - Total duration: 8s162ms - Times executed: 6193 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:02:00 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 13:45:00', $2 = '1.35583', $3 = '1.35615', $4 = '1.35563', $5 = '1.35601', $6 = '835', $7 = '515840230504056300', $8 = '0', $9 = '2025-06-17 13:02:00.281', $10 = '2025-06-17 13:02:00.165', $11 = '1.35583', $12 = '1.35615', $13 = '1.35563', $14 = '1.35601', $15 = '835', $16 = '0', $17 = '2025-06-17 13:02:00.281', $18 = '2025-06-17 13:02:00.165'
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:47:12 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 14:30:00', $2 = '1.356265', $3 = '1.356335', $4 = '1.356', $5 = '1.356035', $6 = '560', $7 = '515840230581642300', $8 = '0', $9 = '2025-06-17 13:47:12.097', $10 = '2025-06-17 13:47:12.055', $11 = '1.356265', $12 = '1.356335', $13 = '1.356', $14 = '1.356035', $15 = '560', $16 = '0', $17 = '2025-06-17 13:47:12.097', $18 = '2025-06-17 13:47:12.055'
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:30:05 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 14:15:00', $2 = '32.116', $3 = '32.179', $4 = '32.039', $5 = '32.084', $6 = '1065', $7 = '515840217487091300', $8 = '0', $9 = '2025-06-17 13:30:05.385', $10 = '2025-06-17 13:30:05.148', $11 = '32.116', $12 = '32.179', $13 = '32.039', $14 = '32.084', $15 = '1065', $16 = '0', $17 = '2025-06-17 13:30:05.385', $18 = '2025-06-17 13:30:05.148'
11 359ms 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 359ms 3ms [ User: postgres - Total duration: 1s744ms - Times executed: 116 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s744ms - Times executed: 116 ]
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-06-17 13:14:44 Duration: 34ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.249 parameters: $1 = '974', $2 = 'ICMARKETS-AU-MT5', $3 = 'AUDCAD', $4 = 'AUDCHF', $5 = 'AUDJPY', $6 = 'AUDNZD', $7 = 'AUDSGD', $8 = 'AUDUSD', $9 = 'AUS200', $10 = 'BRENT_F0', $11 = 'BRENT_F1', $12 = 'BRENT_F2', $13 = 'BRENT_F3', $14 = 'BRENT_F4', $15 = 'BRENT_F5', $16 = 'BRENT_F6', $17 = 'BRENT_F7', $18 = 'BRENT_F8', $19 = 'BRENT_F9', $20 = 'BRENT_G0', $21 = 'BRENT_G1', $22 = 'BRENT_G2', $23 = 'BRENT_G3', $24 = 'BRENT_G4', $25 = 'BRENT_G5', $26 = 'BRENT_G6', $27 = 'BRENT_G7', $28 = 'BRENT_G8', $29 = 'BRENT_G9', $30 = 'BRENT_H0', $31 = 'BRENT_H1', $32 = 'BRENT_H2', $33 = 'BRENT_H3', $34 = 'BRENT_H4', $35 = 'BRENT_H5', $36 = 'BRENT_H6', $37 = 'BRENT_H7', $38 = 'BRENT_H8', $39 = 'BRENT_H9', $40 = 'BRENT_J0', $41 = 'BRENT_J1', $42 = 'BRENT_J2', $43 = 'BRENT_J3', $44 = 'BRENT_J4', $45 = 'BRENT_J5', $46 = 'BRENT_J6', $47 = 'BRENT_J7', $48 = 'BRENT_J8', $49 = 'BRENT_J9', $50 = 'BRENT_K0', $51 = 'BRENT_K1', $52 = 'BRENT_K2', $53 = 'BRENT_K3', $54 = 'BRENT_K4', $55 = 'BRENT_K5', $56 = 'BRENT_K6', $57 = 'BRENT_K7', $58 = 'BRENT_K8', $59 = 'BRENT_K9', $60 = 'BRENT_M0', $61 = 'BRENT_M1', $62 = 'BRENT_M2', $63 = 'BRENT_M3', $64 = 'BRENT_M4', $65 = 'BRENT_M5', $66 = 'BRENT_M6', $67 = 'BRENT_M7', $68 = 'BRENT_M8', $69 = 'BRENT_M9', $70 = 'BRENT_N0', $71 = 'BRENT_N1', $72 = 'BRENT_N2', $73 = 'BRENT_N3', $74 = 'BRENT_N4', $75 = 'BRENT_N5', $76 = 'BRENT_N6', $77 = 'BRENT_N7', $78 = 'BRENT_N8', $79 = 'BRENT_N9', $80 = 'BRENT_Q0', $81 = 'BRENT_Q1', $82 = 'BRENT_Q2', $83 = 'BRENT_Q3', $84 = 'BRENT_Q4', $85 = 'BRENT_Q5', $86 = 'BRENT_Q6', $87 = 'BRENT_Q7', $88 = 'BRENT_Q8', $89 = 'BRENT_Q9', $90 = 'BRENT_U0', $91 = 'BRENT_U1', $92 = 'BRENT_U2', $93 = 'BRENT_U3', $94 = 'BRENT_U4', $95 = 'BRENT_U5', $96 = 'BRENT_U6', $97 = 'BRENT_U7', $98 = 'BRENT_U8', $99 = 'BRENT_U9', $100 = 'BRENT_V0', $101 = 'BRENT_V1', $102 = 'BRENT_V2', $103 = 'BRENT_V3', $104 = 'BRENT_V4', $105 = 'BRENT_V5', $106 = 'BRENT_V6', $107 = 'BRENT_V7', $108 = 'BRENT_V8', $109 = 'BRENT_V9', $110 = 'BRENT_X0', $111 = 'BRENT_X1', $112 = 'BRENT_X2', $113 = 'BRENT_X3', $114 = 'BRENT_X4', $115 = 'BRENT_X5', $116 = 'BRENT_X6', $117 = 'BRENT_X7', $118 = 'BRENT_X8', $119 = 'BRENT_X9', $120 = 'BRENT_Z0', $121 = 'BRENT_Z1', $122 = 'BRENT_Z2', $123 = 'BRENT_Z3', $124 = 'BRENT_Z4', $125 = 'BRENT_Z5', $126 = 'BRENT_Z6', $127 = 'BRENT_Z7', $128 = 'BRENT_Z8', $129 = 'BRENT_Z9', $130 = 'BTCUSD', $131 = 'CADCHF', $132 = 'CADJPY', $133 = 'CHFJPY', $134 = 'CHFSGD', $135 = 'CHINA50', $136 = 'Coffee_F0', $137 = 'Coffee_F1', $138 = 'Coffee_F2', $139 = 'Coffee_F3', $140 = 'Coffee_F4', $141 = 'Coffee_F5', $142 = 'Coffee_F6', $143 = 'Coffee_F7', $144 = 'Coffee_F8', $145 = 'Coffee_F9', $146 = 'Coffee_G0', $147 = 'Coffee_G1', $148 = 'Coffee_G2', $149 = 'Coffee_G3', $150 = 'Coffee_G4', $151 = 'Coffee_G5', $152 = 'Coffee_G6', $153 = 'Coffee_G7', $154 = 'Coffee_G8', $155 = 'Coffee_G9', $156 = 'Coffee_H0', $157 = 'Coffee_H1', $158 = 'Coffee_H2', $159 = 'Coffee_H3', $160 = 'Coffee_H4', $161 = 'Coffee_H5', $162 = 'Coffee_H6', $163 = 'Coffee_H7', $164 = 'Coffee_H8', $165 = 'Coffee_H9', $166 = 'Coffee_J0', $167 = 'Coffee_J1', $168 = 'Coffee_J2', $169 = 'Coffee_J3', $170 = 'Coffee_J4', $171 = 'Coffee_J5', $172 = 'Coffee_J6', $173 = 'Coffee_J7', $174 = 'Coffee_J8', $175 = 'Coffee_J9', $176 = 'Coffee_K0', $177 = 'Coffee_K1', $178 = 'Coffee_K2', $179 = 'Coffee_K3', $180 = 'Coffee_K4', $181 = 'Coffee_K5', $182 = 'Coffee_K6', $183 = 'Coffee_K7', $184 = 'Coffee_K8', $185 = 'Coffee_K9', $186 = 'Coffee_M0', $187 = 'Coffee_M1', $188 = 'Coffee_M2', $189 = 'Coffee_M3', $190 = 'Coffee_M4', $191 = 'Coffee_M5', $192 = 'Coffee_M6', $193 = 'Coffee_M7', $194 = 'Coffee_M8', $195 = 'Coffee_M9', $196 = 'Coffee_N0', $197 = 'Coffee_N1', $198 = 'Coffee_N2', $199 = 'Coffee_N3', $200 = 'Coffee_N4', $201 = 'Coffee_N5', $202 = 'Coffee_N6', $203 = 'Coffee_N7', $204 = 'Coffee_N8', $205 = 'Coffee_N9', $206 = 'Coffee_Q0', $207 = 'Coffee_Q1', $208 = 'Coffee_Q2', $209 = 'Coffee_Q3', $210 = 'Coffee_Q4', $211 = 'Coffee_Q5', $212 = 'Coffee_Q6', $213 = 'Coffee_Q7', $214 = 'Coffee_Q8', $215 = 'Coffee_Q9', $216 = 'Coffee_U0', $217 = 'Coffee_U1', $218 = 'Coffee_U2', $219 = 'Coffee_U3', $220 = 'Coffee_U4', $221 = 'Coffee_U5', $222 = 'Coffee_U6', $223 = 'Coffee_U7', $224 = 'Coffee_U8', $225 = 'Coffee_U9', $226 = 'Coffee_V0', $227 = 'Coffee_V1', $228 = 'Coffee_V2', $229 = 'Coffee_V3', $230 = 'Coffee_V4', $231 = 'Coffee_V5', $232 = 'Coffee_V6', $233 = 'Coffee_V7', $234 = 'Coffee_V8', $235 = 'Coffee_V9', $236 = 'Coffee_X0', $237 = 'Coffee_X1', $238 = 'Coffee_X2', $239 = 'Coffee_X3', $240 = 'Coffee_X4', $241 = 'Coffee_X5', $242 = 'Coffee_X6', $243 = 'Coffee_X7', $244 = 'Coffee_X8', $245 = 'Coffee_X9', $246 = 'Coffee_Z0', $247 = 'Coffee_Z1', $248 = 'Coffee_Z2', $249 = 'Coffee_Z3', $250 = 'Coffee_Z4', $251 = 'Coffee_Z5', $252 = 'Coffee_Z6', $253 = 'Coffee_Z7', $254 = 'Coffee_Z8', $255 = 'Coffee_Z9', $256 = 'Corn_F0', $257 = 'Corn_F1', $258 = 'Corn_F2', $259 = 'Corn_F3', $260 = 'Corn_F4', $261 = 'Corn_F5', $262 = 'Corn_F6', $263 = 'Corn_F7', $264 = 'Corn_F8', $265 = 'Corn_F9', $266 = 'Corn_G0', $267 = 'Corn_G1', $268 = 'Corn_G2', $269 = 'Corn_G3', $270 = 'Corn_G4', $271 = 'Corn_G5', $272 = 'Corn_G6', $273 = 'Corn_G7', $274 = 'Corn_G8', $275 = 'Corn_G9', $276 = 'Corn_H0', $277 = 'Corn_H1', $278 = 'Corn_H2', $279 = 'Corn_H3', $280 = 'Corn_H4', $281 = 'Corn_H5', $282 = 'Corn_H6', $283 = 'Corn_H7', $284 = 'Corn_H8', $285 = 'Corn_H9', $286 = 'Corn_J0', $287 = 'Corn_J1', $288 = 'Corn_J2', $289 = 'Corn_J3', $290 = 'Corn_J4', $291 = 'Corn_J5', $292 = 'Corn_J6', $293 = 'Corn_J7', $294 = 'Corn_J8', $295 = 'Corn_J9', $296 = 'Corn_K0', $297 = 'Corn_K1', $298 = 'Corn_K2', $299 = 'Corn_K3', $300 = 'Corn_K4', $301 = 'Corn_K5', $302 = 'Corn_K6', $303 = 'Corn_K7', $304 = 'Corn_K8', $305 = 'Corn_K9', $306 = 'Corn_M0', $307 = 'Corn_M1', $308 = 'Corn_M2', $309 = 'Corn_M3', $310 = 'Corn_M4', $311 = 'Corn_M5', $312 = 'Corn_M6', $313 = 'Corn_M7', $314 = 'Corn_M8', $315 = 'Corn_M9', $316 = 'Corn_N0', $317 = 'Corn_N1', $318 = 'Corn_N2', $319 = 'Corn_N3', $320 = 'Corn_N4', $321 = 'Corn_N5', $322 = 'Corn_N6', $323 = 'Corn_N7', $324 = 'Corn_N8', $325 = 'Corn_N9', $326 = 'Corn_Q0', $327 = 'Corn_Q1', $328 = 'Corn_Q2', $329 = 'Corn_Q3', $330 = 'Corn_Q4', $331 = 'Corn_Q5', $332 = 'Corn_Q6', $333 = 'Corn_Q7', $334 = 'Corn_Q8', $335 = 'Corn_Q9', $336 = 'Corn_U0', $337 = 'Corn_U1', $338 = 'Corn_U2', $339 = 'Corn_U3', $340 = 'Corn_U4', $341 = 'Corn_U5', $342 = 'Corn_U6', $343 = 'Corn_U7', $344 = 'Corn_U8', $345 = 'Corn_U9', $346 = 'Corn_V0', $347 = 'Corn_V1', $348 = 'Corn_V2', $349 = 'Corn_V3', $350 = 'Corn_V4', $351 = 'Corn_V5', $352 = 'Corn_V6', $353 = 'Corn_V7', $354 = 'Corn_V8', $355 = 'Corn_V9', $356 = 'Corn_X0', $357 = 'Corn_X1', $358 = 'Corn_X2', $359 = 'Corn_X3', $360 = 'Corn_X4', $361 = 'Corn_X5', $362 = 'Corn_X6', $363 = 'Corn_X7', $364 = 'Corn_X8', $365 = 'Corn_X9', $366 = 'Corn_Z0', $367 = 'Corn_Z1', $368 = 'Corn_Z2', $369 = 'Corn_Z3', $370 = 'Corn_Z4', $371 = 'Corn_Z5', $372 = 'Corn_Z6', $373 = 'Corn_Z7', $374 = 'Corn_Z8', $375 = 'Corn_Z9', $376 = 'DE30', $377 = 'ES35', $378 = 'EURAUD', $379 = 'EURCAD', $380 = 'EURCHF', $381 = 'EURDKK', $382 = 'EURGBP', $383 = 'EURHKD', $384 = 'EURJPY', $385 = 'EURNOK', $386 = 'EURNZD', $387 = 'EURPLN', $388 = 'EURSEK', $389 = 'EURSGD', $390 = 'EURTRY', $391 = 'EURUSD', $392 = 'EURZAR', $393 = 'F40', $394 = 'GBPAUD', $395 = 'GBPCAD', $396 = 'GBPCHF', $397 = 'GBPDKK', $398 = 'GBPJPY', $399 = 'GBPNOK', $400 = 'GBPNZD', $401 = 'GBPSEK', $402 = 'GBPSGD', $403 = 'GBPUSD', $404 = 'HK50', $405 = 'IT40', $406 = 'JP225', $407 = 'NOKJPY', $408 = 'NOKSEK', $409 = 'NZDCAD', $410 = 'NZDCHF', $411 = 'NZDJPY', $412 = 'NZDUSD', $413 = 'SEKJPY', $414 = 'SGDJPY', $415 = 'STOXX50', $416 = 'Soybean_F0', $417 = 'Soybean_F1', $418 = 'Soybean_F2', $419 = 'Soybean_F3', $420 = 'Soybean_F4', $421 = 'Soybean_F5', $422 = 'Soybean_F6', $423 = 'Soybean_F7', $424 = 'Soybean_F8', $425 = 'Soybean_F9', $426 = 'Soybean_G0', $427 = 'Soybean_G1', $428 = 'Soybean_G2', $429 = 'Soybean_G3', $430 = 'Soybean_G4', $431 = 'Soybean_G5', $432 = 'Soybean_G6', $433 = 'Soybean_G7', $434 = 'Soybean_G8', $435 = 'Soybean_G9', $436 = 'Soybean_H0', $437 = 'Soybean_H1', $438 = 'Soybean_H2', $439 = 'Soybean_H3', $440 = 'Soybean_H4', $441 = 'Soybean_H5', $442 = 'Soybean_H6', $443 = 'Soybean_H7', $444 = 'Soybean_H8', $445 = 'Soybean_H9', $446 = 'Soybean_J0', $447 = 'Soybean_J1', $448 = 'Soybean_J2', $449 = 'Soybean_J3', $450 = 'Soybean_J4', $451 = 'Soybean_J5', $452 = 'Soybean_J6', $453 = 'Soybean_J7', $454 = 