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Global information
- Generated on Wed Mar 5 12:00:31 2025
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2025-03-05_130000.log, ..., /home/postgres/pg_data/data/pg_log/postgresql-2025-03-05_134530.log
- Parsed 3,218,424 log entries in 1m30s
- Log start from 2025-03-05 13:00:00 to 2025-03-05 14:00:00
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Overview
Global Stats
- 261 Number of unique normalized queries
- 193,808 Number of queries
- 2h3m53s Total query duration
- 2025-03-05 13:00:00 First query
- 2025-03-05 13:59:59 Last query
- 3,942 queries/s at 2025-03-05 13:15:04 Query peak
- 2h3m53s Total query duration
- 8s695ms Prepare/parse total duration
- 1m18s Bind total duration
- 2h2m25s Execute total duration
- 8 Number of events
- 1 Number of unique normalized events
- 8 Max number of times the same event was reported
- 0 Number of cancellation
- 44 Total number of automatic vacuums
- 61 Total number of automatic analyzes
- 664 Number temporary file
- 121.55 MiB Max size of temporary file
- 4.80 MiB Average size of temporary file
- 3,904 Total number of sessions
- 11 sessions at 2025-03-05 13:45:20 Session peak
- 14d5h28m1s Total duration of sessions
- 5m14s Average duration of sessions
- 49 Average queries per session
- 1s903ms Average queries duration per session
- 5m12s Average idle time per session
- 3,894 Total number of connections
- 32 connections/s at 2025-03-05 13:15:03 Connection peak
- 2 Total number of databases
SQL Traffic
Key values
- 3,942 queries/s Query Peak
- 2025-03-05 13:15:04 Date
SELECT Traffic
Key values
- 3,878 queries/s Query Peak
- 2025-03-05 13:15:04 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 183 queries/s Query Peak
- 2025-03-05 13:00:52 Date
Queries duration
Key values
- 2h3m53s 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) Mar 05 13 193,808 0ms 34s668ms 37ms 3m23s 4m5s 5m29s 14 0 0ms 0ms 0ms 0ms 0ms 0ms Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Mar 05 13 154,324 26 1ms 6s710ms 12s432ms 29s129ms 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) Mar 05 13 26,177 2,935 16 96 1ms 659ms 1s47ms 3s628ms 14 0 0 0 0 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Mar 05 13 24,420 172,995 7.08 12.81% 14 1 0 0.00 100.00% Day Hour Count Average / Second Mar 05 13 3,894 1.08/s 14 0 0.00/s Day Hour Count Average Duration Average idle time Mar 05 13 3,904 5m14s 5m12s 14 0 0ms 0ms -
Connections
Established Connections
Key values
- 32 connections Connection Peak
- 2025-03-05 13:15:03 Date
Connections per database
Key values
- acaweb_fx Main Database
- 3,894 connections Total
Connections per user
Key values
- postgres Main User
- 3,894 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 1436 connections
- 3,894 Total connections
Host Count 127.0.0.1 125 192.168.0.114 6 192.168.0.216 101 192.168.1.127 25 192.168.1.145 186 192.168.1.20 230 192.168.1.231 10 192.168.1.239 10 192.168.1.250 791 192.168.1.49 7 192.168.1.8 7 192.168.1.90 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 62 192.168.4.142 1,436 192.168.4.150 10 192.168.4.238 20 192.168.4.248 11 192.168.4.33 66 192.168.4.66 1 192.168.4.98 330 [local] 274 -
Sessions
Simultaneous sessions
Key values
- 11 sessions Session Peak
- 2025-03-05 13:45:20 Date
Histogram of session times
Key values
- 2,972 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 3,904 sessions Total
Sessions per user
Key values
- postgres Main User
- 3,904 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 3,904 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 125 1h12s 28s900ms 192.168.0.114 6 11d3h10m59s 1d20h31m49s 192.168.0.216 101 1m13s 723ms 192.168.1.127 25 2s743ms 109ms 192.168.1.145 186 7h15m21s 2m20s 192.168.1.20 230 15h49m36s 4m7s 192.168.1.231 20 8h25m4s 25m15s 192.168.1.239 10 62ms 6ms 192.168.1.250 791 14h20m34s 1m5s 192.168.1.49 7 3h25m52s 29m24s 192.168.1.8 7 3h25m51s 29m24s 192.168.1.90 52 36s104ms 694ms 192.168.2.126 62 6s366ms 102ms 192.168.2.182 12 721ms 60ms 192.168.2.205 12 401ms 33ms 192.168.2.82 48 11s428ms 238ms 192.168.3.199 62 21s378ms 344ms 192.168.4.142 1,436 15m59s 668ms 192.168.4.150 10 20h5m7s 2h30s 192.168.4.238 20 53s589ms 2s679ms 192.168.4.248 11 7m36s 41s521ms 192.168.4.33 66 4s866ms 73ms 192.168.4.66 1 185ms 185ms 192.168.4.98 330 12s830ms 38ms [local] 274 2m2s 447ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 37,183 buffers Checkpoint Peak
- 2025-03-05 13:37:43 Date
- 209.897 seconds Highest write time
- 0.006 seconds Sync time
Checkpoints Wal files
Key values
- 16 files Wal files usage Peak
- 2025-03-05 13:37:43 Date
Checkpoints distance
Key values
- 510.99 Mo Distance Peak
- 2025-03-05 13:37:43 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Mar 05 13 78,947 1,668.694s 0.052s 1,669.033s 14 0 0s 0s 0s Day Hour Added Removed Recycled Synced files Longest sync Average sync Mar 05 13 0 0 35 1,960 0.005s 0s 14 0 0 0 0 0s 0s Day Hour Count Avg time (sec) Mar 05 13 0 0s 14 0 0s Day Hour Mean distance Mean estimate Mar 05 13 51,883.36 kB 133,978.55 kB 14 0.00 kB 0.00 kB -
Temporary Files
Size of temporary files
Key values
- 142.19 MiB Temp Files size Peak
- 2025-03-05 13:10:06 Date
Number of temporary files
Key values
- 64 per second Temp Files Peak
- 2025-03-05 13:02:08 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Mar 05 13 664 3.11 GiB 4.80 MiB 14 0 0 0 Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 112 500.12 MiB 3.03 MiB 7.84 MiB 4.47 MiB with rar_max as ( ;-
WITH rar_max as ( ;
Date: 2025-03-05 13:45:46 Duration: 0ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown]
2 38 1.51 GiB 3.06 MiB 121.55 MiB 40.75 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), 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: 2025-03-05 13:00:11 Duration: 8s427ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-05 13:30:10 Duration: 7s240ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-05 13:40:07 Duration: 4s865ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
3 16 296.20 MiB 18.51 MiB 18.52 MiB 18.51 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: 2025-03-05 13:01:12 Duration: 1s347ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-03-05 13:50:13 Duration: 1s287ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-03-05 13:31:13 Duration: 1s222ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
4 16 619.33 MiB 38.70 MiB 38.71 MiB 38.71 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: 2025-03-05 13:33:16 Duration: 2s781ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-03-05 13:16:16 Duration: 2s639ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-03-05 13:41:15 Duration: 2s567ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
5 4 220.94 MiB 55.17 MiB 55.30 MiB 55.23 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2025-03-05 13:17:12 Duration: 10s610ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-03-05 13:32:12 Duration: 10s81ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-03-05 13:02:12 Duration: 10s60ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
6 1 4.56 MiB 4.56 MiB 4.56 MiB 4.56 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: 2025-03-05 13:38:17 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 1 121.55 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: 2025-03-05 13:40:05 ]
2 104.80 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: 2025-03-05 13:20:04 ]
3 95.82 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: 2025-03-05 13:30:06 ]
4 83.90 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: 2025-03-05 13:00:08 ]
5 76.11 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: 2025-03-05 13:10:04 ]
6 70.28 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-03-05 13:30:06 ]
7 69.85 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-03-05 13:10:03 ]
8 65.94 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 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: 2025-03-05 13:50:04 ]
9 63.45 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-03-05 13:00:08 ]
10 62.88 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: 2025-03-05 13:40:04 ]
11 60.95 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-03-05 13:00:08 ]
12 59.67 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: 2025-03-05 13:10:03 ]
13 57.23 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-03-05 13:20:05 ]
14 55.30 MiB select updateageforrelevantresults ();[ Date: 2025-03-05 13:02:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
15 55.28 MiB select updateageforrelevantresults ();[ Date: 2025-03-05 13:32:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
16 55.19 MiB select updateageforrelevantresults ();[ Date: 2025-03-05 13:47:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
17 55.17 MiB select updateageforrelevantresults ();[ Date: 2025-03-05 13:17:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
18 52.30 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: 2025-03-05 13:50:05 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
19 51.71 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: 2025-03-05 13:30:06 ]
20 50.88 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: 2025-03-05 13:20:06 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
-
Vacuums
Vacuums / Analyzes Distribution
Key values
- 0 sec Highest CPU-cost vacuum
Table
Database - Date
- 0 sec Highest CPU-cost analyze
Table
Database - Date
Analyzes per table
Key values
- public.solr_relevance_old (16) Main table analyzed (database acaweb_fx)
- 61 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 16 acaweb_fx.pg_catalog.pg_attribute 7 acaweb_fx.public.datafeeds_latestrun 5 acaweb_fx.public.relevance_keylevels_results 4 acaweb_fx.pg_catalog.pg_class 4 acaweb_fx.public.relevance_fibonacci_results 4 acaweb_fx.pg_catalog.pg_type 4 acaweb_fx.public.relevance_autochartist_results 4 acaweb_fx.pg_catalog.pg_index 2 acaweb_fx.public.autochartist_symbolupdates 2 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.public.relevance_bigmovement_results 2 socialmedia.public.processes 1 acaweb_fx.public.patternresultsrelevance 1 acaweb_fx.pg_catalog.pg_depend 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.relevance_consecutivecandles_results 1 Total 61 Vacuums per table
Key values
- public.solr_relevance_old (19) Main table vacuumed on database acaweb_fx
- 44 vacuums Total
Index Buffer usage Skipped WAL usage Table Vacuums scans hits misses dirtied pins frozen records full page bytes acaweb_fx.public.solr_relevance_old 19 17 15,788 0 57 0 71 10,176 16 1,874,870 acaweb_fx.public.datafeeds_latestrun 5 0 583 0 35 0 0 88 49 90,383 acaweb_fx.pg_toast.pg_toast_2619 2 2 336 0 70 0 0 224 61 248,044 acaweb_fx.pg_catalog.pg_attribute 2 2 1,685 0 324 0 128 788 286 1,708,797 acaweb_fx.public.relevance_keylevels_results 2 2 8,111 0 321 2 192 1,876 303 804,040 acaweb_fx.public.relevance_fibonacci_results 2 2 2,593 0 65 2 110 443 48 117,364 acaweb_fx.pg_catalog.pg_type 2 2 285 0 40 0 0 116 27 172,932 acaweb_fx.public.relevance_autochartist_results 2 2 7,228 0 218 3 462 1,575 201 489,577 acaweb_fx.public.autochartist_symbolupdates 1 1 27,178 0 895 5 36,822 7,981 529 795,280 acaweb_fx.pg_catalog.pg_depend 1 1 343 0 97 0 58 198 75 444,281 acaweb_fx.public.latest_t15_candle_view 1 1 64 0 1 0 0 6 1 9,037 acaweb_fx.pg_catalog.pg_class 1 1 377 0 28 0 41 123 25 143,782 acaweb_fx.pg_catalog.pg_statistic 1 1 874 0 197 0 672 503 175 722,147 acaweb_fx.public.relevance_consecutivecandles_results 1 1 78 0 4 0 0 24 2 15,373 acaweb_fx.public.relevance_bigmovement_results 1 1 226 0 15 0 0 80 15 55,692 acaweb_fx.public.t15 1 1 540,732 0 39,899 0 139,768 67,855 37,965 182,237,048 Total 44 37 606,481 535,300 42,266 12 178,324 92,056 39,778 189,928,647 Tuples removed per table
Key values
- public.solr_relevance_old (71485) Main table with removed tuples on database acaweb_fx
- 110786 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 19 17 71,485 139,652 16,942 0 4,155 acaweb_fx.public.t15 1 1 24,846 2,605,369 44 0 172,175 acaweb_fx.public.autochartist_symbolupdates 1 1 5,288 50,894 59 0 40,691 acaweb_fx.pg_catalog.pg_attribute 2 2 3,036 18,884 0 0 484 acaweb_fx.public.relevance_keylevels_results 2 2 1,641 22,005 0 0 558 acaweb_fx.public.relevance_autochartist_results 2 2 1,513 17,394 0 0 760 acaweb_fx.pg_catalog.pg_depend 1 1 692 11,977 0 0 114 acaweb_fx.pg_catalog.pg_statistic 1 1 677 4,493 0 0 1,194 acaweb_fx.public.relevance_fibonacci_results 2 2 428 2,643 0 0 204 acaweb_fx.pg_catalog.pg_type 2 2 310 2,668 0 0 76 acaweb_fx.public.datafeeds_latestrun 5 0 287 76 1 0 80 acaweb_fx.pg_toast.pg_toast_2619 2 2 154 341 1 0 102 acaweb_fx.pg_catalog.pg_class 1 1 139 1,945 0 0 150 acaweb_fx.public.relevance_consecutivecandles_results 1 1 120 291 0 0 8 acaweb_fx.public.relevance_bigmovement_results 1 1 110 1,385 0 0 33 acaweb_fx.public.latest_t15_candle_view 1 1 60 14 0 0 1 Total 44 37 110,786 2,880,031 17,047 0 220,785 Pages removed per table
Key values
- unknown (0) Main table with removed pages on database unknown
- 0 pages Total removed
Pages removed per tables
NO DATASET
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_toast.pg_toast_2619 2 2 154 0 acaweb_fx.public.autochartist_symbolupdates 1 1 5288 0 acaweb_fx.public.datafeeds_latestrun 5 0 287 0 acaweb_fx.pg_catalog.pg_attribute 2 2 3036 0 acaweb_fx.pg_catalog.pg_depend 1 1 692 0 acaweb_fx.public.latest_t15_candle_view 1 1 60 0 acaweb_fx.public.relevance_keylevels_results 2 2 1641 0 acaweb_fx.pg_catalog.pg_class 1 1 139 0 acaweb_fx.public.relevance_fibonacci_results 2 2 428 0 acaweb_fx.pg_catalog.pg_type 2 2 310 0 acaweb_fx.pg_catalog.pg_statistic 1 1 677 0 acaweb_fx.public.relevance_consecutivecandles_results 1 1 120 0 acaweb_fx.public.relevance_bigmovement_results 1 1 110 0 acaweb_fx.public.t15 1 1 24846 0 acaweb_fx.public.solr_relevance_old 19 17 71485 0 acaweb_fx.public.relevance_autochartist_results 2 2 1513 0 Total 44 37 110,786 0 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Mar 05 13 44 61 14 0 0 - 0 sec Highest CPU-cost vacuum
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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
- 154,324 Total read queries
- 36,328 Total write queries
Queries by database
Key values
- acaweb_fx Main database
- 192,294 Requests
- 2h2m23s (acaweb_fx)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 192,294 2h2m23s copy from 96 6s647ms copy to 26 11s206ms cte 6,390 1h56m55s ddl 16 488ms delete 16 24ms insert 26,117 23s512ms others 3,106 8s744ms select 152,948 4m21s tcl 660 190ms update 2,919 16s688ms socialmedia Total 1,514 1s950ms insert 60 90ms others 50 2ms select 1,376 1s831ms tcl 12 0ms update 16 26ms Queries by user
Key values
- postgres Main user
- 193,808 Requests
User Request type Count Duration postgres Total 193,808 2h2m25s copy from 96 6s647ms copy to 26 11s206ms cte 6,390 1h56m55s ddl 16 488ms delete 16 24ms insert 26,177 23s603ms others 3,156 8s746ms select 154,324 4m22s tcl 672 190ms update 2,935 16s714ms Duration by user
Key values
- 2h2m25s (postgres) Main time consuming user
User Request type Count Duration postgres Total 193,808 2h2m25s copy from 96 6s647ms copy to 26 11s206ms cte 6,390 1h56m55s ddl 16 488ms delete 16 24ms insert 26,177 23s603ms others 3,156 8s746ms select 154,324 4m22s tcl 672 190ms update 2,935 16s714ms Queries by host
Key values
- 192.168.1.145 Main host
- 53,528 Requests
- 43m47s (192.168.1.250)
- Main time consuming host
Host Request type Count Duration 127.0.0.1 Total 16,157 37s882ms copy to 26 11s206ms cte 25 291ms insert 12,816 11s686ms others 36 0ms select 880 13s283ms update 2,374 1s412ms 182.165.1.42 Total 158 7m16s cte 60 7m16s select 98 106ms 192.168.0.114 Total 24 36ms select 12 35ms tcl 12 0ms 192.168.0.216 Total 404 372ms others 202 20ms select 194 216ms update 8 134ms 192.168.0.236 Total 62 17ms cte 6 1ms select 56 15ms 192.168.0.239 Total 609 398ms select 609 398ms 192.168.0.42 Total 2,717 1s207ms insert 927 74ms select 1,790 1s132ms 192.168.1.127 Total 1,318 1s704ms insert 2 7ms others 50 2ms select 1,262 1s689ms update 4 5ms 192.168.1.135 Total 164 368ms cte 8 187ms select 156 181ms 192.168.1.145 Total 53,528 33m20s cte 1,033 32m4s others 372 4ms select 52,123 1m15s 192.168.1.20 Total 51,470 33m32s cte 1,049 32m22s others 460 5ms select 49,961 1m10s 192.168.1.201 Total 2,243 2s256ms select 2,243 2s256ms 192.168.1.23 Total 2,601 2s86ms select 2,601 2s86ms 192.168.1.231 Total 24 2ms others 20 0ms select 4 1ms 192.168.1.239 Total 40 25ms others 20 1ms select 20 23ms 192.168.1.250 Total 42,631 43m47s cte 3,550 43m23s others 1,582 16ms select 37,499 24s361ms 192.168.1.49 Total 66 32ms cte 6 12ms others 7 0ms select 53 20ms 192.168.1.8 Total 72 39ms cte 6 13ms others 7 0ms select 59 26ms 192.168.1.90 Total 60 34s102ms cte 6 34s57ms others 8 0ms select 46 44ms 192.168.1.97 Total 56 12ms cte 6 2ms select 50 10ms 192.168.2.126 Total 80 68ms others 18 0ms select 62 68ms 192.168.2.182 Total 48 240ms others 24 2ms select 12 10ms update 12 227ms 192.168.2.205 Total 138 98ms insert 90 7ms others 24 2ms select 20 19ms update 4 69ms 192.168.2.82 Total 1,080 1s826ms insert 674 1s46ms others 96 9ms select 185 104ms update 125 665ms 192.168.3.199 Total 248 262ms others 124 11ms select 112 112ms update 12 138ms 192.168.4.142 Total 13,154 12s439ms insert 11,610 10s696ms select 1,544 1s742ms 192.168.4.150 Total 22 954ms others 21 0ms select 1 953ms 192.168.4.238 Total 48 26s718ms cte 8 26s717ms others 40 0ms 192.168.4.248 Total 3,077 13s991ms cte 530 13s280ms others 33 0ms select 2,514 710ms 192.168.4.33 Total 172 209ms insert 58 83ms select 102 105ms update 12 20ms 192.168.4.66 Total 3 35ms cte 1 35ms others 2 0ms 192.168.4.98 Total 996 9s257ms others 6 8s403ms select 6 31ms tcl 660 190ms update 324 631ms [local] Total 338 2m1s copy from 96 6s647ms cte 96 33s415ms ddl 16 488ms delete 16 24ms others 4 263ms select 50 1m7s update 60 13s408ms Queries by application
Key values
- PostgreSQL JDBC Driver Main application
- 157,926 Requests
- 1h51m28s (PostgreSQL JDBC Driver)
- Main time consuming application
Application Request type Count Duration PostgreSQL JDBC Driver Total 157,926 1h51m28s cte 6,179 1h48m30s insert 927 74ms others 1,283 15ms select 149,537 2m57s [unknown] Total 35,431 8m43s cte 90 7m50s insert 25,250 23s528ms others 1,869 8s467ms select 4,685 17s450ms tcl 672 190ms update 2,865 3s276ms psql Total 451 2m13s copy from 96 6s647ms copy to 26 11s206ms cte 121 33s707ms ddl 16 488ms delete 16 24ms others 4 263ms select 102 1m7s update 70 13s438ms Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2025-03-05 13:09:49 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 119,143 0-1ms duration
Slowest individual queries
Rank Duration Query 1 34s668ms 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: 2025-03-05 13:47:05 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
2 32s758ms 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: 2025-03-05 13:41:39 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
3 32s256ms 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: 2025-03-05 13:52:32 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
4 31s942ms 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: 2025-03-05 13:30:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
5 30s784ms 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: 2025-03-05 13:57:51 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
6 30s459ms 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: 2025-03-05 13:24:58 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
7 30s212ms 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: 2025-03-05 13:12:20 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
8 30s210ms 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: 2025-03-05 13:17:28 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
9 29s891ms 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: 2025-03-05 13:06:39 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
10 29s843ms 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: 2025-03-05 13:35:46 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
11 25s502ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-03-05 13:16:34 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
12 21s811ms 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: 2025-03-05 13:05:52 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
13 20s969ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-03-05 13:46:35 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
14 20s672ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-03-05 13:31:18 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
15 20s610ms 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 = '529' 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 ('183' = 0 OR coalesce(bim.code, s.symbol) in ('AUDUSD', 'EURUSD', 'GBPUSD', 'USDCAD', 'USDCHF', 'USDJPY', 'XAGAUD', 'XAGEUR', 'XAGUSD', 'XAUAUD', 'XAUCHF', 'XAUEUR', 'XAUGBP', 'XAUJPY', 'XAUUSD', 'XPDUSD', 'XPTUSD', 'AUS200', 'CA60', 'CHINAH', 'CN50', 'EUSTX50', 'FRA40', 'GER40', 'GERTEC30', 'HK50', 'JPN225', 'MidDE50', 'NAS100', 'NETH25', 'NOR25', 'SA40', 'SCI25', 'SPA35', 'SWI20', 'UK100', 'US2000', 'US30', 'US500', 'VIX', 'AUDCAD', 'AUDCHF', 'AUDNZD', 'AUDSGD', 'EURAUD', 'EURCHF', 'EURGBP', 'GBPAUD', 'GBPCHF', 'NZDUSD', 'CHFSGD', 'EURCZK', 'EURHUF', 'EURMXN', 'EURNOK', 'EURPLN', 'EURSEK', 'EURSGD', 'EURTRY', 'EURZAR', 'GBPMXN', 'GBPNOK', 'GBPSEK', 'GBPSGD', 'GBPTRY', 'NOKJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'SEKJPY', 'SGDJPY', 'USDCNH', 'USDCZK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTHB', 'USDTRY', 'USDZAR', 'ZARJPY', 'ADAUSD', 'AVAXUSD', 'BCHUSD', 'BNBUSD', 'BTCUSD', 'Crypto10', 'Crypto20', 'Crypto30', 'DOGEUSD', 'DOTUSD', 'EOSUSD', 'ETHUSD', 'LINKUSD', 'LTCUSD', 'MATICUSD', 'SOLUSD', 'UNIUSD', 'XLMUSD', 'XRPUSD', 'XTZUSD', 'EURX', 'JPYX', 'USDX', 'Gasoline', 'NatGas', 'SpotBrent', 'SpotCrude', 'AAPL.US', 'ABNB.US', 'AMD.US', 'AMZN.US', 'AXP.US', 'BA.US', 'BABA.US', 'BIDU.US', 'BYND.US', 'C.US', 'COIN.US', 'CRM.US', 'DIS.US', 'EA.US', 'GOOG.US', 'GS.US', 'IBM.US', 'JPM.US', 'LMT.US', 'MA.US', 'MCD.US', 'META.US', 'MRNA.US', 'MSFT.US', 'NFLX.US', 'NKE.US', 'NVDA.US', 'ORCL.US', 'PFE.US', 'PG.US', 'PLTR.US', 'PTON.US', 'PYPL.US', 'QCOM.US', 'SNAP.US', 'SPCE.US', 'SPY.US', 'T.US', 'TMUS.US', 'TSLA.US', 'UBER.US', 'V.US', 'WMT.US', 'ZM.US', 'Cattle', 'Cocoa', 'Coffee', 'Corn', 'Cotton', 'LDSugar', 'LeanHogs', 'LondonSugar', 'Lumber', 'OJ', 'Oats', 'RghRice', 'SoyMeal', 'SoyOil', 'Soybeans', 'Sugar', 'Wheat', 'AUDJPY', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURCAD', 'EURJPY', 'EURNZD', 'GBPCAD', 'GBPJPY', 'GBPNZD', 'NZDJPY')) AND ('0' = 0 OR 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: 2025-03-05 13:31:40 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
16 20s28ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-03-05 13:00:18 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
17 19s360ms 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: 2025-03-05 13:00:49 - Database: acaweb_fx - User: postgres - Remote: 182.165.1.42 - Application: [unknown] - Bind query: yes ]
18 18s473ms 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: 2025-03-05 13:46:22 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
19 17s493ms 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: 2025-03-05 13:16:53 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
20 17s321ms 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 = '529' 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 ('31' = 0 OR coalesce(bim.code, s.symbol) in ('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURNZD', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'JPN225', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', 'XAGUSD', 'XAUUSD')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2025-03-05 13:05:47 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