'Soybean_J8', $455 = 'Soybean_J9', $456 = 'Soybean_K0', $457 = 'Soybean_K1', $458 = 'Soybean_K2', $459 = 'Soybean_K3', $460 = 'Soybean_K4', $461 = 'Soybean_K5', $462 = 'Soybean_K6', $463 = 'Soybean_K7', $464 = 'Soybean_K8', $465 = 'Soybean_K9', $466 = 'Soybean_M0', $467 = 'Soybean_M1', $468 = 'Soybean_M2', $469 = 'Soybean_M3', $470 = 'Soybean_M4', $471 = 'Soybean_M5', $472 = 'Soybean_M6', $473 = 'Soybean_M7', $474 = 'Soybean_M8', $475 = 'Soybean_M9', $476 = 'Soybean_N0', $477 = 'Soybean_N1', $478 = 'Soybean_N2', $479 = 'Soybean_N3', $480 = 'Soybean_N4', $481 = 'Soybean_N5', $482 = 'Soybean_N6', $483 = 'Soybean_N7', $484 = 'Soybean_N8', $485 = 'Soybean_N9', $486 = 'Soybean_Q0', $487 = 'Soybean_Q1', $488 = 'Soybean_Q2', $489 = 'Soybean_Q3', $490 = 'Soybean_Q4', $491 = 'Soybean_Q5', $492 = 'Soybean_Q6', $493 = 'Soybean_Q7', $494 = 'Soybean_Q8', $495 = 'Soybean_Q9', $496 = 'Soybean_U0', $497 = 'Soybean_U1', $498 = 'Soybean_U2', $499 = 'Soybean_U3', $500 = 'Soybean_U4', $501 = 'Soybean_U5', $502 = 'Soybean_U6', $503 = 'Soybean_U7', $504 = 'Soybean_U8', $505 = 'Soybean_U9', $506 = 'Soybean_V0', $507 = 'Soybean_V1', $508 = 'Soybean_V2', $509 = 'Soybean_V3', $510 = 'Soybean_V4', $511 = 'Soybean_V5', $512 = 'Soybean_V6', $513 = 'Soybean_V7', $514 = 'Soybean_V8', $515 = 'Soybean_V9', $516 = 'Soybean_X0', $517 = 'Soybean_X1', $518 = 'Soybean_X2', $519 = 'Soybean_X3', $520 = 'Soybean_X4', $521 = 'Soybean_X5', $522 = 'Soybean_X6', $523 = 'Soybean_X7', $524 = 'Soybean_X8', $525 = 'Soybean_X9', $526 = 'Soybean_Z0', $527 = 'Soybean_Z1', $528 = 'Soybean_Z2', $529 = 'Soybean_Z3', $530 = 'Soybean_Z4', $531 = 'Soybean_Z5', $532 = 'Soybean_Z6', $533 = 'Soybean_Z7', $534 = 'Soybean_Z8', $535 = 'Soybean_Z9', $536 = 'Sugar_F0', $537 = 'Sugar_F1', $538 = 'Sugar_F2', $539 = 'Sugar_F3', $540 = 'Sugar_F4', $541 = 'Sugar_F5', $542 = 'Sugar_F6', $543 = 'Sugar_F7', $544 = 'Sugar_F8', $545 = 'Sugar_F9', $546 = 'Sugar_G0', $547 = 'Sugar_G1', $548 = 'Sugar_G2', $549 = 'Sugar_G3', $550 = 'Sugar_G4', $551 = 'Sugar_G5', $552 = 'Sugar_G6', $553 = 'Sugar_G7', $554 = 'Sugar_G8', $555 = 'Sugar_G9', $556 = 'Sugar_H0', $557 = 'Sugar_H1', $558 = 'Sugar_H2', $559 = 'Sugar_H3', $560 = 'Sugar_H4', $561 = 'Sugar_H5', $562 = 'Sugar_H6', $563 = 'Sugar_H7', $564 = 'Sugar_H8', $565 = 'Sugar_H9', $566 = 'Sugar_J0', $567 = 'Sugar_J1', $568 = 'Sugar_J2', $569 = 'Sugar_J3', $570 = 'Sugar_J4', $571 = 'Sugar_J5', $572 = 'Sugar_J6', $573 = 'Sugar_J7', $574 = 'Sugar_J8', $575 = 'Sugar_J9', $576 = 'Sugar_K0', $577 = 'Sugar_K1', $578 = 'Sugar_K2', $579 = 'Sugar_K3', $580 = 'Sugar_K4', $581 = 'Sugar_K5', $582 = 'Sugar_K6', $583 = 'Sugar_K7', $584 = 'Sugar_K8', $585 = 'Sugar_K9', $586 = 'Sugar_M0', $587 = 'Sugar_M1', $588 = 'Sugar_M2', $589 = 'Sugar_M3', $590 = 'Sugar_M4', $591 = 'Sugar_M5', $592 = 'Sugar_M6', $593 = 'Sugar_M7', $594 = 'Sugar_M8', $595 = 'Sugar_M9', $596 = 'Sugar_N0', $597 = 'Sugar_N1', $598 = 'Sugar_N2', $599 = 'Sugar_N3', $600 = 'Sugar_N4', $601 = 'Sugar_N5', $602 = 'Sugar_N6', $603 = 'Sugar_N7', $604 = 'Sugar_N8', $605 = 'Sugar_N9', $606 = 'Sugar_Q0', $607 = 'Sugar_Q1', $608 = 'Sugar_Q2', $609 = 'Sugar_Q3', $610 = 'Sugar_Q4', $611 = 'Sugar_Q5', $612 = 'Sugar_Q6', $613 = 'Sugar_Q7', $614 = 'Sugar_Q8', $615 = 'Sugar_Q9', $616 = 'Sugar_U0', $617 = 'Sugar_U1', $618 = 'Sugar_U2', $619 = 'Sugar_U3', $620 = 'Sugar_U4', $621 = 'Sugar_U5', $622 = 'Sugar_U6', $623 = 'Sugar_U7', $624 = 'Sugar_U8', $625 = 'Sugar_U9', $626 = 'Sugar_V0', $627 = 'Sugar_V1', $628 = 'Sugar_V2', $629 = 'Sugar_V3', $630 = 'Sugar_V4', $631 = 'Sugar_V5', $632 = 'Sugar_V6', $633 = 'Sugar_V7', $634 = 'Sugar_V8', $635 = 'Sugar_V9', $636 = 'Sugar_X0', $637 = 'Sugar_X1', $638 = 'Sugar_X2', $639 = 'Sugar_X3', $640 = 'Sugar_X4', $641 = 'Sugar_X5', $642 = 'Sugar_X6', $643 = 'Sugar_X7', $644 = 'Sugar_X8', $645 = 'Sugar_X9', $646 = 'Sugar_Z0', $647 = 'Sugar_Z1', $648 = 'Sugar_Z2', $649 = 'Sugar_Z3', $650 = 'Sugar_Z4', $651 = 'Sugar_Z5', $652 = 'Sugar_Z6', $653 = 'Sugar_Z7', $654 = 'Sugar_Z8', $655 = 'Sugar_Z9', $656 = 'UK100', $657 = 'US2000', $658 = 'US30', $659 = 'US500', $660 = 'USDCAD', $661 = 'USDCHF', $662 = 'USDCNH', $663 = 'USDCZK', $664 = 'USDDKK', $665 = 'USDHKD', $666 = 'USDHUF', $667 = 'USDJPY', $668 = 'USDMXN', $669 = 'USDNOK', $670 = 'USDPLN', $671 = 'USDRUB', $672 = 'USDSEK', $673 = 'USDSGD', $674 = 'USDTHB', $675 = 'USDTRY', $676 = 'USDZAR', $677 = 'USTEC', $678 = 'WTI_F0', $679 = 'WTI_F1', $680 = 'WTI_F2', $681 = 'WTI_F3', $682 = 'WTI_F4', $683 = 'WTI_F5', $684 = 'WTI_F6', $685 = 'WTI_F7', $686 = 'WTI_F8', $687 = 'WTI_F9', $688 = 'WTI_G0', $689 = 'WTI_G1', $690 = 'WTI_G2', $691 = 'WTI_G3', $692 = 'WTI_G4', $693 = 'WTI_G5', $694 = 'WTI_G6', $695 = 'WTI_G7', $696 = 'WTI_G8', $697 = 'WTI_G9', $698 = 'WTI_H0', $699 = 'WTI_H1', $700 = 'WTI_H2', $701 = 'WTI_H3', $702 = 'WTI_H4', $703 = 'WTI_H5', $704 = 'WTI_H6', $705 = 'WTI_H7', $706 = 'WTI_H8', $707 = 'WTI_H9', $708 = 'WTI_J0', $709 = 'WTI_J1', $710 = 'WTI_J2', $711 = 'WTI_J3', $712 = 'WTI_J4', $713 = 'WTI_J5', $714 = 'WTI_J6', $715 = 'WTI_J7', $716 = 'WTI_J8', $717 = 'WTI_J9', $718 = 'WTI_K0', $719 = 'WTI_K1', $720 = 'WTI_K2', $721 = 'WTI_K3', $722 = 'WTI_K4', $723 = 'WTI_K5', $724 = 'WTI_K6', $725 = 'WTI_K7', $726 = 'WTI_K8', $727 = 'WTI_K9', $728 = 'WTI_M0', $729 = 'WTI_M1', $730 = 'WTI_M2', $731 = 'WTI_M3', $732 = 'WTI_M4', $733 = 'WTI_M5', $734 = 'WTI_M6', $735 = 'WTI_M7', $736 = 'WTI_M8', $737 = 'WTI_M9', $738 = 'WTI_N0', $739 = 'WTI_N1', $740 = 'WTI_N2', $741 = 'WTI_N3', $742 = 'WTI_N4', $743 = 'WTI_N5', $744 = 'WTI_N6', $745 = 'WTI_N7', $746 = 'WTI_N8', $747 = 'WTI_N9', $748 = 'WTI_Q0', $749 = 'WTI_Q1', $750 = 'WTI_Q2', $751 = 'WTI_Q3', $752 = 'WTI_Q4', $753 = 'WTI_Q5', $754 = 'WTI_Q6', $755 = 'WTI_Q7', $756 = 'WTI_Q8', $757 = 'WTI_Q9', $758 = 'WTI_U0', $759 = 'WTI_U1', $760 = 'WTI_U2', $761 = 'WTI_U3', $762 = 'WTI_U4', $763 = 'WTI_U5', $764 = 'WTI_U6', $765 = 'WTI_U7', $766 = 'WTI_U8', $767 = 'WTI_U9', $768 = 'WTI_V0', $769 = 'WTI_V1', $770 = 'WTI_V2', $771 = 'WTI_V3', $772 = 'WTI_V4', $773 = 'WTI_V5', $774 = 'WTI_V6', $775 = 'WTI_V7', $776 = 'WTI_V8', $777 = 'WTI_V9', $778 = 'WTI_X0', $779 = 'WTI_X1', $780 = 'WTI_X2', $781 = 'WTI_X3', $782 = 'WTI_X4', $783 = 'WTI_X5', $784 = 'WTI_X6', $785 = 'WTI_X7', $786 = 'WTI_X8', $787 = 'WTI_X9', $788 = 'WTI_Z0', $789 = 'WTI_Z1', $790 = 'WTI_Z2', $791 = 'WTI_Z3', $792 = 'WTI_Z4', $793 = 'WTI_Z5', $794 = 'WTI_Z6', $795 = 'WTI_Z7', $796 = 'WTI_Z8', $797 = 'WTI_Z9', $798 = 'Wheat_F0', $799 = 'Wheat_F1', $800 = 'Wheat_F2', $801 = 'Wheat_F3', $802 = 'Wheat_F4', $803 = 'Wheat_F5', $804 = 'Wheat_F6', $805 = 'Wheat_F7', $806 = 'Wheat_F8', $807 = 'Wheat_F9', $808 = 'Wheat_G0', $809 = 'Wheat_G1', $810 = 'Wheat_G2', $811 = 'Wheat_G3', $812 = 'Wheat_G4', $813 = 'Wheat_G5', $814 = 'Wheat_G6', $815 = 'Wheat_G7', $816 = 'Wheat_G8', $817 = 'Wheat_G9', $818 = 'Wheat_H0', $819 = 'Wheat_H1', $820 = 'Wheat_H2', $821 = 'Wheat_H3', $822 = 'Wheat_H4', $823 = 'Wheat_H5', $824 = 'Wheat_H6', $825 = 'Wheat_H7', $826 = 'Wheat_H8', $827 = 'Wheat_H9', $828 = 'Wheat_J0', $829 = 'Wheat_J1', $830 = 'Wheat_J2', $831 = 'Wheat_J3', $832 = 'Wheat_J4', $833 = 'Wheat_J5', $834 = 'Wheat_J6', $835 = 'Wheat_J7', $836 = 'Wheat_J8', $837 = 'Wheat_J9', $838 = 'Wheat_K0', $839 = 'Wheat_K1', $840 = 'Wheat_K2', $841 = 'Wheat_K3', $842 = 'Wheat_K4', $843 = 'Wheat_K5', $844 = 'Wheat_K6', $845 = 'Wheat_K7', $846 = 'Wheat_K8', $847 = 'Wheat_K9', $848 = 'Wheat_M0', $849 = 'Wheat_M1', $850 = 'Wheat_M2', $851 = 'Wheat_M3', $852 = 'Wheat_M4', $853 = 'Wheat_M5', $854 = 'Wheat_M6', $855 = 'Wheat_M7', $856 = 'Wheat_M8', $857 = 'Wheat_M9', $858 = 'Wheat_N0', $859 = 'Wheat_N1', $860 = 'Wheat_N2', $861 = 'Wheat_N3', $862 = 'Wheat_N4', $863 = 'Wheat_N5', $864 = 'Wheat_N6', $865 = 'Wheat_N7', $866 = 'Wheat_N8', $867 = 'Wheat_N9', $868 = 'Wheat_Q0', $869 = 'Wheat_Q1', $870 = 'Wheat_Q2', $871 = 'Wheat_Q3', $872 = 'Wheat_Q4', $873 = 'Wheat_Q5', $874 = 'Wheat_Q6', $875 = 'Wheat_Q7', $876 = 'Wheat_Q8', $877 = 'Wheat_Q9', $878 = 'Wheat_U0', $879 = 'Wheat_U1', $880 = 'Wheat_U2', $881 = 'Wheat_U3', $882 = 'Wheat_U4', $883 = 'Wheat_U5', $884 = 'Wheat_U6', $885 = 'Wheat_U7', $886 = 'Wheat_U8', $887 = 'Wheat_U9', $888 = 'Wheat_V0', $889 = 'Wheat_V1', $890 = 'Wheat_V2', $891 = 'Wheat_V3', $892 = 'Wheat_V4', $893 = 'Wheat_V5', $894 = 'Wheat_V6', $895 = 'Wheat_V7', $896 = 'Wheat_V8', $897 = 'Wheat_V9', $898 = 'Wheat_X0', $899 = 'Wheat_X1', $900 = 'Wheat_X2', $901 = 'Wheat_X3', $902 = 'Wheat_X4', $903 = 'Wheat_X5', $904 = 'Wheat_X6', $905 = 'Wheat_X7', $906 = 'Wheat_X8', $907 = 'Wheat_X9', $908 = 'Wheat_Z0', $909 = 'Wheat_Z1', $910 = 'Wheat_Z2', $911 = 'Wheat_Z3', $912 = 'Wheat_Z4', $913 = 'Wheat_Z5', $914 = 'Wheat_Z6', $915 = 'Wheat_Z7', $916 = 'Wheat_Z8', $917 = 'Wheat_Z9', $918 = 'XAGEUR', $919 = 'XAGUSD', $920 = 'XAUEUR', $921 = 'XAUUSD', $922 = 'XBRUSD', $923 = 'XNGUSD', $924 = 'XPDUSD', $925 = 'XPTUSD', $926 = 'XTIUSD', $927 = 'AUDCAD', $928 = 'AUDCHF', $929 = 'AUDJPY', $930 = 'AUDNZD', $931 = 'AUDSGD', $932 = 'AUDUSD', $933 = 'AUS200', $934 = 'BRENT_F0', $935 = 'BRENT_F1', $936 = 'BRENT_F2', $937 = 'BRENT_F3', $938 = 'BRENT_F4', $939 = 'BRENT_F5', $940 = 'BRENT_F6', $941 = 'BRENT_F7', $942 = 'BRENT_F8', $943 = 'BRENT_F9', $944 = 'BRENT_G0', $945 = 'BRENT_G1', $946 = 'BRENT_G2', $947 = 'BRENT_G3', $948 = 'BRENT_G4', $949 = 'BRENT_G5', $950 = 'BRENT_G6', $951 = 'BRENT_G7', $952 = 'BRENT_G8', $953 = 'BRENT_G9', $954 = 'BRENT_H0', $955 = 'BRENT_H1', $956 = 'BRENT_H2', $957 = 'BRENT_H3', $958 = 'BRENT_H4', $959 = 'BRENT_H5', $960 = 'BRENT_H6', $961 = 'BRENT_H7', $962 = 'BRENT_H8', $963 = 'BRENT_H9', $964 = 'BRENT_J0', $965 = 'BRENT_J1', $966 = 'BRENT_J2', $967 = 'BRENT_J3', $968 = 'BRENT_J4', $969 = 'BRENT_J5', $970 = 'BRENT_J6', $971 = 'BRENT_J7', $972 = 'BRENT_J8', $973 = 'BRENT_J9', $974 = 'BRENT_K0', $975 = 'BRENT_K1', $976 = 'BRENT_K2', $977 = 'BRENT_K3', $978 = 'BRENT_K4', $979 = 'BRENT_K5', $980 = 'BRENT_K6', $981 = 'BRENT_K7', $982 = 'BRENT_K8', $983 = 'BRENT_K9', $984 = 'BRENT_M0', $985 = 'BRENT_M1', $986 = 'BRENT_M2', $987 = 'BRENT_M3', $988 = 'BRENT_M4', $989 = 'BRENT_M5', $990 = 'BRENT_M6', $991 = 'BRENT_M7', $992 = 'BRENT_M8', $993 = 'BRENT_M9', $994 = 'BRENT_N0', $995 = 'BRENT_N1', $996 = 'BRENT_N2', $997 = 'BRENT_N3', $998 = 'BRENT_N4', $999 = 'BRENT_N5', $1000 = 'BRENT_N6', $1001 = 'BRENT_N7', $1002 = 'BRENT_N8', $1003 = 'BRENT_N9', $1004 = 'BRENT_Q0', $1005 = 'BRENT_Q1', $1006 = 'BRENT_Q2', $1007 = 'BRENT_Q3', $1008 = 'BRENT_Q4', $1009 = 'BRENT_Q5', $1010 = 'BRENT_Q6', $1011 = 'BRENT_Q7', $1012 = 'BRENT_Q8', $1013 = 'BRENT_Q9', $1014 = 'BRENT_U0', $1015 = 'BRENT_U1', $1016 = 'BRENT_U2', $1017 = 'BRENT_U3', $1018 = 'BRENT_U4', $1019 = 'BRENT_U5', $1020 = 'BRENT_U6', $1021 = 'BRENT_U7', $1022 = 'BRENT_U8', $1023 = 'BRENT_U9', $1024 = 'BRENT_V0', $1025 = 'BRENT_V1', $1026 = 'BRENT_V2', $1027 = 'BRENT_V3', $1028 = 'BRENT_V4', $1029 = 'BRENT_V5', $1030 = 'BRENT_V6', $1031 = 'BRENT_V7', $1032 = 'BRENT_V8', $1033 = 'BRENT_V9', $1034 = 'BRENT_X0', $1035 = 'BRENT_X1', $1036 = 'BRENT_X2', $1037 = 'BRENT_X3', $1038 = 'BRENT_X4', $1039 = 'BRENT_X5', $1040 = 'BRENT_X6', $1041 = 'BRENT_X7', $1042 = 'BRENT_X8', $1043 = 'BRENT_X9', $1044 = 'BRENT_Z0', $1045 = 'BRENT_Z1', $1046 = 'BRENT_Z2', $1047 = 'BRENT_Z3', $1048 = 'BRENT_Z4', $1049 = 'BRENT_Z5', $1050 = 'BRENT_Z6', $1051 = 'BRENT_Z7', $1052 = 'BRENT_Z8', $1053 = 'BRENT_Z9', $1054 = 'BTCUSD', $1055 = 'CADCHF', $1056 = 'CADJPY', $1057 = 'CHFJPY', $1058 = 'CHFSGD', $1059 = 'CHINA50', $1060 = 'Coffee_F0', $1061 = 'Coffee_F1', $1062 = 'Coffee_F2', $1063 = 'Coffee_F3', $1064 = 'Coffee_F4', $1065 = 'Coffee_F5', $1066 = 'Coffee_F6', $1067 = 'Coffee_F7', $1068 = 'Coffee_F8', $1069 = 'Coffee_F9', $1070 = 'Coffee_G0', $1071 = 'Coffee_G1', $1072 = 'Coffee_G2', $1073 = 'Coffee_G3', $1074 = 'Coffee_G4', $1075 = 'Coffee_G5', $1076 = 'Coffee_G6', $1077 = 'Coffee_G7', $1078 = 'Coffee_G8', $1079 = 'Coffee_G9', $1080 = 'Coffee_H0', $1081 = 'Coffee_H1', $1082 = 'Coffee_H2', $1083 = 'Coffee_H3', $1084 = 'Coffee_H4', $1085 = 'Coffee_H5', $1086 = 'Coffee_H6', $1087 = 'Coffee_H7', $1088 = 'Coffee_H8', $1089 = 'Coffee_H9', $1090 = 'Coffee_J0', $1091 = 'Coffee_J1', $1092 = 'Coffee_J2', $1093 = 'Coffee_J3', $1094 = 'Coffee_J4', $1095 = 'Coffee_J5', $1096 = 'Coffee_J6', $1097 = 'Coffee_J7', $1098 = 'Coffee_J8', $1099 = 'Coffee_J9', $1100 = 'Coffee_K0', $1101 = 'Coffee_K1', $1102 = 'Coffee_K2', $1103 = 'Coffee_K3', $1104 = 'Coffee_K4', $1105 = 'Coffee_K5', $1106 = 'Coffee_K6', $1107 = 'Coffee_K7', $1108 = 'Coffee_K8', $1109 = 'Coffee_K9', $1110 = 'Coffee_M0', $1111 = 'Coffee_M1', $1112 = 'Coffee_M2', $1113 = 'Coffee_M3', $1114 = 'Coffee_M4', $1115 = 'Coffee_M5', $1116 = 'Coffee_M6', $1117 = 'Coffee_M7', $1118 = 'Coffee_M8', $1119 = 'Coffee_M9', $1120 = 'Coffee_N0', $1121 = 'Coffee_N1', $1122 = 'Coffee_N2', $1123 = 'Coffee_N3', $1124 = 'Coffee_N4', $1125 = 'Coffee_N5', $1126 = 'Coffee_N6', $1127 = 'Coffee_N7', $1128 = 'Coffee_N8', $1129 = 'Coffee_N9', $1130 = 'Coffee_Q0', $1131 = 'Coffee_Q1', $1132 = 'Coffee_Q2', $1133 = 'Coffee_Q3', $1134 = 'Coffee_Q4', $1135 = 'Coffee_Q5', $1136 = 'Coffee_Q6', $1137 = 'Coffee_Q7', $1138 = 'Coffee_Q8', $1139 = 'Coffee_Q9', $1140 = 'Coffee_U0', $1141 = 'Coffee_U1', $1142 = 'Coffee_U2', $1143 = 'Coffee_U3', $1144 = 'Coffee_U4', $1145 = 'Coffee_U5', $1146 = 'Coffee_U6', $1147 = 'Coffee_U7', $1148 = 'Coffee_U8', $1149 = 'Coffee_U9', $1150 = 'Coffee_V0', $1151 = 'Coffee_V1', $1152 = 'Coffee_V2', $1153 = 'Coffee_V3', $1154 = 'Coffee_V4', $1155 = 'Coffee_V5', $1156 = 'Coffee_V6', $1157 = 'Coffee_V7', $1158 = 'Coffee_V8', $1159 = 'Coffee_V9', $1160 = 'Coffee_X0', $1161 = 'Coffee_X1', $1162 = 'Coffee_X2', $1163 = 'Coffee_X3', $1164 = 'Coffee_X4', $1165 = 'Coffee_X5', $1166 = 'Coffee_X6', $1167 = 'Coffee_X7', $1168 = 'Coffee_X8', $1169 = 'Coffee_X9', $1170 = 'Coffee_Z0', $1171 = 'Coffee_Z1', $1172 = 'Coffee_Z2', $1173 = 'Coffee_Z3', $1174 = 'Coffee_Z4', $1175 = 'Coffee_Z5', $1176 = 'Coffee_Z6', $1177 = 'Coffee_Z7', $1178 = 'Coffee_Z8', $1179 = 'Coffee_Z9', $1180 = 'Corn_F0', $1181 = 'Corn_F1', $1182 = 'Corn_F2', $1183 = 'Corn_F3', $1184 = 'Corn_F4', $1185 = 'Corn_F5', $1186 = 'Corn_F6', $1187 = 'Corn_F7', $1188 = 'Corn_F8', $1189 = 'Corn_F9', $1190 = 'Corn_G0', $1191 = 'Corn_G1', $1192 = 'Corn_G2', $1193 = 'Corn_G3', $1194 = 'Corn_G4', $1195 = 'Corn_G5', $1196 = 'Corn_G6', $1197 = 'Corn_G7', $1198 = 'Corn_G8', $1199 = 'Corn_G9', $1200 = 'Corn_H0', $1201 = 'Corn_H1', $1202 = 'Corn_H2', $1203 = 'Corn_H3', $1204 = 'Corn_H4', $1205 = 'Corn_H5', $1206 = 'Corn_H6', $1207 = 'Corn_H7', $1208 = 'Corn_H8', $1209 = 'Corn_H9', $1210 = 'Corn_J0', $1211 = 'Corn_J1', $1212 = 'Corn_J2', $1213 = 'Corn_J3', $1214 = 'Corn_J4', $1215 = 'Corn_J5', $1216 = 'Corn_J6', $1217 = 'Corn_J7', $1218 = 'Corn_J8', $1219 = 'Corn_J9', $1220 = 'Corn_K0', $1221 = 'Corn_K1', $1222 = 'Corn_K2', $1223 = 'Corn_K3', $1224 = 'Corn_K4', $1225 = 'Corn_K5', $1226 = 'Corn_K6', $1227 = 'Corn_K7', $1228 = 'Corn_K8', $1229 = 'Corn_K9', $1230 = 'Corn_M0', $1231 = 'Corn_M1', $1232 = 'Corn_M2', $1233 = 'Corn_M3', $1234 = 'Corn_M4', $1235 = 'Corn_M5', $1236 = 'Corn_M6', $1237 = 'Corn_M7', $1238 = 'Corn_M8', $1239 = 'Corn_M9', $1240 = 'Corn_N0', $1241 = 'Corn_N1', $1242 = 'Corn_N2', $1243 = 'Corn_N3', $1244 = 'Corn_N4', $1245 = 'Corn_N5', $1246 = 'Corn_N6', $1247 = 'Corn_N7', $1248 = 'Corn_N8', $1249 = 'Corn_N9', $1250 = 'Corn_Q0', $1251 = 'Corn_Q1', $1252 = 'Corn_Q2', $1253 = 'Corn_Q3', $1254 = 'Corn_Q4', $1255 = 'Corn_Q5', $1256 = 'Corn_Q6', $1257 = 'Corn_Q7', $1258 = 'Corn_Q8', $1259 = 'Corn_Q9', $1260 = 'Corn_U0', $1261 = 'Corn_U1', $1262 = 'Corn_U2', $1263 = 'Corn_U3', $1264 = 'Corn_U4', $1265 = 'Corn_U5', $1266 = 'Corn_U6', $1267 = 'Corn_U7', $1268 = 'Corn_U8', $1269 = 'Corn_U9', $1270 = 'Corn_V0', $1271 = 'Corn_V1', $1272 = 'Corn_V2', $1273 = 'Corn_V3', $1274 = 'Corn_V4', $1275 = 'Corn_V5', $1276 = 'Corn_V6', $1277 = 'Corn_V7', $1278 = 'Corn_V8', $1279 = 'Corn_V9', $1280 = 'Corn_X0', $1281 = 'Corn_X1', $1282 = 'Corn_X2', $1283 = 'Corn_X3', $1284 = 'Corn_X4', $1285 = 'Corn_X5', $1286 = 'Corn_X6', $1287 = 'Corn_X7', $1288 = 'Corn_X8', $1289 = 'Corn_X9', $1290 = 'Corn_Z0', $1291 = 'Corn_Z1', $1292 = 'Corn_Z2', $1293 = 'Corn_Z3', $1294 = 'Corn_Z4', $1295 = 'Corn_Z5', $1296 = 'Corn_Z6', $1297 = 'Corn_Z7', $1298 = 'Corn_Z8', $1299 = 'Corn_Z9', $1300 = 'DE30', $1301 = 'ES35', $1302 = 'EURAUD', $1303 = 'EURCAD', $1304 = 'EURCHF', $1305 = 'EURDKK', $1306 = 'EURGBP', $1307 = 'EURHKD', $1308 = 'EURJPY', $1309 = 'EURNOK', $1310 = 'EURNZD', $1311 = 'EURPLN', $1312 = 'EURSEK', $1313 = 'EURSGD', $1314 = 'EURTRY', $1315 = 'EURUSD', $1316 = 'EURZAR', $1317 = 'F40', $1318 = 'GBPAUD', $1319 = 'GBPCAD', $1320 = 'GBPCHF', $1321 = 'GBPDKK', $1322 = 'GBPJPY', $1323 = 'GBPNOK', $1324 = 'GBPNZD', $1325 = 'GBPSEK', $1326 = 'GBPSGD', $1327 = 'GBPUSD', $1328 = 'HK50', $1329 = 'IT40', $1330 = 'JP225', $1331 = 'NOKJPY', $1332 = 'NOKSEK', $1333 = 'NZDCAD', $1334 = 'NZDCHF', $1335 = 'NZDJPY', $1336 = 'NZDUSD', $1337 = 'SEKJPY', $1338 = 'SGDJPY', $1339 = 'STOXX50', $1340 = 'Soybean_F0', $1341 = 'Soybean_F1', $1342 = 'Soybean_F2', $1343 = 'Soybean_F3', $1344 = 'Soybean_F4', $1345 = 'Soybean_F5', $1346 = 'Soybean_F6', $1347 = 'Soybean_F7', $1348 = 'Soybean_F8', $1349 = 'Soybean_F9', $1350 = 'Soybean_G0', $1351 = 'Soybean_G1', $1352 = 'Soybean_G2', $1353 = 'Soybean_G3', $1354 = 'Soybean_G4', $1355 = 'Soybean_G5', $1356 = 'Soybean_G6', $1357 = 'Soybean_G7', $1358 = 'Soybean_G8', $1359 = 'Soybean_G9', $1360 = 'Soybean_H0', $1361 = 'Soybean_H1', $1362 = 'Soybean_H2', $1363 = 'Soybean_H3', $1364 = 'Soybean_H4', $1365 = 'Soybean_H5', $1366 = 'Soybean_H6', $1367 = 'Soybean_H7', $1368 = 'Soybean_H8', $1369 = 'Soybean_H9', $1370 = 'Soybean_J0', $1371 = 'Soybean_J1', $1372 = 'Soybean_J2', $1373 = 'Soybean_J3', $1374 = 'Soybean_J4', $1375 = 'Soybean_J5', $1376 = 'Soybean_J6', $1377 = 'Soybean_J7', $1378 = 'Soybean_J8', $1379 = 'Soybean_J9', $1380 = 'Soybean_K0', $1381 = 'Soybean_K1', $1382 = 'Soybean_K2', $1383 = 'Soybean_K3', $1384 = 'Soybean_K4', $1385 = 'Soybean_K5', $1386 = 'Soybean_K6', $1387 = 'Soybean_K7', $1388 = 'Soybean_K8', $1389 = 'Soybean_K9', $1390 = 'Soybean_M0', $1391 = 'Soybean_M1', $1392 = 'Soybean_M2', $1393 = 'Soybean_M3', $1394 = 'Soybean_M4', $1395 = 'Soybean_M5', $1396 = 'Soybean_M6', $1397 = 'Soybean_M7', $1398 = 'Soybean_M8', $1399 = 'Soybean_M9', $1400 = 'Soybean_N0', $1401 = 'Soybean_N1', $1402 = 'Soybean_N2', $1403 = 'Soybean_N3', $1404 = 'Soybean_N4', $1405 = 'Soybean_N5', $1406 = 'Soybean_N6', $1407 = 'Soybean_N7', $1408 = 'Soybean_N8', $1409 = 'Soybean_N9', $1410 = 'Soybean_Q0', $1411 = 'Soybean_Q1', $1412 = 'Soybean_Q2', $1413 = 'Soybean_Q3', $1414 = 'Soybean_Q4', $1415 = 'Soybean_Q5', $1416 = 'Soybean_Q6', $1417 = 'Soybean_Q7', $1418 = 'Soybean_Q8', $1419 = 'Soybean_Q9', $1420 = 'Soybean_U0', $1421 = 'Soybean_U1', $1422 = 'Soybean_U2', $1423 = 'Soybean_U3', $1424 = 'Soybean_U4', $1425 = 'Soybean_U5', $1426 = 'Soybean_U6', $1427 = 'Soybean_U7', $1428 = 'Soybean_U8', $1429 = 'Soybean_U9', $1430 = 'Soybean_V0', $1431 = 'Soybean_V1', $1432 = 'Soybean_V2', $1433 = 'Soybean_V3', $1434 = 'Soybean_V4', $1435 = 'Soybean_V5', $1436 = 'Soybean_V6', $1437 = 'Soybean_V7', $1438 = 'Soybean_V8', $1439 = 'Soybean_V9', $1440 = 'Soybean_X0', $1441 = 'Soybean_X1', $1442 = 'Soybean_X2', $1443 = 'Soybean_X3', $1444 = 'Soybean_X4', $1445 = 'Soybean_X5', $1446 = 'Soybean_X6', $1447 = 'Soybean_X7', $1448 = 'Soybean_X8', $1449 = 'Soybean_X9', $1450 = 'Soybean_Z0', $1451 = 'Soybean_Z1', $1452 = 'Soybean_Z2', $1453 = 'Soybean_Z3', $1454 = 'Soybean_Z4', $1455 = 'Soybean_Z5', $1456 = 'Soybean_Z6', $1457 = 'Soybean_Z7', $1458 = 'Soybean_Z8', $1459 = 'Soybean_Z9', $1460 = 'Sugar_F0', $1461 = 'Sugar_F1', $1462 = 'Sugar_F2', $1463 = 'Sugar_F3', $1464 = 'Sugar_F4', $1465 = 'Sugar_F5', $1466 = 'Sugar_F6', $1467 = 'Sugar_F7', $1468 = 'Sugar_F8', $1469 = 'Sugar_F9', $1470 = 'Sugar_G0', $1471 = 'Sugar_G1', $1472 = 'Sugar_G2', $1473 = 'Sugar_G3', $1474 = 'Sugar_G4', $1475 = 'Sugar_G5', $1476 = 'Sugar_G6', $1477 = 'Sugar_G7', $1478 = 'Sugar_G8', $1479 = 'Sugar_G9', $1480 = 'Sugar_H0', $1481 = 'Sugar_H1', $1482 = 'Sugar_H2', $1483 = 'Sugar_H3', $1484 = 'Sugar_H4', $1485 = 'Sugar_H5', $1486 = 'Sugar_H6', $1487 = 'Sugar_H7', $1488 = 'Sugar_H8', $1489 = 'Sugar_H9', $1490 = 'Sugar_J0', $1491 = 'Sugar_J1', $1492 = 'Sugar_J2', $1493 = 'Sugar_J3', $1494 = 'Sugar_J4', $1495 = 'Sugar_J5', $1496 = 'Sugar_J6', $1497 = 'Sugar_J7', $1498 = 'Sugar_J8', $1499 = 'Sugar_J9', $1500 = 'Sugar_K0', $1501 = 'Sugar_K1', $1502 = 'Sugar_K2', $1503 = 'Sugar_K3', $1504 = 'Sugar_K4', $1505 = 'Sugar_K5', $1506 = 'Sugar_K6', $1507 = 'Sugar_K7', $1508 = 'Sugar_K8', $1509 = 