Time consuming queries
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 53m18s 380 390ms 25s502ms 8s416ms 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 Mar 05 13 380 53m18s 8s416ms [ User: postgres - Total duration: 53m18s - Times executed: 380 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 49m51s - Times executed: 368 ]
[ Application: [unknown] - Total duration: 3m26s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:16:34 Duration: 25s502ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:05:52 Duration: 21s811ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:46:35 Duration: 20s969ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
2 43m41s 381 169ms 34s668ms 6s881ms 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 Mar 05 13 381 43m41s 6s881ms [ User: postgres - Total duration: 43m41s - Times executed: 381 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 41m11s - Times executed: 369 ]
[ Application: [unknown] - Total duration: 2m30s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-03-05 13:47:05 Duration: 34s668ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-03-05 13:41:39 Duration: 32s758ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-03-05 13:52:32 Duration: 32s256ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
3 14m12s 372 406ms 8s298ms 2s291ms 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 Mar 05 13 372 14m12s 2s291ms [ User: postgres - Total duration: 14m12s - Times executed: 372 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 13m13s - Times executed: 360 ]
[ Application: [unknown] - Total duration: 58s538ms - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('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: 2025-03-05 13:46:30 Duration: 8s298ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:40:55 Duration: 7s628ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:31:26 Duration: 7s341ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
4 2m24s 235 0ms 2s423ms 613ms 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 Mar 05 13 235 2m24s 613ms [ User: postgres - Total duration: 2m24s - Times executed: 235 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m5s - Times executed: 223 ]
[ Application: [unknown] - Total duration: 18s608ms - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:16:08 Duration: 2s423ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:05:43 Duration: 2s353ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:41:11 Duration: 2s187ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
5 1m37s 32,402 0ms 51ms 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 Mar 05 13 32,402 1m37s 3ms [ User: postgres - Total duration: 1m37s - Times executed: 32402 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m37s - Times executed: 32402 ]
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'SpotBrent' OR dss.downloadersymbol = 'SpotBrent') AND dss.enabled = 1;
Date: 2025-03-05 13:30:06 Duration: 51ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'GBPJPY' OR dss.downloadersymbol = 'GBPJPY') AND dss.enabled = 1;
Date: 2025-03-05 13:15:05 Duration: 45ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'BA.US' OR dss.downloadersymbol = 'BA.US') AND dss.enabled = 1;
Date: 2025-03-05 13:45:04 Duration: 38ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
6 1m 195 135ms 1s472ms 312ms with last_candle as ( select acs.symbolid as symbolid, acs.latestpricedatetime as latest_candle_time, bsl.brokerid as broker_id, coalesce(bim.code, s.symbol) as symbol, bim.code as symbol_mapping, s.exchange as exchange, s.timegranularity as timegranularity from autochartist_symbolupdates acs inner join brokersymbollist bsl on acs.symbolid = bsl.symbolid inner join symbols s on acs.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bsl.brokerid = ? and s.deleted = ? and s.nonliquid = ? and acs.latestpricedatetime is not null ) select * from ( select lc.broker_id as brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / ?) + ? as sast_hh, mod(cast(psp.fromtime as int), ?) as sast_mm, current_timestamp as datetime, (powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice as closingprice, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / ?.?) as low_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / ?.?) as high_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / ?.?) as low_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / ?.?) as high_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / ?.?) as low_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / ?.?) as high_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / ?.?) as low_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / ?.?) as high_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / ?.?) as low_1440, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / ?.?) as high_1440, dtt.absolutetimezoneoffset as datafeedtimezoneoffset, dtt.timezone as datafeedtimezonename, (round((cast(? as float) - rank) / ? * ?)) as rank_rounded, ((cast(? as float) - rank) / ? * ?) as rank from last_candle lc inner join downloadersymbolsettings dss on lc.symbolid = dss.symbolid inner join datafeedstimetable dtt on trim(dss.classname) = trim(dtt.classname) and dtt.dayofweek = ? -- assuming timezone is same for whole week. inner join powerstats_symboldata psd on psd.symbolid = lc.symbolid left outer join powerstats_trumpet psp on psd.trumpetsymbolid = psp.symbolid and psp.dayofweek = extract(dow from lc.latest_candle_time) and psp.fromtime = cast(extract(? from lc.latest_candle_time) as integer) * ? + extract(? from (cast(extract(? from lc.latest_candle_time) as integer) / ?) * ? * interval ?) inner join prfsymboltree prf on psd.symbolid = prf.symbolid and date_trunc(?, prf.enddate) = date_trunc(?, psp.enddate) left join lateral ( select ph.hour, (ave + stddev) as volatility, rank() over (order by (ave + stddev) desc) as rank from powerstats_hourly ph where ph.symbolid = psd.hourlysymbolid and date_trunc(?,ph.enddate) = date_trunc(?, prf.enddate) ) rank_query on true where prf.brokerid = ? and rank_query.hour = floor((psp.fromtime) / ?) and volatility > ? order by rank desc, rank_rounded desc, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Mar 05 13 195 1m 312ms [ User: postgres - Total duration: 1m - Times executed: 195 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m - Times executed: 195 ]
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '621' 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 = '621' 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: 2025-03-05 13:00:05 Duration: 1s472ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '558' 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 = '558' 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: 2025-03-05 13:00:06 Duration: 864ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-03-05 13:52:18 Duration: 826ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
7 49s672ms 34,412 0ms 33ms 1ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Mar 05 13 34,412 49s672ms 1ms [ User: postgres - Total duration: 49s672ms - Times executed: 34412 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 49s672ms - Times executed: 34412 ]
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243265160300';
Date: 2025-03-05 13:30:05 Duration: 33ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243225790300';
Date: 2025-03-05 13:00:04 Duration: 32ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, 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 = '515840249459042300';
Date: 2025-03-05 13:00:06 Duration: 29ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
8 38s169ms 4 7s416ms 10s610ms 9s542ms select updateageforrelevantresults ();Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Mar 05 13 4 38s169ms 9s542ms [ User: postgres - Total duration: 38s169ms - Times executed: 4 ]
[ Application: psql - Total duration: 38s169ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-03-05 13:17:12 Duration: 10s610ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-03-05 13:32:12 Duration: 10s81ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2025-03-05 13:02:12 Duration: 10s60ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
9 34s57ms 6 4s353ms 8s427ms 5s676ms 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 Mar 05 13 6 34s57ms 5s676ms [ User: postgres - Total duration: 34s57ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 34s57ms - Times executed: 6 ]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-05 13:00:11 Duration: 8s427ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-05 13:30:10 Duration: 7s240ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-05 13:40:07 Duration: 4s865ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
10 30s862ms 16 1s530ms 2s781ms 1s928ms 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 Mar 05 13 16 30s862ms 1s928ms [ User: postgres - Total duration: 30s862ms - Times executed: 16 ]
[ Application: psql - Total duration: 30s862ms - Times executed: 16 ]
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-03-05 13:33:16 Duration: 2s781ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-03-05 13:16:16 Duration: 2s639ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-03-05 13:41:15 Duration: 2s567ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 26s717ms 8 3s199ms 3s548ms 3s339ms 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 = ? ) 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 Mar 05 13 8 26s717ms 3s339ms [ User: postgres - Total duration: 26s717ms - Times executed: 8 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 26s717ms - Times executed: 8 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '617' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '617' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '617') 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: 2025-03-05 13:21:56 Duration: 3s548ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '620' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '620' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '620') 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: 2025-03-05 13:06:46 Duration: 3s402ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '620' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '620' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '620') 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: 2025-03-05 13:36:50 Duration: 3s392ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
12 24s977ms 235 0ms 440ms 106ms with rar_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ), all_results as ( select bmr.resultuid as resultuid, ? 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, bmr.patternendtime as identified, bmr.patternlengthbars, dtt.timezone as timezone, g.basegroupname, case when rbr.age is not null then rbr.age when bmr.resultuid <= rm.resultuid then ? else ? end as age, case when rbr.relevant is not null then rbr.relevant when bmr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from bigmovement_results bmr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = bmr.symbolid inner join symbols s on bmr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on bmr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on bmr.symbolid = sg.symbolid inner 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_bigmovement_results rbr on rbr.resultuid = bmr.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 = ? where bmr.gmttimefound > now() - interval ? and s.deleted = ? and (bmr.simulation = ? or bmr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or bmr.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, interval desc;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Mar 05 13 235 24s977ms 106ms [ User: postgres - Total duration: 24s977ms - Times executed: 235 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 21s734ms - Times executed: 223 ]
[ Application: [unknown] - Total duration: 3s243ms - Times executed: 12 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 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, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER 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_bigmovement_results rbr ON rbr.resultuid = bmr.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' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.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 bmr.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, interval DESC;
Date: 2025-03-05 13:01:15 Duration: 440ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 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, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER 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_bigmovement_results rbr ON rbr.resultuid = bmr.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' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.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 bmr.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, interval DESC;
Date: 2025-03-05 13:16:09 Duration: 381ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 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, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER 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_bigmovement_results rbr ON rbr.resultuid = bmr.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' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.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 bmr.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, interval DESC;
Date: 2025-03-05 13:41:12 Duration: 381ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
13 21s443ms 34 12ms 6s483ms 630ms select fixcandlegaps (?, false);Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Mar 05 13 34 21s443ms 630ms [ User: postgres - Total duration: 21s443ms - Times executed: 34 ]
[ Application: psql - Total duration: 21s443ms - Times executed: 34 ]
-
select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-03-05 13:06:23 Duration: 6s483ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select fixcandlegaps ('ATFX', false);
Date: 2025-03-05 13:06:07 Duration: 2s956ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select fixcandlegaps ('AXIORY', false);
Date: 2025-03-05 13:06:09 Duration: 2s218ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
14 14s797ms 12,721 0ms 5ms 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 #14
Day Hour Count Duration Avg duration Mar 05 13 12,721 14s797ms 1ms [ User: postgres - Total duration: 14s797ms - Times executed: 12721 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14s797ms - Times executed: 12721 ]
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243257534300';
Date: 2025-03-05 13:31:28 Duration: 5ms 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 = '515840233380062300';
Date: 2025-03-05 13:52:04 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '958' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '958' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243161146300';
Date: 2025-03-05 13:46:01 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
15 12s981ms 16 580ms 1s347ms 811ms 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 #15
Day Hour Count Duration Avg duration Mar 05 13 16 12s981ms 811ms [ User: postgres - Total duration: 12s981ms - Times executed: 16 ]
[ Application: psql - Total duration: 12s981ms - 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: 2025-03-05 13:01:12 Duration: 1s347ms 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: 2025-03-05 13:50:13 Duration: 1s287ms 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: 2025-03-05 13:31:13 Duration: 1s222ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
16 8s403ms 6 1s3ms 1s714ms 1s400ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 05 13 6 8s403ms 1s400ms [ User: postgres - Total duration: 8s403ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 8s403ms - Times executed: 6 ]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-03-05 13:31:18 Duration: 1s714ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-03-05 13:16:18 Duration: 1s693ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-03-05 13:01:18 Duration: 1s660ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
17 7s435ms 5,904 0ms 34ms 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 Mar 05 13 5,904 7s435ms 1ms [ User: postgres - Total duration: 7s435ms - Times executed: 5904 ]
[ Application: [unknown] - Total duration: 7s435ms - Times executed: 5904 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-05 12:45:00', '0.94829', '0.94878', '0.9481', '0.94856', '1821', '515840245870618300', '0', '2025-03-05 13:00:05.629', '2025-03-05 13:00:05.407') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.94829', high = '0.94878', low = '0.9481', close = '0.94856', volume = '1821', bsf = '0', sastdatetimewritten = '2025-03-05 13:00:05.629', sastdatetimereceived = '2025-03-05 13:00:05.407';
Date: 2025-03-05 13:00:05 Duration: 34ms 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 ('2025-03-05 12:45:00', '93.8635', '93.9185', '93.8085', '93.8415', '1818', '515840230426691300', '0', '2025-03-05 13:00:04.893', '2025-03-05 13:00:04.818') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '93.8635', high = '93.9185', low = '93.8085', close = '93.8415', volume = '1818', bsf = '0', sastdatetimewritten = '2025-03-05 13:00:04.893', sastdatetimereceived = '2025-03-05 13:00:04.818';
Date: 2025-03-05 13:00:04 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 ('2025-03-05 13:30:00', '0.88899', '0.88909', '0.8887', '0.88888', '741', '515840243869386300', '0', '2025-03-05 13:45:04.482', '2025-03-05 13:45:04.437') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.88899', high = '0.88909', low = '0.8887', close = '0.88888', volume = '741', bsf = '0', sastdatetimewritten = '2025-03-05 13:45:04.482', sastdatetimereceived = '2025-03-05 13:45:04.437';
Date: 2025-03-05 13:45:04 Duration: 25ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
18 7s405ms 8,006 0ms 20ms 0ms insert into autochartist_results (resultid, symbolid, bandwidth, pattern, qtytp, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, relevancestartdistance, simulation, writtendatetime) values (?, ?, ?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Mar 05 13 8,006 7s405ms 0ms [ User: postgres - Total duration: 7s405ms - Times executed: 8006 ]
[ Application: [unknown] - Total duration: 7s405ms - Times executed: 8006 ]
-
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 ('500991628217975200-1|45720.6562|45721.4583|45720.5729|45720.7292|19.5964|19.7211|19.5097|19.5272', 500991628217975200, 6.000000000000000000000000000000, 'Channel Up', 4, '2025-03-05 10:57:18'::timestamp without time zone, - 1, 0.520935587575008907100000000000, - 1.000000000000000000000000000000, 0.625666837772581363400000000000, 0.600964391517040841200000000000, 0.302235437659273520400000000000, 19.630578318075361470000000000000, 19.655289299198067000000000000000, '2025-03-05 12:45:00'::timestamp without time zone, '2025-03-06 00:15:00'::timestamp without time zone, '2025-03-04 09:00:00'::timestamp without time zone, '2025-03-05 12:45:00'::timestamp without time zone, 19.553419999999999140000000000000, 19.644320000000000450000000000000, '2025-03-04 15:45:00'::timestamp without time zone, '2025-03-05 11:00:00'::timestamp without time zone, '2025-03-04 13:45:00'::timestamp without time zone, '2025-03-04 17:30:00'::timestamp without time zone, 19.596370000000000290000000000000, 19.721119999999999100000000000000, 19.509720000000001500000000000000, 19.527219999999999800000000000000, 0.001166666666666552922000000000, 0.001620129870129854554000000000, 1.687485203228533903000000000000, 0.407402211239080547200000000000, 'Continuation', 0.000000000000000000000000000000, '2025-03-05 12:45:00'::timestamp without time zone, 19.672940000000000540000000000000, 92, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-05 13:00:57 Duration: 20ms 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 ('515840231327754300-1|45719.9792|45721.4792|45720.7083|45721.3958|0.9405|0.95|0.9345|0.945', 515840231327754300, 2.000000000000000000000000000000, 'Rising Wedge', 5, '2025-03-05 10:57:28'::timestamp without time zone, - 1, 0.046608383878661598100000000000, - 1.000000000000000000000000000000, 0.791964602540154327600000000000, 0.079199208015453700920000000000, 0.859582599689130755200000000000, 0.944215219738674393900000000000, 0.946773008224447654200000000000, '2025-03-05 12:30:00'::timestamp without time zone, '2025-03-06 07:00:00'::timestamp without time zone, '2025-03-03 22:30:00'::timestamp without time zone, '2025-03-05 12:30:00'::timestamp without time zone, 0.938400000000000011900000000000, 0.947640000000000037900000000000, '2025-03-03 23:30:00'::timestamp without time zone, '2025-03-05 11:30:00'::timestamp without time zone, '2025-03-04 17:00:00'::timestamp without time zone, '2025-03-05 09:30:00'::timestamp without time zone, 0.940509999999999957200000000000, 0.949999999999999955600000000000, 0.934509999999999951800000000000, 0.945010000000000016700000000000, 0.000318181818181820154800000000, 0.000131805555555555527800000000, 2.557526825025136396000000000000, 0.608997258517446238300000000000, 'Reversal', 0.000000000000000000000000000000, '2025-03-05 12:30:00'::timestamp without time zone, 0.948599999999999998800000000000, 74, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-05 13:01:07 Duration: 11ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('515840249557361300-1|45719.4375|45720.1667|45719.6562|45720.6562|98.79|100.65|96.55|100.42', 515840249557361300, 2.000000000000000000000000000000, 'Channel Up', 4, '2025-03-05 11:27:45'::timestamp without time zone, 1, 0.019607574598391463990000000000, - 1.000000000000000000000000000000, 1.000000000000000000000000000000, 0.653023704494049339600000000000, 0.586273012651454594800000000000, 102.355733236228829240000000000000, 102.853759766949195860000000000000, '2025-03-05 05:15:00'::timestamp without time zone, '2025-03-06 02:37:30'::timestamp without time zone, '2025-03-03 08:00:00'::timestamp without time zone, '2025-03-05 05:15:00'::timestamp without time zone, 98.209999999999993750000000000000, 102.000000000000000000000000000000, '2025-03-03 10:30:00'::timestamp without time zone, '2025-03-04 04:00:00'::timestamp without time zone, '2025-03-03 15:45:00'::timestamp without time zone, '2025-03-04 15:45:00'::timestamp without time zone, 98.790000000000006250000000000000, 100.650000000000005680000000000000, 96.549999999999997160000000000000, 100.420000000000001710000000000000, 0.094390243902439135980000000000, 0.084545454545454520880000000000, 1.465456896847789236000000000000, 0.317618960918598924900000000000, 'Continuation', 0.000000000000000000000000000000, '2025-03-05 05:15:00'::timestamp without time zone, 102.000000000000000000000000000000, 64, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-05 13:31:23 Duration: 10ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
19 7s363ms 197 13ms 175ms 37ms 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 #19
Day Hour Count Duration Avg duration Mar 05 13 197 7s363ms 37ms [ User: postgres - Total duration: 7s363ms - Times executed: 197 ]
[ Application: [unknown] - Total duration: 7s363ms - Times executed: 197 ]
-
SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-03-05 13:16:00 Duration: 175ms 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 'ICMARKETS - 1';
Date: 2025-03-05 13:01:04 Duration: 152ms 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 'ICMARKETS - 1';
Date: 2025-03-05 13:31:14 Duration: 150ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