'Sugar_K9', $1510 = 'Sugar_M0', $1511 = 'Sugar_M1', $1512 = 'Sugar_M2', $1513 = 'Sugar_M3', $1514 = 'Sugar_M4', $1515 = 'Sugar_M5', $1516 = 'Sugar_M6', $1517 = 'Sugar_M7', $1518 = 'Sugar_M8', $1519 = 'Sugar_M9', $1520 = 'Sugar_N0', $1521 = 'Sugar_N1', $1522 = 'Sugar_N2', $1523 = 'Sugar_N3', $1524 = 'Sugar_N4', $1525 = 'Sugar_N5', $1526 = 'Sugar_N6', $1527 = 'Sugar_N7', $1528 = 'Sugar_N8', $1529 = 'Sugar_N9', $1530 = 'Sugar_Q0', $1531 = 'Sugar_Q1', $1532 = 'Sugar_Q2', $1533 = 'Sugar_Q3', $1534 = 'Sugar_Q4', $1535 = 'Sugar_Q5', $1536 = 'Sugar_Q6', $1537 = 'Sugar_Q7', $1538 = 'Sugar_Q8', $1539 = 'Sugar_Q9', $1540 = 'Sugar_U0', $1541 = 'Sugar_U1', $1542 = 'Sugar_U2', $1543 = 'Sugar_U3', $1544 = 'Sugar_U4', $1545 = 'Sugar_U5', $1546 = 'Sugar_U6', $1547 = 'Sugar_U7', $1548 = 'Sugar_U8', $1549 = 'Sugar_U9', $1550 = 'Sugar_V0', $1551 = 'Sugar_V1', $1552 = 'Sugar_V2', $1553 = 'Sugar_V3', $1554 = 'Sugar_V4', $1555 = 'Sugar_V5', $1556 = 'Sugar_V6', $1557 = 'Sugar_V7', $1558 = 'Sugar_V8', $1559 = 'Sugar_V9', $1560 = 'Sugar_X0', $1561 = 'Sugar_X1', $1562 = 'Sugar_X2', $1563 = 'Sugar_X3', $1564 = 'Sugar_X4', $1565 = 'Sugar_X5', $1566 = 'Sugar_X6', $1567 = 'Sugar_X7', $1568 = 'Sugar_X8', $1569 = 'Sugar_X9', $1570 = 'Sugar_Z0', $1571 = 'Sugar_Z1', $1572 = 'Sugar_Z2', $1573 = 'Sugar_Z3', $1574 = 'Sugar_Z4', $1575 = 'Sugar_Z5', $1576 = 'Sugar_Z6', $1577 = 'Sugar_Z7', $1578 = 'Sugar_Z8', $1579 = 'Sugar_Z9', $1580 = 'UK100', $1581 = 'US2000', $1582 = 'US30', $1583 = 'US500', $1584 = 'USDCAD', $1585 = 'USDCHF', $1586 = 'USDCNH', $1587 = 'USDCZK', $1588 = 'USDDKK', $1589 = 'USDHKD', $1590 = 'USDHUF', $1591 = 'USDJPY', $1592 = 'USDMXN', $1593 = 'USDNOK', $1594 = 'USDPLN', $1595 = 'USDRUB', $1596 = 'USDSEK', $1597 = 'USDSGD', $1598 = 'USDTHB', $1599 = 'USDTRY', $1600 = 'USDZAR', $1601 = 'USTEC', $1602 = 'WTI_F0', $1603 = 'WTI_F1', $1604 = 'WTI_F2', $1605 = 'WTI_F3', $1606 = 'WTI_F4', $1607 = 'WTI_F5', $1608 = 'WTI_F6', $1609 = 'WTI_F7', $1610 = 'WTI_F8', $1611 = 'WTI_F9', $1612 = 'WTI_G0', $1613 = 'WTI_G1', $1614 = 'WTI_G2', $1615 = 'WTI_G3', $1616 = 'WTI_G4', $1617 = 'WTI_G5', $1618 = 'WTI_G6', $1619 = 'WTI_G7', $1620 = 'WTI_G8', $1621 = 'WTI_G9', $1622 = 'WTI_H0', $1623 = 'WTI_H1', $1624 = 'WTI_H2', $1625 = 'WTI_H3', $1626 = 'WTI_H4', $1627 = 'WTI_H5', $1628 = 'WTI_H6', $1629 = 'WTI_H7', $1630 = 'WTI_H8', $1631 = 'WTI_H9', $1632 = 'WTI_J0', $1633 = 'WTI_J1', $1634 = 'WTI_J2', $1635 = 'WTI_J3', $1636 = 'WTI_J4', $1637 = 'WTI_J5', $1638 = 'WTI_J6', $1639 = 'WTI_J7', $1640 = 'WTI_J8', $1641 = 'WTI_J9', $1642 = 'WTI_K0', $1643 = 'WTI_K1', $1644 = 'WTI_K2', $1645 = 'WTI_K3', $1646 = 'WTI_K4', $1647 = 'WTI_K5', $1648 = 'WTI_K6', $1649 = 'WTI_K7', $1650 = 'WTI_K8', $1651 = 'WTI_K9', $1652 = 'WTI_M0', $1653 = 'WTI_M1', $1654 = 'WTI_M2', $1655 = 'WTI_M3', $1656 = 'WTI_M4', $1657 = 'WTI_M5', $1658 = 'WTI_M6', $1659 = 'WTI_M7', $1660 = 'WTI_M8', $1661 = 'WTI_M9', $1662 = 'WTI_N0', $1663 = 'WTI_N1', $1664 = 'WTI_N2', $1665 = 'WTI_N3', $1666 = 'WTI_N4', $1667 = 'WTI_N5', $1668 = 'WTI_N6', $1669 = 'WTI_N7', $1670 = 'WTI_N8', $1671 = 'WTI_N9', $1672 = 'WTI_Q0', $1673 = 'WTI_Q1', $1674 = 'WTI_Q2', $1675 = 'WTI_Q3', $1676 = 'WTI_Q4', $1677 = 'WTI_Q5', $1678 = 'WTI_Q6', $1679 = 'WTI_Q7', $1680 = 'WTI_Q8', $1681 = 'WTI_Q9', $1682 = 'WTI_U0', $1683 = 'WTI_U1', $1684 = 'WTI_U2', $1685 = 'WTI_U3', $1686 = 'WTI_U4', $1687 = 'WTI_U5', $1688 = 'WTI_U6', $1689 = 'WTI_U7', $1690 = 'WTI_U8', $1691 = 'WTI_U9', $1692 = 'WTI_V0', $1693 = 'WTI_V1', $1694 = 'WTI_V2', $1695 = 'WTI_V3', $1696 = 'WTI_V4', $1697 = 'WTI_V5', $1698 = 'WTI_V6', $1699 = 'WTI_V7', $1700 = 'WTI_V8', $1701 = 'WTI_V9', $1702 = 'WTI_X0', $1703 = 'WTI_X1', $1704 = 'WTI_X2', $1705 = 'WTI_X3', $1706 = 'WTI_X4', $1707 = 'WTI_X5', $1708 = 'WTI_X6', $1709 = 'WTI_X7', $1710 = 'WTI_X8', $1711 = 'WTI_X9', $1712 = 'WTI_Z0', $1713 = 'WTI_Z1', $1714 = 'WTI_Z2', $1715 = 'WTI_Z3', $1716 = 'WTI_Z4', $1717 = 'WTI_Z5', $1718 = 'WTI_Z6', $1719 = 'WTI_Z7', $1720 = 'WTI_Z8', $1721 = 'WTI_Z9', $1722 = 'Wheat_F0', $1723 = 'Wheat_F1', $1724 = 'Wheat_F2', $1725 = 'Wheat_F3', $1726 = 'Wheat_F4', $1727 = 'Wheat_F5', $1728 = 'Wheat_F6', $1729 = 'Wheat_F7', $1730 = 'Wheat_F8', $1731 = 'Wheat_F9', $1732 = 'Wheat_G0', $1733 = 'Wheat_G1', $1734 = 'Wheat_G2', $1735 = 'Wheat_G3', $1736 = 'Wheat_G4', $1737 = 'Wheat_G5', $1738 = 'Wheat_G6', $1739 = 'Wheat_G7', $1740 = 'Wheat_G8', $1741 = 'Wheat_G9', $1742 = 'Wheat_H0', $1743 = 'Wheat_H1', $1744 = 'Wheat_H2', $1745 = 'Wheat_H3', $1746 = 'Wheat_H4', $1747 = 'Wheat_H5', $1748 = 'Wheat_H6', $1749 = 'Wheat_H7', $1750 = 'Wheat_H8', $1751 = 'Wheat_H9', $1752 = 'Wheat_J0', $1753 = 'Wheat_J1', $1754 = 'Wheat_J2', $1755 = 'Wheat_J3', $1756 = 'Wheat_J4', $1757 = 'Wheat_J5', $1758 = 'Wheat_J6', $1759 = 'Wheat_J7', $1760 = 'Wheat_J8', $1761 = 'Wheat_J9', $1762 = 'Wheat_K0', $1763 = 'Wheat_K1', $1764 = 'Wheat_K2', $1765 = 'Wheat_K3', $1766 = 'Wheat_K4', $1767 = 'Wheat_K5', $1768 = 'Wheat_K6', $1769 = 'Wheat_K7', $1770 = 'Wheat_K8', $1771 = 'Wheat_K9', $1772 = 'Wheat_M0', $1773 = 'Wheat_M1', $1774 = 'Wheat_M2', $1775 = 'Wheat_M3', $1776 = 'Wheat_M4', $1777 = 'Wheat_M5', $1778 = 'Wheat_M6', $1779 = 'Wheat_M7', $1780 = 'Wheat_M8', $1781 = 'Wheat_M9', $1782 = 'Wheat_N0', $1783 = 'Wheat_N1', $1784 = 'Wheat_N2', $1785 = 'Wheat_N3', $1786 = 'Wheat_N4', $1787 = 'Wheat_N5', $1788 = 'Wheat_N6', $1789 = 'Wheat_N7', $1790 = 'Wheat_N8', $1791 = 'Wheat_N9', $1792 = 'Wheat_Q0', $1793 = 'Wheat_Q1', $1794 = 'Wheat_Q2', $1795 = 'Wheat_Q3', $1796 = 'Wheat_Q4', $1797 = 'Wheat_Q5', $1798 = 'Wheat_Q6', $1799 = 'Wheat_Q7', $1800 = 'Wheat_Q8', $1801 = 'Wheat_Q9', $1802 = 'Wheat_U0', $1803 = 'Wheat_U1', $1804 = 'Wheat_U2', $1805 = 'Wheat_U3', $1806 = 'Wheat_U4', $1807 = 'Wheat_U5', $1808 = 'Wheat_U6', $1809 = 'Wheat_U7', $1810 = 'Wheat_U8', $1811 = 'Wheat_U9', $1812 = 'Wheat_V0', $1813 = 'Wheat_V1', $1814 = 'Wheat_V2', $1815 = 'Wheat_V3', $1816 = 'Wheat_V4', $1817 = 'Wheat_V5', $1818 = 'Wheat_V6', $1819 = 'Wheat_V7', $1820 = 'Wheat_V8', $1821 = 'Wheat_V9', $1822 = 'Wheat_X0', $1823 = 'Wheat_X1', $1824 = 'Wheat_X2', $1825 = 'Wheat_X3', $1826 = 'Wheat_X4', $1827 = 'Wheat_X5', $1828 = 'Wheat_X6', $1829 = 'Wheat_X7', $1830 = 'Wheat_X8', $1831 = 'Wheat_X9', $1832 = 'Wheat_Z0', $1833 = 'Wheat_Z1', $1834 = 'Wheat_Z2', $1835 = 'Wheat_Z3', $1836 = 'Wheat_Z4', $1837 = 'Wheat_Z5', $1838 = 'Wheat_Z6', $1839 = 'Wheat_Z7', $1840 = 'Wheat_Z8', $1841 = 'Wheat_Z9', $1842 = 'XAGEUR', $1843 = 'XAGUSD', $1844 = 'XAUEUR', $1845 = 'XAUUSD', $1846 = 'XBRUSD', $1847 = 'XNGUSD', $1848 = 'XPDUSD', $1849 = 'XPTUSD', $1850 = 'XTIUSD', $1851 = '5'
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-06-17 13:14:44 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.249 parameters: $1 = '972', $2 = 'ICMARKETS-AU-MT5', $3 = 'AUDSGD', $4 = 'CHFSGD', $5 = 'EURDKK', $6 = 'EURHKD', $7 = 'EURNOK', $8 = 'EURPLN', $9 = 'EURSEK', $10 = 'EURSGD', $11 = 'EURTRY', $12 = 'EURZAR', $13 = 'GBPDKK', $14 = 'GBPNOK', $15 = 'GBPSEK', $16 = 'GBPSGD', $17 = 'NOKJPY', $18 = 'NOKSEK', $19 = 'SEKJPY', $20 = 'SGDJPY', $21 = 'USDCNH', $22 = 'USDCZK', $23 = 'USDDKK', $24 = 'USDHKD', $25 = 'USDHUF', $26 = 'USDMXN', $27 = 'USDNOK', $28 = 'USDPLN', $29 = 'USDRUB', $30 = 'USDSEK', $31 = 'USDTHB', $32 = 'USDTRY', $33 = 'USDZAR', $34 = 'AUDUSD', $35 = 'EURUSD', $36 = 'GBPUSD', $37 = 'USDCAD', $38 = 'USDCHF', $39 = 'USDJPY', $40 = 'AUDCAD', $41 = 'AUDCHF', $42 = 'AUDJPY', $43 = 'AUDNZD', $44 = 'CADCHF', $45 = 'CADJPY', $46 = 'CHFJPY', $47 = 'EURAUD', $48 = 'EURCAD', $49 = 'EURCHF', $50 = 'EURGBP', $51 = 'EURJPY', $52 = 'EURNZD', $53 = 'GBPAUD', $54 = 'GBPCAD', $55 = 'GBPCHF', $56 = 'GBPJPY', $57 = 'GBPNZD', $58 = 'NZDCAD', $59 = 'NZDCHF', $60 = 'NZDJPY', $61 = 'NZDUSD', $62 = 'USDSGD', $63 = 'AUS200', $64 = 'CHINA50', $65 = 'DE30', $66 = 'ES35', $67 = 'F40', $68 = 'HK50', $69 = 'IT40', $70 = 'JP225', $71 = 'STOXX50', $72 = 'UK100', $73 = 'US2000', $74 = 'US30', $75 = 'US500', $76 = 'USTEC', $77 = 'XAGEUR', $78 = 'XAGUSD', $79 = 'XAUEUR', $80 = 'XAUUSD', $81 = 'XPDUSD', $82 = 'XPTUSD', $83 = 'XBRUSD', $84 = 'XNGUSD', $85 = 'XTIUSD', $86 = 'BTCUSD', $87 = 'BRENT_F0', $88 = 'BRENT_F1', $89 = 'BRENT_F2', $90 = 'BRENT_F3', $91 = 'BRENT_F4', $92 = 'BRENT_F5', $93 = 'BRENT_F6', $94 = 'BRENT_F7', $95 = 'BRENT_F8', $96 = 'BRENT_F9', $97 = 'BRENT_G0', $98 = 'BRENT_G1', $99 = 'BRENT_G2', $100 = 'BRENT_G3', $101 = 'BRENT_G4', $102 = 'BRENT_G5', $103 = 'BRENT_G6', $104 = 'BRENT_G7', $105 = 'BRENT_G8', $106 = 'BRENT_G9', $107 = 'BRENT_H0', $108 = 'BRENT_H1', $109 = 'BRENT_H2', $110 = 'BRENT_H3', $111 = 'BRENT_H4', $112 = 'BRENT_H5', $113 = 'BRENT_H6', $114 = 'BRENT_H7', $115 = 'BRENT_H8', $116 = 'BRENT_H9', $117 = 'BRENT_J0', $118 = 'BRENT_J1', $119 = 'BRENT_J2', $120 = 'BRENT_J3', $121 = 'BRENT_J4', $122 = 'BRENT_J5', $123 = 'BRENT_J6', $124 = 'BRENT_J7', $125 = 'BRENT_J8', $126 = 'BRENT_J9', $127 = 'BRENT_K0', $128 = 'BRENT_K1', $129 = 'BRENT_K2', $130 = 'BRENT_K3', $131 = 'BRENT_K4', $132 = 'BRENT_K5', $133 = 'BRENT_K6', $134 = 'BRENT_K7', $135 = 'BRENT_K8', $136 = 'BRENT_K9', $137 = 'BRENT_M0', $138 = 'BRENT_M1', $139 = 'BRENT_M2', $140 = 'BRENT_M3', $141 = 'BRENT_M4', $142 = 'BRENT_M5', $143 = 'BRENT_M6', $144 = 'BRENT_M7', $145 = 'BRENT_M8', $146 = 'BRENT_M9', $147 = 'BRENT_N0', $148 = 'BRENT_N1', $149 = 'BRENT_N2', $150 = 'BRENT_N3', $151 = 'BRENT_N4', $152 = 'BRENT_N5', $153 = 'BRENT_N6', $154 = 'BRENT_N7', $155 = 'BRENT_N8', $156 = 'BRENT_N9', $157 = 'BRENT_Q0', $158 = 'BRENT_Q1', $159 = 'BRENT_Q2', $160 = 'BRENT_Q3', $161 = 'BRENT_Q4', $162 = 'BRENT_Q5', $163 = 'BRENT_Q6', $164 = 'BRENT_Q7', $165 = 'BRENT_Q8', $166 = 'BRENT_Q9', $167 = 'BRENT_U0', $168 = 'BRENT_U1', $169 = 'BRENT_U2', $170 = 'BRENT_U3', $171 = 'BRENT_U4', $172 = 'BRENT_U5', $173 = 'BRENT_U6', $174 = 'BRENT_U7', $175 = 'BRENT_U8', $176 = 'BRENT_U9', $177 = 'BRENT_V0', $178 = 'BRENT_V1', $179 = 'BRENT_V2', $180 = 'BRENT_V3', $181 = 'BRENT_V4', $182 = 'BRENT_V5', $183 = 'BRENT_V6', $184 = 'BRENT_V7', $185 = 'BRENT_V8', $186 = 'BRENT_V9', $187 = 'BRENT_X0', $188 = 'BRENT_X1', $189 = 'BRENT_X2', $190 = 'BRENT_X3', $191 = 'BRENT_X4', $192 = 'BRENT_X5', $193 = 'BRENT_X6', $194 = 'BRENT_X7', $195 = 'BRENT_X8', $196 = 'BRENT_X9', $197 = 'BRENT_Z0', $198 = 'BRENT_Z1', $199 = 'BRENT_Z2', $200 = 'BRENT_Z3', $201 = 'BRENT_Z4', $202 = 'BRENT_Z5', $203 = 'BRENT_Z6', $204 = 'BRENT_Z7', $205 = 'BRENT_Z8', $206 = 'BRENT_Z9', $207 = 'Coffee_F0', $208 = 'Coffee_F1', $209 = 'Coffee_F2', $210 = 'Coffee_F3', $211 = 'Coffee_F4', $212 = 'Coffee_F5', $213 = 'Coffee_F6', $214 = 'Coffee_F7', $215 = 'Coffee_F8', $216 = 'Coffee_F9', $217 = 'Coffee_G0', $218 = 'Coffee_G1', $219 = 'Coffee_G2', $220 = 'Coffee_G3', $221 = 'Coffee_G4', $222 = 'Coffee_G5', $223 = 'Coffee_G6', $224 = 'Coffee_G7', $225 = 'Coffee_G8', $226 = 'Coffee_G9', $227 = 'Coffee_H0', $228 = 'Coffee_H1', $229 = 'Coffee_H2', $230 = 'Coffee_H3', $231 = 'Coffee_H4', $232 = 'Coffee_H5', $233 = 'Coffee_H6', $234 = 'Coffee_H7', $235 = 'Coffee_H8', $236 = 'Coffee_H9', $237 = 'Coffee_J0', $238 = 'Coffee_J1', $239 = 'Coffee_J2', $240 = 'Coffee_J3', $241 = 'Coffee_J4', $242 = 'Coffee_J5', $243 = 'Coffee_J6', $244 = 'Coffee_J7', $245 = 'Coffee_J8', $246 = 'Coffee_J9', $247 = 'Coffee_K0', $248 = 'Coffee_K1', $249 = 'Coffee_K2', $250 = 'Coffee_K3', $251 = 'Coffee_K4', $252 = 'Coffee_K5', $253 = 'Coffee_K6', $254 = 'Coffee_K7', $255 = 'Coffee_K8', $256 = 'Coffee_K9', $257 = 'Coffee_M0', $258 = 'Coffee_M1', $259 = 'Coffee_M2', $260 = 'Coffee_M3', $261 = 'Coffee_M4', $262 = 'Coffee_M5', $263 = 'Coffee_M6', $264 = 'Coffee_M7', $265 = 'Coffee_M8', $266 = 'Coffee_M9', $267 = 'Coffee_N0', $268 = 'Coffee_N1', $269 = 'Coffee_N2', $270 = 'Coffee_N3', $271 = 'Coffee_N4', $272 = 'Coffee_N5', $273 = 'Coffee_N6', $274 = 'Coffee_N7', $275 = 'Coffee_N8', $276 = 'Coffee_N9', $277 = 'Coffee_Q0', $278 = 'Coffee_Q1', $279 = 'Coffee_Q2', $280 = 'Coffee_Q3', $281 = 'Coffee_Q4', $282 = 'Coffee_Q5', $283 = 'Coffee_Q6', $284 = 'Coffee_Q7', $285 = 'Coffee_Q8', $286 = 'Coffee_Q9', $287 = 'Coffee_U0', $288 = 'Coffee_U1', $289 = 'Coffee_U2', $290 = 'Coffee_U3', $291 = 'Coffee_U4', $292 = 'Coffee_U5', $293 = 'Coffee_U6', $294 = 'Coffee_U7', $295 = 'Coffee_U8', $296 = 'Coffee_U9', $297 = 'Coffee_V0', $298 = 'Coffee_V1', $299 = 'Coffee_V2', $300 = 'Coffee_V3', $301 = 'Coffee_V4', $302 = 'Coffee_V5', $303 = 'Coffee_V6', $304 = 'Coffee_V7', $305 = 'Coffee_V8', $306 = 'Coffee_V9', $307 = 'Coffee_X0', $308 = 'Coffee_X1', $309 = 'Coffee_X2', $310 = 'Coffee_X3', $311 = 'Coffee_X4', $312 = 'Coffee_X5', $313 = 'Coffee_X6', $314 = 'Coffee_X7', $315 = 'Coffee_X8', $316 = 'Coffee_X9', $317 = 'Coffee_Z0', $318 = 'Coffee_Z1', $319 = 'Coffee_Z2', $320 = 'Coffee_Z3', $321 = 'Coffee_Z4', $322 = 'Coffee_Z5', $323 = 'Coffee_Z6', $324 = 'Coffee_Z7', $325 = 'Coffee_Z8', $326 = 'Coffee_Z9', $327 = 'Corn_F0', $328 = 'Corn_F1', $329 = 'Corn_F2', $330 = 'Corn_F3', $331 = 'Corn_F4', $332 = 'Corn_F5', $333 = 'Corn_F6', $334 = 'Corn_F7', $335 = 'Corn_F8', $336 = 'Corn_F9', $337 = 'Corn_G0', $338 = 'Corn_G1', $339 = 'Corn_G2', $340 = 'Corn_G3', $341 = 'Corn_G4', $342 = 'Corn_G5', $343 = 'Corn_G6', $344 = 'Corn_G7', $345 = 'Corn_G8', $346 = 'Corn_G9', $347 = 'Corn_H0', $348 = 'Corn_H1', $349 = 'Corn_H2', $350 = 'Corn_H3', $351 = 'Corn_H4', $352 = 'Corn_H5', $353 = 'Corn_H6', $354 = 'Corn_H7', $355 = 'Corn_H8', $356 = 'Corn_H9', $357 = 'Corn_J0', $358 = 'Corn_J1', $359 = 'Corn_J2', $360 = 'Corn_J3', $361 = 'Corn_J4', $362 = 'Corn_J5', $363 = 'Corn_J6', $364 = 'Corn_J7', $365 = 'Corn_J8', $366 = 'Corn_J9', $367 = 'Corn_K0', $368 = 'Corn_K1', $369 = 'Corn_K2', $370 = 'Corn_K3', $371 = 'Corn_K4', $372 = 'Corn_K5', $373 = 'Corn_K6', $374 = 'Corn_K7', $375 = 'Corn_K8', $376 = 'Corn_K9', $377 = 'Corn_M0', $378 = 'Corn_M1', $379 = 'Corn_M2', $380 = 'Corn_M3', $381 = 'Corn_M4', $382 = 'Corn_M5', $383 = 'Corn_M6', $384 = 'Corn_M7', $385 = 'Corn_M8', $386 = 'Corn_M9', $387 = 'Corn_N0', $388 = 'Corn_N1', $389 = 'Corn_N2', $390 = 'Corn_N3', $391 = 'Corn_N4', $392 = 'Corn_N5', $393 = 'Corn_N6', $394 = 'Corn_N7', $395 = 'Corn_N8', $396 = 'Corn_N9', $397 = 'Corn_Q0', $398 = 'Corn_Q1', $399 = 'Corn_Q2', $400 = 'Corn_Q3', $401 = 'Corn_Q4', $402 = 'Corn_Q5', $403 = 'Corn_Q6', $404 = 'Corn_Q7', $405 = 'Corn_Q8', $406 = 'Corn_Q9', $407 = 'Corn_U0', $408 = 'Corn_U1', $409 = 'Corn_U2', $410 = 'Corn_U3', $411 = 'Corn_U4', $412 = 'Corn_U5', $413 = 'Corn_U6', $414 = 'Corn_U7', $415 = 'Corn_U8', $416 = 'Corn_U9', $417 = 'Corn_V0', $418 = 'Corn_V1', $419 = 'Corn_V2', $420 = 'Corn_V3', $421 = 'Corn_V4', $422 = 'Corn_V5', $423 = 'Corn_V6', $424 = 'Corn_V7', $425 = 'Corn_V8', $426 = 'Corn_V9', $427 = 'Corn_X0', $428 = 'Corn_X1', $429 = 'Corn_X2', $430 = 'Corn_X3', $431 = 'Corn_X4', $432 = 'Corn_X5', $433 = 'Corn_X6', $434 = 'Corn_X7', $435 = 'Corn_X8', $436 = 'Corn_X9', $437 = 'Corn_Z0', $438 = 'Corn_Z1', $439 = 'Corn_Z2', $440 = 'Corn_Z3', $441 = 'Corn_Z4', $442 = 'Corn_Z5', $443 = 'Corn_Z6', $444 = 'Corn_Z7', $445 = 'Corn_Z8', $446 = 'Corn_Z9', $447 = 'Soybean_F0', $448 = 'Soybean_F1', $449 = 'Soybean_F2', $450 = 'Soybean_F3', $451 = 'Soybean_F4', $452 = 'Soybean_F5', $453 = 'Soybean_F6', $454 = 'Soybean_F7', $455 = 'Soybean_F8', $456 = 'Soybean_F9', $457 = 'Soybean_G0', $458 = 'Soybean_G1', $459 = 'Soybean_G2', $460 = 'Soybean_G3', $461 = 'Soybean_G4', $462 = 'Soybean_G5', $463 = 'Soybean_G6', $464 = 'Soybean_G7', $465 = 'Soybean_G8', $466 = 'Soybean_G9', $467 = 'Soybean_H0', $468 = 'Soybean_H1', $469 = 'Soybean_H2', $470 = 'Soybean_H3', $471 = 'Soybean_H4', $472 = 'Soybean_H5', $473 = 'Soybean_H6', $474 = 'Soybean_H7', $475 = 'Soybean_H8', $476 = 'Soybean_H9', $477 = 'Soybean_J0', $478 = 'Soybean_J1', $479 = 'Soybean_J2', $480 = 'Soybean_J3', $481 = 'Soybean_J4', $482 = 'Soybean_J5', $483 = 'Soybean_J6', $484 = 'Soybean_J7', $485 = 'Soybean_J8', $486 = 'Soybean_J9', $487 = 'Soybean_K0', $488 = 'Soybean_K1', $489 = 'Soybean_K2', $490 = 'Soybean_K3', $491 = 'Soybean_K4', $492 = 'Soybean_K5', $493 = 'Soybean_K6', $494 = 'Soybean_K7', $495 = 'Soybean_K8', $496 = 'Soybean_K9', $497 = 'Soybean_M0', $498 = 'Soybean_M1', $499 = 'Soybean_M2', $500 = 'Soybean_M3', $501 = 'Soybean_M4', $502 = 'Soybean_M5', $503 = 'Soybean_M6', $504 = 'Soybean_M7', $505 = 'Soybean_M8', $506 = 'Soybean_M9', $507 = 'Soybean_N0', $508 = 'Soybean_N1', $509 = 'Soybean_N2', $510 = 'Soybean_N3', $511 = 'Soybean_N4', $512 = 'Soybean_N5', $513 = 'Soybean_N6', $514 = 'Soybean_N7', $515 = 'Soybean_N8', $516 = 'Soybean_N9', $517 = 'Soybean_Q0', $518 = 'Soybean_Q1', $519 = 'Soybean_Q2', $520 = 'Soybean_Q3', $521 = 'Soybean_Q4', $522 = 'Soybean_Q5', $523 = 'Soybean_Q6', $524 = 'Soybean_Q7', $525 = 'Soybean_Q8', $526 = 'Soybean_Q9', $527 = 'Soybean_U0', $528 = 'Soybean_U1', $529 = 'Soybean_U2', $530 = 'Soybean_U3', $531 = 'Soybean_U4', $532 = 'Soybean_U5', $533 = 'Soybean_U6', $534 = 'Soybean_U7', $535 = 'Soybean_U8', $536 = 'Soybean_U9', $537 = 'Soybean_V0', $538 = 'Soybean_V1', $539 = 'Soybean_V2', $540 = 'Soybean_V3', $541 = 'Soybean_V4', $542 = 'Soybean_V5', $543 = 'Soybean_V6', $544 = 'Soybean_V7', $545 = 'Soybean_V8', $546 = 'Soybean_V9', $547 = 'Soybean_X0', $548 = 'Soybean_X1', $549 = 'Soybean_X2', $550 = 'Soybean_X3', $551 = 'Soybean_X4', $552 = 'Soybean_X5', $553 = 'Soybean_X6', $554 = 'Soybean_X7', $555 = 'Soybean_X8', $556 = 'Soybean_X9', $557 = 'Soybean_Z0', $558 = 'Soybean_Z1', $559 = 'Soybean_Z2', $560 = 'Soybean_Z3', $561 = 'Soybean_Z4', $562 = 'Soybean_Z5', $563 = 'Soybean_Z6', $564 = 'Soybean_Z7', $565 = 'Soybean_Z8', $566 = 'Soybean_Z9', $567 = 'Sugar_F0', $568 = 'Sugar_F1', $569 = 'Sugar_F2', $570 = 'Sugar_F3', $571 = 'Sugar_F4', $572 = 'Sugar_F5', $573 = 'Sugar_F6', $574 = 'Sugar_F7', $575 = 'Sugar_F8', $576 = 'Sugar_F9', $577 = 'Sugar_G0', $578 = 'Sugar_G1', $579 = 'Sugar_G2', $580 = 'Sugar_G3', $581 = 'Sugar_G4', $582 = 'Sugar_G5', $583 = 'Sugar_G6', $584 = 'Sugar_G7', $585 = 'Sugar_G8', $586 = 'Sugar_G9', $587 = 'Sugar_H0', $588 = 'Sugar_H1', $589 = 'Sugar_H2', $590 = 'Sugar_H3', $591 = 'Sugar_H4', $592 = 'Sugar_H5', $593 = 'Sugar_H6', $594 = 'Sugar_H7', $595 = 'Sugar_H8', $596 = 'Sugar_H9', $597 = 'Sugar_J0', $598 = 'Sugar_J1', $599 = 'Sugar_J2', $600 = 'Sugar_J3', $601 = 'Sugar_J4', $602 = 'Sugar_J5', $603 = 'Sugar_J6', $604 = 'Sugar_J7', $605 = 'Sugar_J8', $606 = 'Sugar_J9', $607 = 'Sugar_K0', $608 = 'Sugar_K1', $609 = 'Sugar_K2', $610 = 'Sugar_K3', $611 = 'Sugar_K4', $612 = 'Sugar_K5', $613 = 'Sugar_K6', $614 = 'Sugar_K7', $615 = 'Sugar_K8', $616 = 'Sugar_K9', $617 = 'Sugar_M0', $618 = 'Sugar_M1', $619 = 'Sugar_M2', $620 = 'Sugar_M3', $621 = 'Sugar_M4', $622 = 'Sugar_M5', $623 = 'Sugar_M6', $624 = 'Sugar_M7', $625 = 'Sugar_M8', $626 = 'Sugar_M9', $627 = 'Sugar_N0', $628 = 'Sugar_N1', $629 = 'Sugar_N2', $630 = 'Sugar_N3', $631 = 'Sugar_N4', $632 = 'Sugar_N5', $633 = 'Sugar_N6', $634 = 'Sugar_N7', $635 = 'Sugar_N8', $636 = 'Sugar_N9', $637 = 'Sugar_Q0', $638 = 'Sugar_Q1', $639 = 'Sugar_Q2', $640 = 'Sugar_Q3', $641 = 'Sugar_Q4', $642 = 'Sugar_Q5', $643 = 'Sugar_Q6', $644 = 'Sugar_Q7', $645 = 'Sugar_Q8', $646 = 'Sugar_Q9', $647 = 'Sugar_U0', $648 = 'Sugar_U1', $649 = 'Sugar_U2', $650 = 'Sugar_U3', $651 = 'Sugar_U4', $652 = 'Sugar_U5', $653 = 'Sugar_U6', $654 = 'Sugar_U7', $655 = 'Sugar_U8', $656 = 'Sugar_U9', $657 = 'Sugar_V0', $658 = 'Sugar_V1', $659 = 'Sugar_V2', $660 = 'Sugar_V3', $661 = 'Sugar_V4', $662 = 'Sugar_V5', $663 = 'Sugar_V6', $664 = 'Sugar_V7', $665 = 'Sugar_V8', $666 = 'Sugar_V9', $667 = 'Sugar_X0', $668 = 'Sugar_X1', $669 = 'Sugar_X2', $670 = 'Sugar_X3', $671 = 'Sugar_X4', $672 = 'Sugar_X5', $673 = 'Sugar_X6', $674 = 'Sugar_X7', $675 = 'Sugar_X8', $676 = 'Sugar_X9', $677 = 'Sugar_Z0', $678 = 'Sugar_Z1', $679 = 'Sugar_Z2', $680 = 'Sugar_Z3', $681 = 'Sugar_Z4', $682 = 'Sugar_Z5', $683 = 'Sugar_Z6', $684 = 'Sugar_Z7', $685 = 'Sugar_Z8', $686 = 'Sugar_Z9', $687 = 'Wheat_F0', $688 = 'Wheat_F1', $689 = 'Wheat_F2', $690 = 'Wheat_F3', $691 = 'Wheat_F4', $692 = 'Wheat_F5', $693 = 'Wheat_F6', $694 = 'Wheat_F7', $695 = 'Wheat_F8', $696 = 'Wheat_F9', $697 = 'Wheat_G0', $698 = 'Wheat_G1', $699 = 'Wheat_G2', $700 = 'Wheat_G3', $701 = 'Wheat_G4', $702 = 'Wheat_G5', $703 = 'Wheat_G6', $704 = 'Wheat_G7', $705 = 'Wheat_G8', $706 = 'Wheat_G9', $707 = 'Wheat_H0', $708 = 'Wheat_H1', $709 = 'Wheat_H2', $710 = 'Wheat_H3', $711 = 'Wheat_H4', $712 = 'Wheat_H5', $713 = 'Wheat_H6', $714 = 'Wheat_H7', $715 = 'Wheat_H8', $716 = 'Wheat_H9', $717 = 'Wheat_J0', $718 = 'Wheat_J1', $719 = 'Wheat_J2', $720 = 'Wheat_J3', $721 = 'Wheat_J4', $722 = 'Wheat_J5', $723 = 'Wheat_J6', $724 = 'Wheat_J7', $725 = 'Wheat_J8', $726 = 'Wheat_J9', $727 = 'Wheat_K0', $728 = 'Wheat_K1', $729 = 'Wheat_K2', $730 = 'Wheat_K3', $731 = 'Wheat_K4', $732 = 'Wheat_K5', $733 = 'Wheat_K6', $734 = 'Wheat_K7', $735 = 'Wheat_K8', $736 = 'Wheat_K9', $737 = 'Wheat_M0', $738 = 'Wheat_M1', $739 = 'Wheat_M2', $740 = 'Wheat_M3', $741 = 'Wheat_M4', $742 = 'Wheat_M5', $743 = 'Wheat_M6', $744 = 'Wheat_M7', $745 = 'Wheat_M8', $746 = 'Wheat_M9', $747 = 'Wheat_N0', $748 = 'Wheat_N1', $749 = 'Wheat_N2', $750 = 'Wheat_N3', $751 = 'Wheat_N4', $752 = 'Wheat_N5', $753 = 'Wheat_N6', $754 = 'Wheat_N7', $755 = 'Wheat_N8', $756 = 'Wheat_N9', $757 = 'Wheat_Q0', $758 = 'Wheat_Q1', $759 = 'Wheat_Q2', $760 = 'Wheat_Q3', $761 = 'Wheat_Q4', $762 = 'Wheat_Q5', $763 = 'Wheat_Q6', $764 = 'Wheat_Q7', $765 = 'Wheat_Q8', $766 = 'Wheat_Q9', $767 = 'Wheat_U0', $768 = 'Wheat_U1', $769 = 'Wheat_U2', $770 = 'Wheat_U3', $771 = 'Wheat_U4', $772 = 'Wheat_U5', $773 = 'Wheat_U6', $774 = 'Wheat_U7', $775 = 'Wheat_U8', $776 = 'Wheat_U9', $777 = 'Wheat_V0', $778 = 'Wheat_V1', $779 = 'Wheat_V2', $780 = 'Wheat_V3', $781 = 'Wheat_V4', $782 = 'Wheat_V5', $783 = 'Wheat_V6', $784 = 'Wheat_V7', $785 = 'Wheat_V8', $786 = 'Wheat_V9', $787 = 'Wheat_X0', $788 = 'Wheat_X1', $789 = 'Wheat_X2', $790 = 'Wheat_X3', $791 = 'Wheat_X4', $792 = 'Wheat_X5', $793 = 'Wheat_X6', $794 = 'Wheat_X7', $795 = 'Wheat_X8', $796 = 'Wheat_X9', $797 = 'Wheat_Z0', $798 = 'Wheat_Z1', $799 = 'Wheat_Z2', $800 = 'Wheat_Z3', $801 = 'Wheat_Z4', $802 = 'Wheat_Z5', $803 = 'Wheat_Z6', $804 = 'Wheat_Z7', $805 = 'Wheat_Z8', $806 = 'Wheat_Z9', $807 = 'WTI_F0', $808 = 'WTI_F1', $809 = 'WTI_F2', $810 = 'WTI_F3', $811 = 'WTI_F4', $812 = 'WTI_F5', $813 = 'WTI_F6', $814 = 'WTI_F7', $815 = 'WTI_F8', $816 = 'WTI_F9', $817 = 'WTI_G0', $818 = 'WTI_G1', $819 = 'WTI_G2', $820 = 'WTI_G3', $821 = 'WTI_G4', $822 = 'WTI_G5', $823 = 'WTI_G6', $824 = 'WTI_G7', $825 = 'WTI_G8', $826 = 'WTI_G9', $827 = 'WTI_H0', $828 = 'WTI_H1', $829 = 'WTI_H2', $830 = 'WTI_H3', $831 = 'WTI_H4', $832 = 'WTI_H5', $833 = 'WTI_H6', $834 = 'WTI_H7', $835 = 'WTI_H8', $836 = 'WTI_H9', $837 = 'WTI_J0', $838 = 'WTI_J1', $839 = 'WTI_J2', $840 = 'WTI_J3', $841 = 'WTI_J4', $842 = 'WTI_J5', $843 = 'WTI_J6', $844 = 'WTI_J7', $845 = 'WTI_J8', $846 = 'WTI_J9', $847 = 'WTI_K0', $848 = 'WTI_K1', $849 = 'WTI_K2', $850 = 'WTI_K3', $851 = 'WTI_K4', $852 = 'WTI_K5', $853 = 'WTI_K6', $854 = 'WTI_K7', $855 = 'WTI_K8', $856 = 'WTI_K9', $857 = 'WTI_M0', $858 = 'WTI_M1', $859 = 'WTI_M2', $860 = 'WTI_M3', $861 = 'WTI_M4', $862 = 'WTI_M5', $863 = 'WTI_M6', $864 = 'WTI_M7', $865 = 'WTI_M8', $866 = 'WTI_M9', $867 = 'WTI_N0', $868 = 'WTI_N1', $869 = 'WTI_N2', $870 = 'WTI_N3', $871 = 'WTI_N4', $872 = 'WTI_N5', $873 = 'WTI_N6', $874 = 'WTI_N7', $875 = 'WTI_N8', $876 = 'WTI_N9', $877 = 'WTI_Q0', $878 = 'WTI_Q1', $879 = 'WTI_Q2', $880 = 'WTI_Q3', $881 = 'WTI_Q4', $882 = 'WTI_Q5', $883 = 'WTI_Q6', $884 = 'WTI_Q7', $885 = 'WTI_Q8', $886 = 'WTI_Q9', $887 = 'WTI_U0', $888 = 'WTI_U1', $889 = 'WTI_U2', $890 = 'WTI_U3', $891 = 'WTI_U4', $892 = 'WTI_U5', $893 = 'WTI_U6', $894 = 'WTI_U7', $895 = 'WTI_U8', $896 = 'WTI_U9', $897 = 'WTI_V0', $898 = 'WTI_V1', $899 = 'WTI_V2', $900 = 'WTI_V3', $901 = 'WTI_V4', $902 = 'WTI_V5', $903 = 'WTI_V6', $904 = 'WTI_V7', $905 = 'WTI_V8', $906 = 'WTI_V9', $907 = 'WTI_X0', $908 = 'WTI_X1', $909 = 'WTI_X2', $910 = 'WTI_X3', $911 = 'WTI_X4', $912 = 'WTI_X5', $913 = 'WTI_X6', $914 = 'WTI_X7', $915 = 'WTI_X8', $916 = 'WTI_X9', $917 = 'WTI_Z0', $918 = 'WTI_Z1', $919 = 'WTI_Z2', $920 = 'WTI_Z3', $921 = 'WTI_Z4', $922 = 'WTI_Z5', $923 = 'WTI_Z6', $924 = 'WTI_Z7', $925 = 'WTI_Z8', $926 = 'WTI_Z9', $927 = 'AUDSGD', $928 = 'CHFSGD', $929 = 'EURDKK', $930 = 'EURHKD', $931 = 'EURNOK', $932 = 'EURPLN', $933 = 'EURSEK', $934 = 'EURSGD', $935 = 'EURTRY', $936 = 'EURZAR', $937 = 'GBPDKK', $938 = 'GBPNOK', $939 = 'GBPSEK', $940 = 'GBPSGD', $941 = 'NOKJPY', $942 = 'NOKSEK', $943 = 'SEKJPY', $944 = 'SGDJPY', $945 = 'USDCNH', $946 = 'USDCZK', $947 = 'USDDKK', $948 = 'USDHKD', $949 = 'USDHUF', $950 = 'USDMXN', $951 = 'USDNOK', $952 = 'USDPLN', $953 = 'USDRUB', $954 = 'USDSEK', $955 = 'USDTHB', $956 = 'USDTRY', $957 = 'USDZAR', $958 = 'AUDUSD', $959 = 'EURUSD', $960 = 'GBPUSD', $961 = 'USDCAD', $962 = 'USDCHF', $963 = 'USDJPY', $964 = 'AUDCAD', $965 = 'AUDCHF', $966 = 'AUDJPY', $967 = 'AUDNZD', $968 = 'CADCHF', $969 = 'CADJPY', $970 = 'CHFJPY', $971 = 'EURAUD', $972 = 'EURCAD', $973 = 'EURCHF', $974 = 'EURGBP', $975 = 'EURJPY', $976 = 'EURNZD', $977 = 'GBPAUD', $978 = 'GBPCAD', $979 = 'GBPCHF', $980 = 'GBPJPY', $981 = 'GBPNZD', $982 = 'NZDCAD', $983 = 'NZDCHF', $984 = 'NZDJPY', $985 = 'NZDUSD', $986 = 'USDSGD', $987 = 'AUS200', $988 = 'CHINA50', $989 = 'DE30', $990 = 'ES35', $991 = 'F40', $992 = 'HK50', $993 = 'IT40', $994 = 'JP225', $995 = 'STOXX50', $996 = 'UK100', $997 = 'US2000', $998 = 'US30', $999 = 'US500', $1000 = 'USTEC', $1001 = 'XAGEUR', $1002 = 'XAGUSD', $1003 = 'XAUEUR', $1004 = 'XAUUSD', $1005 = 'XPDUSD', $1006 = 'XPTUSD', $1007 = 'XBRUSD', $1008 = 'XNGUSD', $1009 = 'XTIUSD', $1010 = 'BTCUSD', $1011 = 'BRENT_F0', $1012 = 'BRENT_F1', $1013 = 'BRENT_F2', $1014 = 'BRENT_F3', $1015 = 'BRENT_F4', $1016 = 'BRENT_F5', $1017 = 'BRENT_F6', $1018 = 'BRENT_F7', $1019 = 'BRENT_F8', $1020 = 'BRENT_F9', $1021 = 'BRENT_G0', $1022 = 'BRENT_G1', $1023 = 'BRENT_G2', $1024 = 'BRENT_G3', $1025 = 'BRENT_G4', $1026 = 'BRENT_G5', $1027 = 'BRENT_G6', $1028 = 'BRENT_G7', $1029 = 'BRENT_G8', $1030 = 'BRENT_G9', $1031 = 'BRENT_H0', $1032 = 'BRENT_H1', $1033 = 'BRENT_H2', $1034 = 'BRENT_H3', $1035 = 'BRENT_H4', $1036 = 'BRENT_H5', $1037 = 'BRENT_H6', $1038 = 'BRENT_H7', $1039 = 'BRENT_H8', $1040 = 'BRENT_H9', $1041 = 'BRENT_J0', $1042 = 'BRENT_J1', $1043 = 'BRENT_J2', $1044 = 'BRENT_J3', $1045 = 'BRENT_J4', $1046 = 'BRENT_J5', $1047 = 'BRENT_J6', $1048 = 'BRENT_J7', $1049 = 'BRENT_J8', $1050 = 'BRENT_J9', $1051 = 'BRENT_K0', $1052 = 'BRENT_K1', $1053 = 'BRENT_K2', $1054 = 'BRENT_K3', $1055 = 'BRENT_K4', $1056 = 'BRENT_K5', $1057 = 'BRENT_K6', $1058 = 'BRENT_K7', $1059 = 'BRENT_K8', $1060 = 'BRENT_K9', $1061 = 'BRENT_M0', $1062 = 'BRENT_M1', $1063 = 'BRENT_M2', $1064 = 'BRENT_M3', $1065 = 'BRENT_M4', $1066 = 'BRENT_M5', $1067 = 'BRENT_M6', $1068 = 'BRENT_M7', $1069 = 'BRENT_M8', $1070 = 'BRENT_M9', $1071 = 'BRENT_N0', $1072 = 'BRENT_N1', $1073 = 'BRENT_N2', $1074 = 'BRENT_N3', $1075 = 'BRENT_N4', $1076 = 'BRENT_N5', $1077 = 'BRENT_N6', $1078 = 'BRENT_N7', $1079 = 'BRENT_N8', $1080 = 'BRENT_N9', $1081 = 'BRENT_Q0', $1082 = 'BRENT_Q1', $1083 = 'BRENT_Q2', $1084 = 'BRENT_Q3', $1085 = 'BRENT_Q4', $1086 = 'BRENT_Q5', $1087 = 'BRENT_Q6', $1088 = 'BRENT_Q7', $1089 = 'BRENT_Q8', $1090 = 'BRENT_Q9', $1091 = 'BRENT_U0', $1092 = 'BRENT_U1', $1093 = 'BRENT_U2', $1094 = 'BRENT_U3', $1095 = 'BRENT_U4', $1096 = 'BRENT_U5', $1097 = 'BRENT_U6', $1098 = 'BRENT_U7', $1099 = 'BRENT_U8', $1100 = 'BRENT_U9', $1101 = 'BRENT_V0', $1102 = 'BRENT_V1', $1103 = 'BRENT_V2', $1104 = 'BRENT_V3', $1105 = 'BRENT_V4', $1106 = 'BRENT_V5', $1107 = 'BRENT_V6', $1108 = 'BRENT_V7', $1109 = 'BRENT_V8', $1110 = 'BRENT_V9', $1111 = 'BRENT_X0', $1112 = 'BRENT_X1', $1113 = 'BRENT_X2', $1114 = 'BRENT_X3', $1115 = 'BRENT_X4', $1116 = 'BRENT_X5', $1117 = 'BRENT_X6', $1118 = 'BRENT_X7', $1119 = 'BRENT_X8', $1120 = 'BRENT_X9', $1121 = 'BRENT_Z0', $1122 = 'BRENT_Z1', $1123 = 'BRENT_Z2', $1124 = 'BRENT_Z3', $1125 = 'BRENT_Z4', $1126 = 'BRENT_Z5', $1127 = 'BRENT_Z6', $1128 = 'BRENT_Z7', $1129 = 'BRENT_Z8', $1130 = 'BRENT_Z9', $1131 = 'Coffee_F0', $1132 = 'Coffee_F1', $1133 = 'Coffee_F2', $1134 = 'Coffee_F3', $1135 = 'Coffee_F4', $1136 = 'Coffee_F5', $1137 = 'Coffee_F6', $1138 = 'Coffee_F7', $1139 = 'Coffee_F8', $1140 = 'Coffee_F9', $1141 = 'Coffee_G0', $1142 = 'Coffee_G1', $1143 = 'Coffee_G2', $1144 = 'Coffee_G3', $1145 = 'Coffee_G4', $1146 = 'Coffee_G5', $1147 = 'Coffee_G6', $1148 = 'Coffee_G7', $1149 = 'Coffee_G8', $1150 = 'Coffee_G9', $1151 = 'Coffee_H0', $1152 = 'Coffee_H1', $1153 = 'Coffee_H2', $1154 = 'Coffee_H3', $1155 = 'Coffee_H4', $1156 = 'Coffee_H5', $1157 = 'Coffee_H6', $1158 = 'Coffee_H7', $1159 = 'Coffee_H8', $1160 = 'Coffee_H9', $1161 = 'Coffee_J0', $1162 = 'Coffee_J1', $1163 = 'Coffee_J2', $1164 = 'Coffee_J3', $1165 = 'Coffee_J4', $1166 = 'Coffee_J5', $1167 = 'Coffee_J6', $1168 = 'Coffee_J7', $1169 = 'Coffee_J8', $1170 = 'Coffee_J9', $1171 = 'Coffee_K0', $1172 = 'Coffee_K1', $1173 = 'Coffee_K2', $1174 = 'Coffee_K3', $1175 = 'Coffee_K4', $1176 = 'Coffee_K5', $1177 = 'Coffee_K6', $1178 = 'Coffee_K7', $1179 = 'Coffee_K8', $1180 = 'Coffee_K9', $1181 = 'Coffee_M0', $1182 = 'Coffee_M1', $1183 = 'Coffee_M2', $1184 = 'Coffee_M3', $1185 = 'Coffee_M4', $1186 = 'Coffee_M5', $1187 = 'Coffee_M6', $1188 = 'Coffee_M7', $1189 = 'Coffee_M8', $1190 = 'Coffee_M9', $1191 = 'Coffee_N0', $1192 = 'Coffee_N1', $1193 = 'Coffee_N2', $1194 = 'Coffee_N3', $1195 = 'Coffee_N4', $1196 = 'Coffee_N5', $1197 = 'Coffee_N6', $1198 = 'Coffee_N7', $1199 = 'Coffee_N8', $1200 = 'Coffee_N9', $1201 = 'Coffee_Q0', $1202 = 'Coffee_Q1', $1203 = 'Coffee_Q2', $1204 = 'Coffee_Q3', $1205 = 'Coffee_Q4', $1206 = 'Coffee_Q5', $1207 = 'Coffee_Q6', $1208 = 'Coffee_Q7', $1209 = 'Coffee_Q8', $1210 = 'Coffee_Q9', $1211 = 'Coffee_U0', $1212 = 'Coffee_U1', $1213 = 'Coffee_U2', $1214 = 'Coffee_U3', $1215 = 'Coffee_U4', $1216 = 'Coffee_U5', $1217 = 'Coffee_U6', $1218 = 'Coffee_U7', $1219 = 'Coffee_U8', $1220 = 'Coffee_U9', $1221 = 'Coffee_V0', $1222 = 'Coffee_V1', $1223 = 'Coffee_V2', $1224 = 'Coffee_V3', $1225 = 'Coffee_V4', $1226 = 'Coffee_V5', $1227 = 'Coffee_V6', $1228 = 'Coffee_V7', $1229 = 'Coffee_V8', $1230 = 'Coffee_V9', $1231 = 'Coffee_X0', $1232 = 'Coffee_X1', $1233 = 'Coffee_X2', $1234 = 'Coffee_X3', $1235 = 'Coffee_X4', $1236 = 'Coffee_X5', $1237 = 'Coffee_X6', $1238 = 'Coffee_X7', $1239 = 'Coffee_X8', $1240 = 'Coffee_X9', $1241 = 'Coffee_Z0', $1242 = 'Coffee_Z1', $1243 = 'Coffee_Z2', $1244 = 'Coffee_Z3', $1245 = 'Coffee_Z4', $1246 = 'Coffee_Z5', $1247 = 'Coffee_Z6', $1248 = 'Coffee_Z7', $1249 = 'Coffee_Z8', $1250 = 'Coffee_Z9', $1251 = 'Corn_F0', $1252 = 'Corn_F1', $1253 = 'Corn_F2', $1254 = 'Corn_F3', $1255 = 'Corn_F4', $1256 = 'Corn_F5', $1257 = 'Corn_F6', $1258 = 'Corn_F7', $1259 = 'Corn_F8', $1260 = 'Corn_F9', $1261 = 'Corn_G0', $1262 = 'Corn_G1', $1263 = 'Corn_G2', $1264 = 'Corn_G3', $1265 = 'Corn_G4', $1266 = 'Corn_G5', $1267 = 'Corn_G6', $1268 = 'Corn_G7', $1269 = 'Corn_G8', $1270 = 'Corn_G9', $1271 = 'Corn_H0', $1272 = 'Corn_H1', $1273 = 'Corn_H2', $1274 = 'Corn_H3', $1275 = 'Corn_H4', $1276 = 'Corn_H5', $1277 = 'Corn_H6', $1278 = 'Corn_H7', $1279 = 'Corn_H8', $1280 = 'Corn_H9', $1281 = 'Corn_J0', $1282 = 'Corn_J1', $1283 = 'Corn_J2', $1284 = 'Corn_J3', $1285 = 'Corn_J4', $1286 = 'Corn_J5', $1287 = 'Corn_J6', $1288 = 'Corn_J7', $1289 = 'Corn_J8', $1290 = 'Corn_J9', $1291 = 'Corn_K0', $1292 = 'Corn_K1', $1293 = 'Corn_K2', $1294 = 'Corn_K3', $1295 = 'Corn_K4', $1296 = 'Corn_K5', $1297 = 'Corn_K6', $1298 = 'Corn_K7', $1299 = 'Corn_K8', $1300 = 'Corn_K9', $1301 = 'Corn_M0', $1302 = 'Corn_M1', $1303 = 'Corn_M2', $1304 = 'Corn_M3', $1305 = 'Corn_M4', $1306 = 'Corn_M5', $1307 = 'Corn_M6', $1308 = 'Corn_M7', $1309 = 'Corn_M8', $1310 = 'Corn_M9', $1311 = 'Corn_N0', $1312 = 'Corn_N1', $1313 = 'Corn_N2', $1314 = 'Corn_N3', $1315 = 'Corn_N4', $1316 = 'Corn_N5', $1317 = 'Corn_N6', $1318 = 'Corn_N7', $1319 = 'Corn_N8', $1320 = 'Corn_N9', $1321 = 'Corn_Q0', $1322 = 'Corn_Q1', $1323 = 'Corn_Q2', $1324 = 'Corn_Q3', $1325 = 'Corn_Q4', $1326 = 'Corn_Q5', $1327 = 'Corn_Q6', $1328 = 'Corn_Q7', $1329 = 'Corn_Q8', $1330 = 'Corn_Q9', $1331 = 'Corn_U0', $1332 = 'Corn_U1', $1333 = 'Corn_U2', $1334 = 'Corn_U3', $1335 = 'Corn_U4', $1336 = 'Corn_U5', $1337 = 'Corn_U6', $1338 = 'Corn_U7', $1339 = 'Corn_U8', $1340 = 'Corn_U9', $1341 = 'Corn_V0', $1342 = 'Corn_V1', $1343 = 'Corn_V2', $1344 = 'Corn_V3', $1345 = 'Corn_V4', $1346 = 'Corn_V5', $1347 = 'Corn_V6', $1348 = 'Corn_V7', $1349 = 'Corn_V8', $1350 = 'Corn_V9', $1351 = 'Corn_X0', $1352 = 'Corn_X1', $1353 = 'Corn_X2', $1354 = 'Corn_X3', $1355 = 'Corn_X4', $1356 = 'Corn_X5', $1357 = 'Corn_X6', $1358 = 'Corn_X7', $1359 = 'Corn_X8', $1360 = 'Corn_X9', $1361 = 'Corn_Z0', $1362 = 'Corn_Z1', $1363 = 'Corn_Z2', $1364 = 'Corn_Z3', $1365 = 'Corn_Z4', $1366 = 'Corn_Z5', $1367 = 'Corn_Z6', $1368 = 'Corn_Z7', $1369 = 'Corn_Z8', $1370 = 'Corn_Z9', $1371 = 'Soybean_F0', $1372 = 'Soybean_F1', $1373 = 'Soybean_F2', $1374 = 'Soybean_F3', $1375 = 'Soybean_F4', $1376 = 'Soybean_F5', $1377 = 'Soybean_F6', $1378 = 'Soybean_F7', $1379 = 'Soybean_F8', $1380 = 'Soybean_F9', $1381 = 'Soybean_G0', $1382 = 'Soybean_G1', $1383 = 'Soybean_G2', $1384 = 'Soybean_G3', $1385 = 'Soybean_G4', $1386 = 'Soybean_G5', $1387 = 'Soybean_G6', $1388 = 'Soybean_G7', $1389 = 'Soybean_G8', $1390 = 'Soybean_G9', $1391 = 'Soybean_H0', $1392 = 'Soybean_H1', $1393 = 'Soybean_H2', $1394 = 'Soybean_H3', $1395 = 'Soybean_H4', $1396 = 'Soybean_H5', $1397 = 'Soybean_H6', $1398 = 'Soybean_H7', $1399 = 'Soybean_H8', $1400 = 'Soybean_H9', $1401 = 'Soybean_J0', $1402 = 'Soybean_J1', $1403 = 'Soybean_J2', $1404 = 'Soybean_J3', $1405 = 'Soybean_J4', $1406 = 'Soybean_J5', $1407 = 'Soybean_J6', $1408 = 'Soybean_J7', $1409 = 'Soybean_J8', $1410 = 'Soybean_J9', $1411 = 'Soybean_K0', $1412 = 'Soybean_K1', $1413 = 'Soybean_K2', $1414 = 'Soybean_K3', $1415 = 'Soybean_K4', $1416 = 'Soybean_K5', $1417 = 'Soybean_K6', $1418 = 'Soybean_K7', $1419 = 'Soybean_K8', $1420 = 'Soybean_K9', $1421 = 'Soybean_M0', $1422 = 'Soybean_M1', $1423 = 'Soybean_M2', $1424 = 'Soybean_M3', $1425 = 'Soybean_M4', $1426 = 'Soybean_M5', $1427 = 'Soybean_M6', $1428 = 'Soybean_M7', $1429 = 'Soybean_M8', $1430 = 'Soybean_M9', $1431 = 'Soybean_N0', $1432 = 'Soybean_N1', $1433 = 'Soybean_N2', $1434 = 'Soybean_N3', $1435 = 'Soybean_N4', $1436 = 'Soybean_N5', $1437 = 'Soybean_N6', $1438 = 'Soybean_N7', $1439 = 'Soybean_N8', $1440 = 'Soybean_N9', $1441 = 'Soybean_Q0', $1442 = 'Soybean_Q1', $1443 = 'Soybean_Q2', $1444 = 'Soybean_Q3', $1445 = 'Soybean_Q4', $1446 = 'Soybean_Q5', $1447 = 'Soybean_Q6', $1448 = 'Soybean_Q7', $1449 = 'Soybean_Q8', $1450 = 'Soybean_Q9', $1451 = 'Soybean_U0', $1452 = 'Soybean_U1', $1453 = 'Soybean_U2', $1454 = 'Soybean_U3', $1455 = 'Soybean_U4', $1456 = 'Soybean_U5', $1457 = 'Soybean_U6', $1458 = 'Soybean_U7', $1459 = 'Soybean_U8', $1460 = 'Soybean_U9', $1461 = 'Soybean_V0', $1462 = 'Soybean_V1', $1463 = 'Soybean_V2', $1464 = 'Soybean_V3', $1465 = 'Soybean_V4', $1466 = 'Soybean_V5', $1467 = 'Soybean_V6', $1468 = 'Soybean_V7', $1469 = 'Soybean_V8', $1470 = 'Soybean_V9', $1471 = 'Soybean_X0', $1472 = 'Soybean_X1', $1473 = 'Soybean_X2', $1474 = 'Soybean_X3', $1475 = 'Soybean_X4', $1476 = 'Soybean_X5', $1477 = 'Soybean_X6', $1478 = 'Soybean_X7', $1479 = 'Soybean_X8', $1480 = 'Soybean_X9', $1481 = 'Soybean_Z0', $1482 = 'Soybean_Z1', $1483 = 'Soybean_Z2', $1484 = 'Soybean_Z3', $1485 = 'Soybean_Z4', $1486 = 'Soybean_Z5', $1487 = 'Soybean_Z6', $1488 = 'Soybean_Z7', $1489 = 'Soybean_Z8', $1490 = 'Soybean_Z9', $1491 = 'Sugar_F0', $1492 = 'Sugar_F1', $1493 = 'Sugar_F2', $1494 = 'Sugar_F3', $1495 = 'Sugar_F4', $1496 = 'Sugar_F5', $1497 = 'Sugar_F6', $1498 = 'Sugar_F7', $1499 = 'Sugar_F8', $1500 = 'Sugar_F9', $1501 = 'Sugar_G0', $1502 = 'Sugar_G1', $1503 = 'Sugar_G2', $1504 = 'Sugar_G3', $1505 = 'Sugar_G4', $1506 = 'Sugar_G5', $1507 = 'Sugar_G6', $1508 = 'Sugar_G7', $1509 = 'Sugar_G8', $1510 = 'Sugar_G9', $1511 = 'Sugar_H0', $1512 = 'Sugar_H1', $1513 = 'Sugar_H2', $1514 = 'Sugar_H3', $1515 = 'Sugar_H4', $1516 = 'Sugar_H5', $1517 = 'Sugar_H6', $1518 = 'Sugar_H7', $1519 = 'Sugar_H8', $1520 = 'Sugar_H9', $1521 = 'Sugar_J0', $1522 = 'Sugar_J1', $1523 = 'Sugar_J2', $1524 = 'Sugar_J3', $1525 = 'Sugar_J4', $1526 = 'Sugar_J5', $1527 = 'Sugar_J6', $1528 = 'Sugar_J7', $1529 = 'Sugar_J8', $1530 = 'Sugar_J9', $1531 = 'Sugar_K0', $1532 = 'Sugar_K1', $1533 = 'Sugar_K2', $1534 = 'Sugar_K3', $1535 = 'Sugar_K4', $1536 = 'Sugar_K5', $1537 = 'Sugar_K6', $1538 = 'Sugar_K7', $1539 = 'Sugar_K8', $1540 = 'Sugar_K9', $1541 = 'Sugar_M0', $1542 = 'Sugar_M1', $1543 = 'Sugar_M2', $1544 = 'Sugar_M3', $1545 = 'Sugar_M4', $1546 = 'Sugar_M5', $1547 = 'Sugar_M6', $1548 = 'Sugar_M7', $1549 = 'Sugar_M8', $1550 = 'Sugar_M9', $1551 = 'Sugar_N0', $1552 = 'Sugar_N1', $1553 = 'Sugar_N2', $1554 = 'Sugar_N3', $1555 = 'Sugar_N4', $1556 = 'Sugar_N5', $1557 = 'Sugar_N6', $1558 = 'Sugar_N7', $1559 = 'Sugar_N8', $1560 = 'Sugar_N9', $1561 = 'Sugar_Q0', $1562 = 'Sugar_Q1', $1563 = 'Sugar_Q2', $1564 = 'Sugar_Q3', $1565 = 'Sugar_Q4', $1566 = 'Sugar_Q5', $1567 = 'Sugar_Q6', $1568 = 'Sugar_Q7', $1569 = 'Sugar_Q8', $1570 = 'Sugar_Q9', $1571 = 'Sugar_U0', $1572 = 'Sugar_U1', $1573 = 'Sugar_U2', $1574 = 'Sugar_U3', $1575 = 'Sugar_U4', $1576 = 'Sugar_U5', $1577 = 'Sugar_U6', $1578 = 'Sugar_U7', $1579 = 'Sugar_U8', $1580 = 'Sugar_U9', $1581 = 'Sugar_V0', $1582 = 'Sugar_V1', $1583 = 'Sugar_V2', $1584 = 'Sugar_V3', $1585 = 'Sugar_V4', $1586 = 'Sugar_V5', $1587 = 'Sugar_V6', $1588 = 'Sugar_V7', $1589 = 'Sugar_V8', $1590 = 'Sugar_V9', $1591 = 'Sugar_X0', $1592 = 'Sugar_X1', $1593 = 'Sugar_X2', $1594 = 'Sugar_X3', $1595 = 'Sugar_X4', $1596 = 'Sugar_X5', $1597 = 'Sugar_X6', $1598 = 'Sugar_X7', $1599 = 'Sugar_X8', $1600 = 'Sugar_X9', $1601 = 'Sugar_Z0', $1602 = 'Sugar_Z1', $1603 = 'Sugar_Z2', $1604 = 'Sugar_Z3', $1605 = 'Sugar_Z4', $1606 = 'Sugar_Z5', $1607 = 'Sugar_Z6', $1608 = 'Sugar_Z7', $1609 = 'Sugar_Z8', $1610 = 'Sugar_Z9', $1611 = 'Wheat_F0', $1612 = 'Wheat_F1', $1613 = 'Wheat_F2', $1614 = 'Wheat_F3', $1615 = 'Wheat_F4', $1616 = 'Wheat_F5', $1617 = 'Wheat_F6', $1618 = 'Wheat_F7', $1619 = 'Wheat_F8', $1620 = 'Wheat_F9', $1621 = 'Wheat_G0', $1622 = 'Wheat_G1', $1623 = 'Wheat_G2', $1624 = 'Wheat_G3', $1625 = 'Wheat_G4', $1626 = 'Wheat_G5', $1627 = 'Wheat_G6', $1628 = 'Wheat_G7', $1629 = 'Wheat_G8', $1630 = 'Wheat_G9', $1631 = 'Wheat_H0', $1632 = 'Wheat_H1', $1633 = 'Wheat_H2', $1634 = 'Wheat_H3', $1635 = 'Wheat_H4', $1636 = 'Wheat_H5', $1637 = 'Wheat_H6', $1638 = 'Wheat_H7', $1639 = 'Wheat_H8', $1640 = 'Wheat_H9', $1641 = 'Wheat_J0', $1642 = 'Wheat_J1', $1643 = 'Wheat_J2', $1644 = 'Wheat_J3', $1645 = 'Wheat_J4', $1646 = 'Wheat_J5', $1647 = 'Wheat_J6', $1648 = 'Wheat_J7', $1649 = 'Wheat_J8', $1650 = 'Wheat_J9', $1651 = 'Wheat_K0', $1652 = 'Wheat_K1', $1653 = 'Wheat_K2', $1654 = 'Wheat_K3', $1655 = 'Wheat_K4', $1656 = 'Wheat_K5', $1657 = 'Wheat_K6', $1658 = 'Wheat_K7', $1659 = 'Wheat_K8', $1660 = 'Wheat_K9', $1661 = 'Wheat_M0', $1662 = 'Wheat_M1', $1663 = 'Wheat_M2', $1664 = 'Wheat_M3', $1665 = 'Wheat_M4', $1666 = 'Wheat_M5', $1667 = 'Wheat_M6', $1668 = 'Wheat_M7', $1669 = 'Wheat_M8', $1670 = 'Wheat_M9', $1671 = 'Wheat_N0', $1672 = 'Wheat_N1', $1673 = 'Wheat_N2', $1674 = 'Wheat_N3', $1675 = 'Wheat_N4', $1676 = 'Wheat_N5', $1677 = 'Wheat_N6', $1678 = 'Wheat_N7', $1679 = 'Wheat_N8', $1680 = 'Wheat_N9', $1681 = 'Wheat_Q0', $1682 = 'Wheat_Q1', $1683 = 'Wheat_Q2', $1684 = 'Wheat_Q3', $1685 = 'Wheat_Q4', $1686 = 'Wheat_Q5', $1687 = 'Wheat_Q6', $1688 = 'Wheat_Q7', $1689 = 'Wheat_Q8', $1690 = 'Wheat_Q9', $1691 = 'Wheat_U0', $1692 = 'Wheat_U1', $1693 = 'Wheat_U2', $1694 = 'Wheat_U3', $1695 = 'Wheat_U4', $1696 = 'Wheat_U5', $1697 = 'Wheat_U6', $1698 = 'Wheat_U7', $1699 = 'Wheat_U8', $1700 = 'Wheat_U9', $1701 = 'Wheat_V0', $1702 = 'Wheat_V1', $1703 = 'Wheat_V2', $1704 = 'Wheat_V3', $1705 = 'Wheat_V4', $1706 = 'Wheat_V5', $1707 = 'Wheat_V6', $1708 = 'Wheat_V7', $1709 = 'Wheat_V8', $1710 = 'Wheat_V9', $1711 = 'Wheat_X0', $1712 = 'Wheat_X1', $1713 = 'Wheat_X2', $1714 = 'Wheat_X3', $1715 = 'Wheat_X4', $1716 = 'Wheat_X5', $1717 = 'Wheat_X6', $1718 = 'Wheat_X7', $1719 = 'Wheat_X8', $1720 = 'Wheat_X9', $1721 = 'Wheat_Z0', $1722 = 'Wheat_Z1', $1723 = 'Wheat_Z2', $1724 = 'Wheat_Z3', $1725 = 'Wheat_Z4', $1726 = 'Wheat_Z5', $1727 = 'Wheat_Z6', $1728 = 'Wheat_Z7', $1729 = 'Wheat_Z8', $1730 = 'Wheat_Z9', $1731 = 'WTI_F0', $1732 = 'WTI_F1', $1733 = 'WTI_F2', $1734 = 'WTI_F3', $1735 = 'WTI_F4', $1736 = 'WTI_F5', $1737 = 'WTI_F6', $1738 = 'WTI_F7', $1739 = 'WTI_F8', $1740 = 'WTI_F9', $1741 = 'WTI_G0', $1742 = 'WTI_G1', $1743 = 'WTI_G2', $1744 = 'WTI_G3', $1745 = 'WTI_G4', $1746 = 'WTI_G5', $1747 = 'WTI_G6', $1748 = 'WTI_G7', $1749 = 'WTI_G8', $1750 = 'WTI_G9', $1751 = 'WTI_H0', $1752 = 'WTI_H1', $1753 = 'WTI_H2', $1754 = 'WTI_H3', $1755 = 'WTI_H4', $1756 = 'WTI_H5', $1757 = 'WTI_H6', $1758 = 'WTI_H7', $1759 = 'WTI_H8', $1760 = 'WTI_H9', $1761 = 'WTI_J0', $1762 = 'WTI_J1', $1763 = 'WTI_J2', $1764 = 'WTI_J3', $1765 = 'WTI_J4', $1766 = 'WTI_J5', $1767 = 'WTI_J6', $1768 = 'WTI_J7', $1769 = 'WTI_J8', $1770 = 'WTI_J9', $1771 = 'WTI_K0', $1772 = 'WTI_K1', $1773 = 'WTI_K2', $1774 = 'WTI_K3', $1775 = 'WTI_K4', $1776 = 'WTI_K5', $1777 = 'WTI_K6', $1778 = 'WTI_K7', $1779 = 'WTI_K8', $1780 = 'WTI_K9', $1781 = 'WTI_M0', $1782 = 'WTI_M1', $1783 = 'WTI_M2', $1784 = 'WTI_M3', $1785 = 'WTI_M4', $1786 = 'WTI_M5', $1787 = 'WTI_M6', $1788 = 'WTI_M7', $1789 = 'WTI_M8', $1790 = 'WTI_M9', $1791 = 'WTI_N0', $1792 = 'WTI_N1', $1793 = 'WTI_N2', $1794 = 'WTI_N3', $1795 = 'WTI_N4', $1796 = 'WTI_N5', $1797 = 'WTI_N6', $1798 = 'WTI_N7', $1799 = 'WTI_N8', $1800 = 'WTI_N9', $1801 = 'WTI_Q0', $1802 = 'WTI_Q1', $1803 = 'WTI_Q2', $1804 = 'WTI_Q3', $1805 = 'WTI_Q4', $1806 = 'WTI_Q5', $1807 = 'WTI_Q6', $1808 = 'WTI_Q7', $1809 = 'WTI_Q8', $1810 = 'WTI_Q9', $1811 = 'WTI_U0', $1812 = 'WTI_U1', $1813 = 'WTI_U2', $1814 = 'WTI_U3', $1815 = 'WTI_U4', $1816 = 'WTI_U5', $1817 = 'WTI_U6', $1818 = 'WTI_U7', $1819 = 'WTI_U8', $1820 = 'WTI_U9', $1821 = 'WTI_V0', $1822 = 'WTI_V1', $1823 = 'WTI_V2', $1824 = 'WTI_V3', $1825 = 'WTI_V4', $1826 = 'WTI_V5', $1827 = 'WTI_V6', $1828 = 'WTI_V7', $1829 = 'WTI_V8', $1830 = 'WTI_V9', $1831 = 'WTI_X0', $1832 = 'WTI_X1', $1833 = 'WTI_X2', $1834 = 'WTI_X3', $1835 = 'WTI_X4', $1836 = 'WTI_X5', $1837 = 'WTI_X6', $1838 = 'WTI_X7', $1839 = 'WTI_X8', $1840 = 'WTI_X9', $1841 = 'WTI_Z0', $1842 = 'WTI_Z1', $1843 = 'WTI_Z2', $1844 = 'WTI_Z3', $1845 = 'WTI_Z4', $1846 = 'WTI_Z5', $1847 = 'WTI_Z6', $1848 = 'WTI_Z7', $1849 = 'WTI_Z8', $1850 = 'WTI_Z9', $1851 = '5'