20 7s47ms 13 39ms 5s643ms 542ms copy ( select array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ?) as broker_ids, string_to_array(coalesce(replace(broker_symbol_mappings, ?, ?), ?), ?) as broker_symbol_mappings, replace(exchange, ?, ?) as exchange, symbol_id, replace(symbol, ?, ?) as symbol, replace(short_name, ?, ?) as short_name, replace(long_name, ?, ?) as long_name, interval, replace(timezone, ?, ?) as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ?) as search_groups, string_to_array(pattern_basegroupnames, ?) as base_groups, simulation from solr_fetch_results_bm_and_cc (?::character varying, current_timestamp::timestamp without time zone)) t) to ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Mar 05 13 13 7s47ms 542ms [ User: postgres - Total duration: 7s47ms - Times executed: 13 ]
[ Application: psql - Total duration: 7s47ms - Times executed: 13 ]
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-03-05 13:03:08 Duration: 5s643ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-03-05 13:01:02 Duration: 334ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-03-05 13:18:02 Duration: 207ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 60,566 303ms 0ms 12ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 05 13 60,566 303ms 0ms [ User: postgres - Total duration: 303ms - Times executed: 60566 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 290ms - Times executed: 60207 ]
[ Application: [unknown] - Total duration: 12ms - Times executed: 359 ]
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select 1;
Date: 2025-03-05 13:30:06 Duration: 12ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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select 1;
Date: 2025-03-05 13:00:04 Duration: 12ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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select 1;
Date: 2025-03-05 13:00:06 Duration: 12ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
2 34,412 49s672ms 0ms 33ms 1ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, 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 Mar 05 13 34,412 49s672ms 1ms [ User: postgres - Total duration: 49s672ms - Times executed: 34412 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 49s672ms - Times executed: 34412 ]
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243265160300';
Date: 2025-03-05 13:30:05 Duration: 33ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243225790300';
Date: 2025-03-05 13:00:04 Duration: 32ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, 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 = '515840249459042300';
Date: 2025-03-05 13:00:06 Duration: 29ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
3 32,402 1m37s 0ms 51ms 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 Mar 05 13 32,402 1m37s 3ms [ User: postgres - Total duration: 1m37s - Times executed: 32402 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m37s - Times executed: 32402 ]
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'SpotBrent' OR dss.downloadersymbol = 'SpotBrent') AND dss.enabled = 1;
Date: 2025-03-05 13:30:06 Duration: 51ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'GBPJPY' OR dss.downloadersymbol = 'GBPJPY') AND dss.enabled = 1;
Date: 2025-03-05 13:15:05 Duration: 45ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'BA.US' OR dss.downloadersymbol = 'BA.US') AND dss.enabled = 1;
Date: 2025-03-05 13:45:04 Duration: 38ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
4 12,721 14s797ms 0ms 5ms 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 #4
Day Hour Count Duration Avg duration Mar 05 13 12,721 14s797ms 1ms [ User: postgres - Total duration: 14s797ms - Times executed: 12721 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14s797ms - Times executed: 12721 ]
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243257534300';
Date: 2025-03-05 13:31:28 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840233380062300';
Date: 2025-03-05 13:52:04 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '958' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '958' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243161146300';
Date: 2025-03-05 13:46:01 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
5 8,006 7s405ms 0ms 20ms 0ms insert into autochartist_results (resultid, symbolid, bandwidth, pattern, qtytp, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, relevancestartdistance, simulation, writtendatetime) values (?, ?, ?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Mar 05 13 8,006 7s405ms 0ms [ User: postgres - Total duration: 7s405ms - Times executed: 8006 ]
[ Application: [unknown] - Total duration: 7s405ms - Times executed: 8006 ]
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INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('500991628217975200-1|45720.6562|45721.4583|45720.5729|45720.7292|19.5964|19.7211|19.5097|19.5272', 500991628217975200, 6.000000000000000000000000000000, 'Channel Up', 4, '2025-03-05 10:57:18'::timestamp without time zone, - 1, 0.520935587575008907100000000000, - 1.000000000000000000000000000000, 0.625666837772581363400000000000, 0.600964391517040841200000000000, 0.302235437659273520400000000000, 19.630578318075361470000000000000, 19.655289299198067000000000000000, '2025-03-05 12:45:00'::timestamp without time zone, '2025-03-06 00:15:00'::timestamp without time zone, '2025-03-04 09:00:00'::timestamp without time zone, '2025-03-05 12:45:00'::timestamp without time zone, 19.553419999999999140000000000000, 19.644320000000000450000000000000, '2025-03-04 15:45:00'::timestamp without time zone, '2025-03-05 11:00:00'::timestamp without time zone, '2025-03-04 13:45:00'::timestamp without time zone, '2025-03-04 17:30:00'::timestamp without time zone, 19.596370000000000290000000000000, 19.721119999999999100000000000000, 19.509720000000001500000000000000, 19.527219999999999800000000000000, 0.001166666666666552922000000000, 0.001620129870129854554000000000, 1.687485203228533903000000000000, 0.407402211239080547200000000000, 'Continuation', 0.000000000000000000000000000000, '2025-03-05 12:45:00'::timestamp without time zone, 19.672940000000000540000000000000, 92, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-05 13:00:57 Duration: 20ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('515840231327754300-1|45719.9792|45721.4792|45720.7083|45721.3958|0.9405|0.95|0.9345|0.945', 515840231327754300, 2.000000000000000000000000000000, 'Rising Wedge', 5, '2025-03-05 10:57:28'::timestamp without time zone, - 1, 0.046608383878661598100000000000, - 1.000000000000000000000000000000, 0.791964602540154327600000000000, 0.079199208015453700920000000000, 0.859582599689130755200000000000, 0.944215219738674393900000000000, 0.946773008224447654200000000000, '2025-03-05 12:30:00'::timestamp without time zone, '2025-03-06 07:00:00'::timestamp without time zone, '2025-03-03 22:30:00'::timestamp without time zone, '2025-03-05 12:30:00'::timestamp without time zone, 0.938400000000000011900000000000, 0.947640000000000037900000000000, '2025-03-03 23:30:00'::timestamp without time zone, '2025-03-05 11:30:00'::timestamp without time zone, '2025-03-04 17:00:00'::timestamp without time zone, '2025-03-05 09:30:00'::timestamp without time zone, 0.940509999999999957200000000000, 0.949999999999999955600000000000, 0.934509999999999951800000000000, 0.945010000000000016700000000000, 0.000318181818181820154800000000, 0.000131805555555555527800000000, 2.557526825025136396000000000000, 0.608997258517446238300000000000, 'Reversal', 0.000000000000000000000000000000, '2025-03-05 12:30:00'::timestamp without time zone, 0.948599999999999998800000000000, 74, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-05 13:01:07 Duration: 11ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('515840249557361300-1|45719.4375|45720.1667|45719.6562|45720.6562|98.79|100.65|96.55|100.42', 515840249557361300, 2.000000000000000000000000000000, 'Channel Up', 4, '2025-03-05 11:27:45'::timestamp without time zone, 1, 0.019607574598391463990000000000, - 1.000000000000000000000000000000, 1.000000000000000000000000000000, 0.653023704494049339600000000000, 0.586273012651454594800000000000, 102.355733236228829240000000000000, 102.853759766949195860000000000000, '2025-03-05 05:15:00'::timestamp without time zone, '2025-03-06 02:37:30'::timestamp without time zone, '2025-03-03 08:00:00'::timestamp without time zone, '2025-03-05 05:15:00'::timestamp without time zone, 98.209999999999993750000000000000, 102.000000000000000000000000000000, '2025-03-03 10:30:00'::timestamp without time zone, '2025-03-04 04:00:00'::timestamp without time zone, '2025-03-03 15:45:00'::timestamp without time zone, '2025-03-04 15:45:00'::timestamp without time zone, 98.790000000000006250000000000000, 100.650000000000005680000000000000, 96.549999999999997160000000000000, 100.420000000000001710000000000000, 0.094390243902439135980000000000, 0.084545454545454520880000000000, 1.465456896847789236000000000000, 0.317618960918598924900000000000, 'Continuation', 0.000000000000000000000000000000, '2025-03-05 05:15:00'::timestamp without time zone, 102.000000000000000000000000000000, 64, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-05 13:31:23 Duration: 10ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
6 5,904 7s435ms 0ms 34ms 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 Mar 05 13 5,904 7s435ms 1ms [ User: postgres - Total duration: 7s435ms - Times executed: 5904 ]
[ Application: [unknown] - Total duration: 7s435ms - Times executed: 5904 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-05 12:45:00', '0.94829', '0.94878', '0.9481', '0.94856', '1821', '515840245870618300', '0', '2025-03-05 13:00:05.629', '2025-03-05 13:00:05.407') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.94829', high = '0.94878', low = '0.9481', close = '0.94856', volume = '1821', bsf = '0', sastdatetimewritten = '2025-03-05 13:00:05.629', sastdatetimereceived = '2025-03-05 13:00:05.407';
Date: 2025-03-05 13:00:05 Duration: 34ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-05 12:45:00', '93.8635', '93.9185', '93.8085', '93.8415', '1818', '515840230426691300', '0', '2025-03-05 13:00:04.893', '2025-03-05 13:00:04.818') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '93.8635', high = '93.9185', low = '93.8085', close = '93.8415', volume = '1818', bsf = '0', sastdatetimewritten = '2025-03-05 13:00:04.893', sastdatetimereceived = '2025-03-05 13:00:04.818';
Date: 2025-03-05 13:00:04 Duration: 27ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-05 13:30:00', '0.88899', '0.88909', '0.8887', '0.88888', '741', '515840243869386300', '0', '2025-03-05 13:45:04.482', '2025-03-05 13:45:04.437') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.88899', high = '0.88909', low = '0.8887', close = '0.88888', volume = '741', bsf = '0', sastdatetimewritten = '2025-03-05 13:45:04.482', sastdatetimereceived = '2025-03-05 13:45:04.437';
Date: 2025-03-05 13:45:04 Duration: 25ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
7 3,418 2s88ms 0ms 7ms 0ms insert into t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Mar 05 13 3,418 2s88ms 0ms [ User: postgres - Total duration: 2s88ms - Times executed: 3418 ]
[ Application: [unknown] - Total duration: 2s88ms - Times executed: 3418 ]
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-05 13:00:00', '3.88543', '3.89173', '3.88433', '3.88973', '2243', '515840247873808300', '0', '2025-03-05 13:31:00.266', '2025-03-05 13:31:00.219') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '3.88543', high = '3.89173', low = '3.88433', close = '3.88973', volume = '2243', bsf = '0', sastdatetimewritten = '2025-03-05 13:31:00.266', sastdatetimereceived = '2025-03-05 13:31:00.219';
Date: 2025-03-05 13:31:00 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-05 13:00:00', '2912.77', '2915.15', '2912.74', '2913.6', '3161', '515840247906722300', '0', '2025-03-05 13:31:02.605', '2025-03-05 13:31:02.457') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '2912.77', high = '2915.15', low = '2912.74', close = '2913.6', volume = '3161', bsf = '0', sastdatetimewritten = '2025-03-05 13:31:02.605', sastdatetimereceived = '2025-03-05 13:31:02.457';
Date: 2025-03-05 13:31:02 Duration: 7ms 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 ('2025-03-05 12:30:00', '2729.43', '2729.6', '2719.95', '2723.13', '6496', '515840247937025300', '0', '2025-03-05 13:01:02.748', '2025-03-05 13:01:02.606') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '2729.43', high = '2729.6', low = '2719.95', close = '2723.13', volume = '6496', bsf = '0', sastdatetimewritten = '2025-03-05 13:01:02.748', sastdatetimereceived = '2025-03-05 13:01:02.606';
Date: 2025-03-05 13:01:02 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
8 2,636 1s332ms 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 #8
Day Hour Count Duration Avg duration Mar 05 13 2,636 1s332ms 0ms [ User: postgres - Total duration: 1s332ms - Times executed: 2636 ]
[ Application: [unknown] - Total duration: 1s332ms - Times executed: 2636 ]
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INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, 'Butterfly', '2025-03-05 10:58:25'::timestamp without time zone, - 1, '2025-03-05 09:15:00'::timestamp without time zone, '2025-03-05 12:45:00'::timestamp without time zone, 93.995999999999995110000000000000, - 1.000000000000000000000000000000, 5, 93.995999999999995110000000000000, '2025-03-05 09:15:00'::timestamp without time zone, 93.602000000000003870000000000000, '2025-03-05 10:00:00'::timestamp without time zone, 93.957999999999998410000000000000, '2025-03-05 12:00:00'::timestamp without time zone, 93.742999999999995000000000000000, '2025-03-05 12:15:00'::timestamp without time zone, 94.103175741902987280000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.743480603448281485200000000000, - 1.000000000000000000000000000000, 9.239598986876623954000000000000, 13, 93.742999999999995000000000000000, 93.880574891501694880000000000000, 93.520399149598702590000000000000, 93.820023086155813980000000000000, 93.645025120929133780000000000000, 93.923087870951491140000000000000, 93.965600850401287400000000000000, 515840243158623300, 0.513038793103437029700000000000, 'BC=0.618*AB (0.604) ', 0, 'Butterfly|-1|2025-03-05 09:15:00|93.996|-1|5|13|BC=0.618*AB (0.604)|0|515840243158623300|2025-03-05 09:15:00|2025-03-05 10:00:00|2025-03-05 12:00:00|2025-03-05 12:15:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-05 13:02:04 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, 'ABCD', '2025-03-05 10:57:32'::timestamp without time zone, - 1, '2025-03-04 21:30:00'::timestamp without time zone, '2025-03-05 12:30:00'::timestamp without time zone, 7.458070000000000199000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 7.455949999999999634000000000000, '2025-03-05 00:00:00'::timestamp without time zone, 7.457550000000000346000000000000, '2025-03-05 10:30:00'::timestamp without time zone, 7.456319999999999837000000000000, '2025-03-05 12:00:00'::timestamp without time zone, 7.457920000000000549000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.645833089777684055100000000000, - 1.000000000000000000000000000000, 0.799703404597661982000000000000, 45, 7.456319999999999837000000000000, 7.456931145618080236000000000000, 7.455331145618079524000000000000, 7.456662157795520330000000000000, 7.455884768560800069000000000000, 7.457119999999999749000000000000, 7.457308854381920149000000000000, 515840243948250300, 0.508037225042293760800000000000, 'BC=0.786*AB (0.769) ', 0, 'ABCD|-1|2025-03-04 21:30:00|7.45807|-1|4|45|BC=0.786*AB (0.769)|0|515840243948250300|1899-12-29 00:00:00|2025-03-05 00:00:00|2025-03-05 10:30:00|2025-03-05 12:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-05 13:01:11 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 (2.000000000000000000000000000000, 'ABCD', '2025-03-05 11:27:52'::timestamp without time zone, 1, '2025-03-05 05:30:00'::timestamp without time zone, '2025-03-05 13:15:00'::timestamp without time zone, 0.814019999999999965800000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.817629999999999967900000000000, '2025-03-05 11:30:00'::timestamp without time zone, 0.816490000000000049000000000000, '2025-03-05 12:30:00'::timestamp without time zone, 0.817389999999999950000000000000, '2025-03-05 13:00:00'::timestamp without time zone, 0.816250000000000031100000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.678442028985537959400000000000, - 1.000000000000000000000000000000, 11.966191687715237890000000000000, 10, 0.817389999999999950000000000000, 0.816954558747117976000000000000, 0.818094558747117894800000000000, 0.817146212570691976600000000000, 0.817700102400429895700000000000, 0.816819999999999990500000000000, 0.816685441252882005100000000000, 515840233473836300, 0.643115942028923970300000000000, 'BC=0.786*AB (0.789) ', 0, 'ABCD|1|2025-03-05 05:30:00|0.81402|-1|4|10|BC=0.786*AB (0.789)|0|515840233473836300|1899-12-29 00:00:00|2025-03-05 11:30:00|2025-03-05 12:30:00|2025-03-05 13:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-05 13:31:30 Duration: 6ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
9 2,364 1s382ms 0ms 4ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Mar 05 13 2,364 1s382ms 0ms [ User: postgres - Total duration: 1s382ms - Times executed: 2364 ]
[ Application: [unknown] - Total duration: 1s382ms - Times executed: 2364 ]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-03-05 13:00:00', reason = 'Emerging pattern formed a completed pattern.' WHERE uniqueIndex = '515840247868761300-1|45721.0417|45721.375|45721.2083|45721.3958|0.5588|0.5582|0.5554|0.556' and relevant = 1;
Date: 2025-03-05 13:31:37 Duration: 4ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-03-05 13:00:00', reason = 'Emerging pattern broke out in the wrong direction.' WHERE uniqueIndex = '515840243233089300-1|45719.375|45721.3125|45719|45720.6042|34.315|33.759|34.158|33.689' and relevant = 1;
Date: 2025-03-05 13:31:39 Duration: 3ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2025-03-05 12:30:00', reason = 'Price has entered the prediction area for a completed pattern' WHERE uniqueIndex = '5158402494137153000.62|45720.9167|45721.3958|45720.7083|45721.3542|71.66|71.516|70.12|71.126' and relevant = 1;
Date: 2025-03-05 13:00:47 Duration: 3ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
10 2,247 2s99ms 0ms 23ms 0ms with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ) select a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, s.exchange, s.symbol, s.longname, s.shortname, breakout, dtt.timezone, patternstartprice, patternendprice, qtytp, newlevels.profit, newlevels.stop, newlevels.filtered, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern inner join rar_max rm on ? = ? left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid left join lateral calc_cp_signal (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 05 13 2,247 2s99ms 0ms [ User: postgres - Total duration: 2s99ms - Times executed: 2247 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s79ms - Times executed: 2234 ]
[ Application: [unknown] - Total duration: 19ms - Times executed: 13 ]
-
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 = '605718324581072301' 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 = '605718324581072301' OR a.resultuid = '605718324581072301') AND dtt.dayofweek = 3;
Date: 2025-03-05 13:30:04 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_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 = '605718270143755301' 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 = '605718270143755301' OR a.resultuid = '605718270143755301') AND dtt.dayofweek = 3;
Date: 2025-03-05 13:16:28 Duration: 16ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_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 = '605718150783003301' 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 = '605718150783003301' OR a.resultuid = '605718150783003301') AND dtt.dayofweek = 3;
Date: 2025-03-05 13:00:33 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
11 2,184 1s98ms 0ms 7ms 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Mar 05 13 2,184 1s98ms 0ms [ User: postgres - Total duration: 1s98ms - Times executed: 2184 ]
[ Application: [unknown] - Total duration: 1s98ms - Times executed: 2184 ]
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-05 12:00:00', '18.3837', '18.40609', '18.37099', '18.38999', '8197', '515840247968908300', '0', '2025-03-05 13:01:02.979', '2025-03-05 13:01:02.685') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '18.3837', high = '18.40609', low = '18.37099', close = '18.38999', volume = '8197', bsf = '0', sastdatetimewritten = '2025-03-05 13:01:02.979', sastdatetimereceived = '2025-03-05 13:01:02.685';
Date: 2025-03-05 13:01:02 Duration: 7ms 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 ('2025-03-05 13:00:00', '88634.725', '90802.05', '88535.975', '90089.275', '10862', '515840249392121300', '0', '2025-03-05 13:00:08.599', '2025-03-05 13:00:08.598') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '88634.725', high = '90802.05', low = '88535.975', close = '90089.275', volume = '10862', bsf = '0', sastdatetimewritten = '2025-03-05 13:00:08.599', sastdatetimereceived = '2025-03-05 13:00:08.598';
Date: 2025-03-05 13:00:08 Duration: 7ms 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 ('2025-03-05 12:00:00', '1.28341', '1.28404', '1.28165', '1.28307', '5140', '515840247885064300', '0', '2025-03-05 13:00:52.531', '2025-03-05 13:00:52.392') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '1.28341', high = '1.28404', low = '1.28165', close = '1.28307', volume = '5140', bsf = '0', sastdatetimewritten = '2025-03-05 13:00:52.531', sastdatetimereceived = '2025-03-05 13:00:52.392';
Date: 2025-03-05 13:00:52 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
12 1,959 2s496ms 0ms 8ms 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 #12
Day Hour Count Duration Avg duration Mar 05 13 1,959 2s496ms 1ms [ User: postgres - Total duration: 2s496ms - Times executed: 1959 ]
[ Application: [unknown] - Total duration: 2s496ms - Times executed: 1959 ]
-
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, 2, '2025-03-05 11:27:07'::timestamp without time zone, '', 0.500000000000000000000000000000, 4, 233, 1.129129999999999967000000000000, '2025-03-04 17:00:00', '2025-02-26 06:30:00', '2025-02-26 00:00:00', '2025-02-25 20:30:00', '', '', '', '', '', '', 582, 1.128452499999999858000000000000, '2025-03-05 13:00:00'::timestamp without time zone, '2025-03-05 13:00:00', 0.000000000000000000000000000000, 0.000695999999999996643000000000, 1, 515840245879097300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840245879097300|1.12913|2|2025-03-05 13:00:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-02-25 20:30:00', 1.129129999999999967000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-05 13:30:45 Duration: 8ms 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, '2025-03-05 11:27:58'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 47, 1.509370000000000100000000000000, '2025-03-05 12:00:00', '2025-03-04 20:30:00', '2025-03-04 12:30:00', '', '', '', '', '', '', '', 94, 1.509829000000000088000000000000, '2025-03-05 13:00:00'::timestamp without time zone, '2025-03-05 13:00:00', 0.000000000000000000000000000000, 0.000460000000000004892800000000, - 1, 515840216986682300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840216986682300|1.50937|1|2025-03-05 13:00:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-03-04 12:30:00', 1.511200000000000099000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-05 13:31:37 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (7.000000000000000000000000000000, - 1, 1, '2025-03-05 10:57:12'::timestamp without time zone, '', 0.500000000000000000000000000000, 4, 109, 104.378500000000002500000000000000, '2025-03-05 03:00:00', '2025-02-28 10:00:00', '2025-02-26 20:00:00', '2025-02-26 13:00:00', '', '', '', '', '', '', 272, 104.511674999999996770000000000000, '2025-03-05 12:00:00'::timestamp without time zone, '2025-03-05 12:00:00', 0.000000000000000000000000000000, 0.133174999999999960100000000000, - 1, 515840230444033300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840230444033300|104.3785|1|2025-03-05 12:00:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-02-26 13:00:00', 104.974000000000003750000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-05 13:00:50 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