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-06-17 13:14:44 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.249 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 348ms 3,558 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 13 3,558 348ms 0ms [ User: postgres - Total duration: 2s431ms - Times executed: 3558 ]
[ Application: [unknown] - Total duration: 2s431ms - Times executed: 3558 ]
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:31:48 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 14:00:00', $2 = '7.84789', $3 = '7.84866', $4 = '7.84786', $5 = '7.84809', $6 = '231', $7 = '515840245893277300', $8 = '0', $9 = '2025-06-17 13:31:48.541', $10 = '2025-06-17 13:31:48.541', $11 = '7.84789', $12 = '7.84866', $13 = '7.84786', $14 = '7.84809', $15 = '231', $16 = '0', $17 = '2025-06-17 13:31:48.541', $18 = '2025-06-17 13:31:48.541'
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:31:19 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 14:00:00', $2 = '32.526', $3 = '32.5295', $4 = '32.502', $5 = '32.5165', $6 = '473', $7 = '605679104109977300', $8 = '0', $9 = '2025-06-17 13:31:19.726', $10 = '2025-06-17 13:31:19.725', $11 = '32.526', $12 = '32.5295', $13 = '32.502', $14 = '32.5165', $15 = '473', $16 = '0', $17 = '2025-06-17 13:31:19.726', $18 = '2025-06-17 13:31:19.725'
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:30:58 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 14:00:00', $2 = '14.63', $3 = '14.642', $4 = '14.628', $5 = '14.635', $6 = '585', $7 = '515840247908557300', $8 = '0', $9 = '2025-06-17 13:30:58.474', $10 = '2025-06-17 13:30:58.174', $11 = '14.63', $12 = '14.642', $13 = '14.628', $14 = '14.635', $15 = '585', $16 = '0', $17 = '2025-06-17 13:30:58.474', $18 = '2025-06-17 13:30:58.174'
13 232ms 2,285 0ms 0ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 13 2,285 232ms 0ms [ User: postgres - Total duration: 1s297ms - Times executed: 2285 ]
[ Application: [unknown] - Total duration: 1s297ms - Times executed: 2285 ]
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:01:57 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 12:00:00', $2 = '21828.3', $3 = '21830.2', $4 = '21785.4', $5 = '21807.2', $6 = '8118', $7 = '515840248039327300', $8 = '0', $9 = '2025-06-17 13:01:57.982', $10 = '2025-06-17 13:01:57.908', $11 = '21828.3', $12 = '21830.2', $13 = '21785.4', $14 = '21807.2', $15 = '8118', $16 = '0', $17 = '2025-06-17 13:01:57.982', $18 = '2025-06-17 13:01:57.908'
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:11:57 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 12:00:00', $2 = '23972.1', $3 = '23981.6', $4 = '23933.3', $5 = '23954.5', $6 = '2250', $7 = '515840247933961300', $8 = '0', $9 = '2025-06-17 13:11:57.293', $10 = '2025-06-17 13:11:57.227', $11 = '23972.1', $12 = '23981.6', $13 = '23933.3', $14 = '23954.5', $15 = '2250', $16 = '0', $17 = '2025-06-17 13:11:57.293', $18 = '2025-06-17 13:11:57.227'
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-06-17 13:02:00 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-06-17 12:00:00', $2 = '6004.15', $3 = '6004.45', $4 = '5993.45', $5 = '5999.65', $6 = '3457', $7 = '515840248032396300', $8 = '0', $9 = '2025-06-17 13:02:00.084', $10 = '2025-06-17 13:02:00.01', $11 = '6004.15', $12 = '6004.45', $13 = '5993.45', $14 = '5999.65', $15 = '3457', $16 = '0', $17 = '2025-06-17 13:02:00.084', $18 = '2025-06-17 13:02:00.01'
14 197ms 201 0ms 1ms 0ms SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 13 201 197ms 0ms [ User: postgres - Total duration: 1s196ms - Times executed: 201 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s128ms - Times executed: 193 ]
[ Application: [unknown] - Total duration: 67ms - Times executed: 8 ]
-
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2025-06-17 13:31:17 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42 parameters: $1 = '621', $2 = 'USDJPY', $3 = '621'
-
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2025-06-17 13:40:46 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 182.165.1.42 parameters: $1 = '689', $2 = 'XAUUSD', $3 = '689'
-
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2025-06-17 13:22:49 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '529', $2 = 'EURUSD', $3 = '529'
15 82ms 18 3ms 7ms 4ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 13 18 82ms 4ms [ User: postgres - Total duration: 2s171ms - Times executed: 18 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s171ms - Times executed: 18 ]
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-06-17 13:54:47 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '489', $2 = '489'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-06-17 13:27:44 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.15 parameters: $1 = '667', $2 = '667'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-06-17 13:57:53 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '489', $2 = '489'
16 39ms 496 0ms 0ms 0ms /*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 13 496 39ms 0ms [ User: postgres - Total duration: 42ms - Times executed: 496 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 42ms - Times executed: 496 ]
-
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2025-06-17 13:05:11 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '606307150579079301'
-
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2025-06-17 13:36:31 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '606304628911653301'
-
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2025-06-17 13:15:00 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '606306795189971301'
17 31ms 1 31ms 31ms 31ms with maxwhid as ( ;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 13 1 31ms 31ms [ User: postgres - Total duration: 34ms - Times executed: 1 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 34ms - Times executed: 1 ]
-
with maxwhid as ( ;
Date: 2025-06-17 13:21:49 Duration: 31ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.226 parameters: $1 = '335', $2 = '621', $3 = '637', $4 = '642', $5 = '666', $6 = '660', $7 = '643', $8 = '630', $9 = '680', $10 = '641', $11 = '431', $12 = '622', $13 = '489', $14 = '529', $15 = '576', $16 = '665', $17 = '667', $18 = '558', $19 = '620', $20 = '125', $21 = '488', $22 = '567', $23 = '689', $24 = '700', $25 = '758', $26 = '763', $27 = '765', $28 = '817', $29 = '914', $30 = '972'
18 30ms 45 0ms 2ms 0ms WITH tr_max AS ( ;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 13 45 30ms 0ms [ User: postgres - Total duration: 140ms - Times executed: 45 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 140ms - Times executed: 45 ]
-
WITH tr_max AS ( ;
Date: 2025-06-17 13:14:17 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.249 parameters: $1 = '515840243244148300', $2 = '515840243244148300', $3 = '515840243244148300', $4 = '2', $5 = '2', $6 = '780', $7 = 't', $8 = '780'
-
WITH tr_max AS ( ;
Date: 2025-06-17 13:13:29 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.249 parameters: $1 = '515840243239577300', $2 = '515840243239577300', $3 = '515840243239577300', $4 = '2', $5 = '2', $6 = '780', $7 = 't', $8 = '780'
-
WITH tr_max AS ( ;
Date: 2025-06-17 13:13:30 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.249 parameters: $1 = '515840243244148300', $2 = '515840243244148300', $3 = '515840243244148300', $4 = '2', $5 = '2', $6 = '780', $7 = 't', $8 = '780'
19 27ms 324 0ms 0ms 0ms /*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 13 324 27ms 0ms [ User: postgres - Total duration: 20ms - Times executed: 324 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 20ms - Times executed: 324 ]
-
/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;
Date: 2025-06-17 13:23:09 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.239 parameters: $1 = '606306968907075303'
-
/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;
Date: 2025-06-17 13:59:13 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '606307261472733303'
-
/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;
Date: 2025-06-17 13:45:36 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '606307088068296303'
20 27ms 700 0ms 0ms 0ms SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 13 700 27ms 0ms [ User: postgres - Total duration: 24ms - Times executed: 700 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 24ms - Times executed: 700 ]
-
SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-06-17 13:07:07 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '515840233390352300'
-
SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-06-17 13:32:32 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '515840218035774300'
-
SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-06-17 13:48:01 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '515840216971142300'
-
Events
Log levels
Key values
- 663,695 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 0 ERROR entries
- 0 WARNING entries
Errors per 5 minutes
NO DATASET
Most Frequent Errors/Events
Key values
- 0 Max number of times the same event was reported
- 0 Total events found
Rank Times reported Error NO DATASET