13 1,499 800ms 0ms 13ms 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 #13
Day Hour Count Duration Avg duration Mar 05 13 1,499 800ms 0ms [ User: postgres - Total duration: 800ms - Times executed: 1499 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 800ms - Times executed: 1499 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '605713317698657303' 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 = '605713317698657303' OR a.resultuid = '605713317698657303') AND dtt.dayofweek = 3;
Date: 2025-03-05 13:30:06 Duration: 13ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '605718035934327303' 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 = '605718035934327303' OR a.resultuid = '605718035934327303') AND dtt.dayofweek = 3;
Date: 2025-03-05 13:46:29 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '605718144931052303' 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 = '605718144931052303' OR a.resultuid = '605718144931052303') AND dtt.dayofweek = 3;
Date: 2025-03-05 13:53:53 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
14 1,311 12ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Mar 05 13 1,311 12ms 0ms [ User: postgres - Total duration: 12ms - Times executed: 1311 ]
[ Application: [unknown] - Total duration: 12ms - Times executed: 1311 ]
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SET extra_float_digits = 3;
Date: 2025-03-05 13:38:51 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: [unknown] Bind query: yes
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SET extra_float_digits = 3;
Date: 2025-03-05 13:45:06 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: [unknown] Bind query: yes
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SET extra_float_digits = 3;
Date: 2025-03-05 13:15:03 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: [unknown] Bind query: yes
15 1,271 15ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Mar 05 13 1,271 15ms 0ms [ User: postgres - Total duration: 15ms - Times executed: 1271 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 15ms - Times executed: 1271 ]
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-03-05 13:14:04 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-03-05 13:39:00 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-03-05 13:56:35 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
16 1,078 1s589ms 1ms 4ms 1ms select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 05 13 1,078 1s589ms 1ms [ User: postgres - Total duration: 1s589ms - Times executed: 1078 ]
[ Application: [unknown] - Total duration: 1s589ms - Times executed: 1078 ]
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select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;
Date: 2025-03-05 13:56:05 Duration: 4ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
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select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;
Date: 2025-03-05 13:09:18 Duration: 4ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
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select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;
Date: 2025-03-05 13:56:12 Duration: 4ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
17 1,058 381ms 0ms 4ms 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars as length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternstartprice, resy1, supporty1, dtt.timezone, cps.pip, newlevels.profit from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern left join currencypips cps on cps.symbol = s.symbol left join lateral calc_cp_signal (a.resultuid) newlevels on true where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Mar 05 13 1,058 381ms 0ms [ User: postgres - Total duration: 381ms - Times executed: 1058 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 381ms - Times executed: 1058 ]
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SELECT CASE WHEN a.old_resultuid = '605718268108934301' 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 = '605718268108934301' OR a.resultuid = '605718268108934301') AND dtt.dayofweek = 3;
Date: 2025-03-05 13:30:04 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '605718324483628301' 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 = '605718324483628301' OR a.resultuid = '605718324483628301') AND dtt.dayofweek = 3;
Date: 2025-03-05 13:17:35 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '605716141624450301' 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 = '605716141624450301' OR a.resultuid = '605716141624450301') AND dtt.dayofweek = 3;
Date: 2025-03-05 13:01:35 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
18 927 74ms 0ms 1ms 0ms insert into authenticationlog (username, password, brokerid, authclass, attemptdatetime, success, fingerprint, accounttype) values (?, ?, ?, ?, current_timestamp, ?, ?, ?);Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Mar 05 13 927 74ms 0ms [ User: postgres - Total duration: 74ms - Times executed: 927 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 74ms - Times executed: 927 ]
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INSERT INTO authenticationlog (username, password, brokerid, authclass, attemptdatetime, success, fingerprint, accounttype) VALUES ('55534228', '','538','HotForexRealm', CURRENT_TIMESTAMP,1,'', '0');
Date: 2025-03-05 13:58:46 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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INSERT INTO authenticationlog (username, password, brokerid, authclass, attemptdatetime, success, fingerprint, accounttype) VALUES ('1293049', '','538','HotForexRealm', CURRENT_TIMESTAMP,1,'', '0');
Date: 2025-03-05 13:03:50 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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INSERT INTO authenticationlog (username, password, brokerid, authclass, attemptdatetime, success, fingerprint, accounttype) VALUES ('51470407', '','538','HotForexRealm', CURRENT_TIMESTAMP,1,'', '0');
Date: 2025-03-05 13:32:52 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
19 866 9ms 0ms 0ms 0ms select null as table_cat, n.nspname as table_schem, c.relname as table_name, case n.nspname ~ ? or n.nspname = ? when true then case when n.nspname = ? or n.nspname = ? then case c.relkind when ? then ? when ? then ? when ? then ? else null end when n.nspname = ? then case c.relkind when ? then ? when ? then ? else null end else case c.relkind when ? then ? when ? then ? when ? then ? when ? then ? when ? then ? else null end end when false then case c.relkind when ? then ? when ? then ? when ? then ? when ? then ? when ? then ? when ? then ? when ? then ? when ? then ? else null end else null end as table_type, d.description as remarks, ? as type_cat, ? as type_schem, ? as type_name, ? as self_referencing_col_name, ? as ref_generation from pg_catalog.pg_namespace n, pg_catalog.pg_class c left join pg_catalog.pg_description d on (c.oid = d.objoid and d.objsubid = ?) left join pg_catalog.pg_class dc on (d.classoid = dc.oid and dc.relname = ?) left join pg_catalog.pg_namespace dn on (dn.oid = dc.relnamespace and dn.nspname = ?) where c.relnamespace = n.oid and c.relname like ? and (false or (c.relkind = ? and n.nspname !~ ? and n.nspname <> ?)) order by table_type, table_schem, table_name;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Mar 05 13 866 9ms 0ms [ User: postgres - Total duration: 9ms - Times executed: 866 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 9ms - Times executed: 866 ]
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-03-05 13:16:11 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.248 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-03-05 13:16:17 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.248 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-03-05 13:15:41 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.248 Application: PostgreSQL JDBC Driver Bind query: yes
20 778 25ms 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 Mar 05 13 778 25ms 0ms [ User: postgres - Total duration: 25ms - Times executed: 778 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 25ms - Times executed: 778 ]
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '515840248125572300' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-03-05 13:33:02 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '515840243268101300' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-03-05 13:45:22 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '515840243153585300' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-03-05 13:04:54 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 7s416ms 10s610ms 9s542ms 4 38s169ms select updateageforrelevantresults ();Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 05 13 4 38s169ms 9s542ms [ User: postgres - Total duration: 38s169ms - Times executed: 4 ]
[ Application: psql - Total duration: 38s169ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2025-03-05 13:17:12 Duration: 10s610ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-03-05 13:32:12 Duration: 10s81ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateageforrelevantresults ();
Date: 2025-03-05 13:02:12 Duration: 10s60ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
2 390ms 25s502ms 8s416ms 380 53m18s 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 Mar 05 13 380 53m18s 8s416ms [ User: postgres - Total duration: 53m18s - Times executed: 380 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 49m51s - Times executed: 368 ]
[ Application: [unknown] - Total duration: 3m26s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:16:34 Duration: 25s502ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:05:52 Duration: 21s811ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('400' = 0 OR ar.patternlengthbars <= '400') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:46:35 Duration: 20s969ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
3 169ms 34s668ms 6s881ms 381 43m41s 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 Mar 05 13 381 43m41s 6s881ms [ User: postgres - Total duration: 43m41s - Times executed: 381 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 41m11s - Times executed: 369 ]
[ Application: [unknown] - Total duration: 2m30s - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-03-05 13:47:05 Duration: 34s668ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-03-05 13:41:39 Duration: 32s758ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), kr AS ( SELECT a.*, rr.age, rr.relevant from keylevels_results a LEFT OUTER JOIN relevance_keylevels_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_keylevels_results) END ), all_results AS ( SELECT kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, p.patternname AS pattern_name, kr.breakout AS breakout, kr.atbaridentified AS identified, dtt.timezone AS timezone, kr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN kr.age IS NOT NULL THEN kr.age WHEN kr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN hrspatterns p ON kr.patternid = p.patternid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ('0' = 0 OR s.timegranularity in ('0')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('0' = 0 OR kr.patternclassid in ('0')) AND ('0' = 0 OR kr.patternlengthbars <= '0') AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2025-03-05 13:52:32 Duration: 32s256ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
4 4s353ms 8s427ms 5s676ms 6 34s57ms 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 Mar 05 13 6 34s57ms 5s676ms [ User: postgres - Total duration: 34s57ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 34s57ms - Times executed: 6 ]
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-05 13:00:11 Duration: 8s427ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-05 13:30:10 Duration: 7s240ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-05 13:40:07 Duration: 4s865ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
5 3s199ms 3s548ms 3s339ms 8 26s717ms 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 = ? ) 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 #5
Day Hour Count Duration Avg duration Mar 05 13 8 26s717ms 3s339ms [ User: postgres - Total duration: 26s717ms - Times executed: 8 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 26s717ms - Times executed: 8 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '617' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '617'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '617' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '617') 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: 2025-03-05 13:21:56 Duration: 3s548ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '620' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '620' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '620') 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: 2025-03-05 13:06:46 Duration: 3s402ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '620' and basegroupname = 'Forex' and g.designation = '(All Intraday)' and s.nonliquid = 0 ), signals as ( select * from ( select cp.og_symbol, cp.resultuid as cpresultuid, kl.resultuid as klresultuid, cp.symbolid as cpsymbolid, kl.symbolid as klsymbolid, cp.symbol, cp.timegranularity as cpt, kl.timegranularity as klt, cp.direction, cp.patternname as cppatternname, kl.patternname as klpatternname, case when cp.timegranularity < kl.timegranularity then cp.timegranularity else kl.timegranularity end as mint, case when cp.timegranularity < kl.timegranularity then cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / cp.timegranularity) as numeric) else cast(abs(extract(epoch from age(cp.predictiontimefrom, kl.predictiontimefrom)) / kl.timegranularity) as numeric) end as qtycandlesapart, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.openprice else cp.openprice end as openprice, case when cp.predictiontimefrom < kl.predictiontimefrom then kl.predictiontimefrom else cp.predictiontimefrom end as predictiontimefrom, case when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom < kl.predictionpricefrom then cp.predictionpricefrom when kl.patternclassid = 1 AND cp.direction > 0 and cp.predictionpricefrom > kl.predictionpricefrom then kl.predictionpricefrom when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto < kl.predictionpriceto then kl.predictionpriceto when kl.patternclassid = 1 AND cp.direction < 0 and cp.predictionpriceto > kl.predictionpriceto then cp.predictionpriceto when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom < kl.patternprice then cp.predictionpricefrom when kl.patternclassid = 2 AND cp.direction > 0 and cp.predictionpricefrom > kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto < kl.patternprice then kl.patternprice when kl.patternclassid = 2 AND cp.direction < 0 and cp.predictionpriceto > kl.patternprice then cp.predictionpriceto end as forecastprice, case when cp.gmttimefound < kl.gmttimefound then kl.gmttimefound else cp.gmttimefound end as gmttimefound, cp.patternendtime as cppet, kl.patternendtime as klpet, case when cp.patternendtime < kl.patternendtime then kl.patternendtime else cp.patternendtime end as max_patternendtime, cp.absolutetimezoneoffset from ( select si.og_symbol, si.symbolid, si.symbol, si.timegranularity, a.resultuid, direction, (patternendtime + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, a.pattern as patternname, predictionpriceto, a.latestbaratbreakoutprice as openprice, gmttimefound, si.brokerid, a.patternendtime, si.absolutetimezoneoffset from sym_info si inner join autochartist_results a on si.symbolid = a.symbolid where breakout >= 0 and patternquality >= 0.3 and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as cp join ( select patternclassid, patternprice, si.symbolid, si.symbol, si.timegranularity, h.resultuid, direction, (cast(atbaridentified as timestamp) + si.timegranularity * interval '1 minute') as predictiontimefrom, predictionpricefrom, case when direction > 0 then 'Resistance' else 'Support' end as patternname, predictionpriceto, atpriceidentified as openprice, gmttimefound, h.patternendtime from sym_info si inner join keylevels_results h on si.symbolid = h.symbolid where patternclassid in (1, 2) and patternendtime >= current_timestamp - interval '7 days' and patternlengthbars < 501) as kl on cp.symbol = kl.symbol and cp.direction = kl.direction) as _tmp inner join currencypips pips on _tmp.og_symbol = pips.symbol where abs(forecastprice - openprice) / pip >= 20 and _tmp.qtycandlesapart <= 5 and ((cpresultuid > ( SELECT COALESCE(MAX(cpresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620')) OR (klresultuid > ( SELECT COALESCE(MAX(klresultuid), 0) FROM correlating_signals acs where acs.basegroupname = 'Forex' and acs.brokerid = '620'))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = '620' and cs.basegroupname = 'Forex' and date_trunc('day', cs.gmttimefound) = date_trunc('day', now()) and sent is true and filtered is false) <= ( select case when coalesce(daily_max, 5) < 1 then 1000 else coalesce(daily_max, 5) end from corr_sigs_config_v where broker_id = '620') 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: 2025-03-05 13:36:50 Duration: 3s392ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
6 406ms 8s298ms 2s291ms 372 14m12s with rar_max as ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ? ), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end ), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp))) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Mar 05 13 372 14m12s 2s291ms [ User: postgres - Total duration: 14m12s - Times executed: 372 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 13m13s - Times executed: 360 ]
[ Application: [unknown] - Total duration: 58s538ms - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('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: 2025-03-05 13:46:30 Duration: 8s298ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:40:55 Duration: 7s628ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1 ), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END ), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('213' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#CAT', '#CBKG', '#DAIGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#TSLA', '#VOWG', '#WMT', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS_200', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CL_BRENT', 'DASHUSD', 'EOSUSD', 'ESP_35', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'USOIL', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XMRUSD', 'XPTUSD', 'XRPUSD', 'ZARJPY', 'ZECUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDDKK', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDZAR', 'ZARJPY', 'BTCEUR', 'BTCGBP', 'BTCUSD', 'DASHUSD', 'EOSUSD', 'ETHEUR', 'ETHGBP', 'ETHUSD', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NEOUSD', 'OMGUSD', 'TRXUSD', 'XMRUSD', 'XRPUSD', 'ZECUSD', 'XAGUSD', 'XAUEUR', 'XAUUSD', 'XPTUSD', 'CL_BRENT', 'USOIL', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('0' = 0 OR fr.pattern in ('')) AND ('400' = 0 OR fr.patternlengthbars <= '400') AND ('0' = 0 OR ('0' = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ('0' = 2 AND fr.timed < cast('1970-01-01' as timestamp))) ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:31:26 Duration: 7s341ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
7 1s530ms 2s781ms 1s928ms 16 30s862ms with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Mar 05 13 16 30s862ms 1s928ms [ User: postgres - Total duration: 30s862ms - Times executed: 16 ]
[ Application: psql - Total duration: 30s862ms - Times executed: 16 ]
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-03-05 13:33:16 Duration: 2s781ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-03-05 13:16:16 Duration: 2s639ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-03-05 13:41:15 Duration: 2s567ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
8 1s3ms 1s714ms 1s400ms 6 8s403ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Mar 05 13 6 8s403ms 1s400ms [ User: postgres - Total duration: 8s403ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 8s403ms - Times executed: 6 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-03-05 13:31:18 Duration: 1s714ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-03-05 13:16:18 Duration: 1s693ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2025-03-05 13:01:18 Duration: 1s660ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
9 580ms 1s347ms 811ms 16 12s981ms 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 #9
Day Hour Count Duration Avg duration Mar 05 13 16 12s981ms 811ms [ User: postgres - Total duration: 12s981ms - Times executed: 16 ]
[ Application: psql - Total duration: 12s981ms - Times executed: 16 ]
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-03-05 13:01:12 Duration: 1s347ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-03-05 13:50:13 Duration: 1s287ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-03-05 13:31:13 Duration: 1s222ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
10 12ms 6s483ms 630ms 34 21s443ms select fixcandlegaps (?, false);Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 05 13 34 21s443ms 630ms [ User: postgres - Total duration: 21s443ms - Times executed: 34 ]
[ Application: psql - Total duration: 21s443ms - Times executed: 34 ]
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select fixcandlegaps ('ICMARKETS-AU-MT5', false);
Date: 2025-03-05 13:06:23 Duration: 6s483ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ATFX', false);
Date: 2025-03-05 13:06:07 Duration: 2s956ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('AXIORY', false);
Date: 2025-03-05 13:06:09 Duration: 2s218ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 0ms 2s423ms 613ms 235 2m24s 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 Mar 05 13 235 2m24s 613ms [ User: postgres - Total duration: 2m24s - Times executed: 235 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m5s - Times executed: 223 ]
[ Application: [unknown] - Total duration: 18s608ms - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:16:08 Duration: 2s423ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:05:43 Duration: 2s353ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('310' = 0 OR coalesce(bim.code, s.symbol) in ('#AAPL', '#ADS', '#AIG', '#ALV', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BAS', '#BAYN', '#BEI', '#BIDU', '#BMW', '#C', '#CAT', '#CBK', '#CL', '#CSCO', '#CVX', '#DAI', '#DB1', '#DBK', '#DIS', '#DPW', '#DTE', '#EBAY', '#EON', '#F', '#FB', '#FDX', '#FME', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#IFX', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LHA', '#LMT', '#MA', '#MCD', '#META', '#MMM', '#MSFT', '#MUV2', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#RWE', '#SAP', '#SIE', '#T', '#UBER', '#V', '#VOW', '#WB', '#XOM', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'AUS200', 'BRENT', 'BTCUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHI50', 'ESP35', 'ETHUSD', 'EU50', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'FRA40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'LTCUSD', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'SPX500', 'UK100', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'WTI', 'XAGUSD', 'XAUUSD', '#ADS', '#ALV', '#BAS', '#BAYN', '#BEI', '#BMW', '#CBK', '#DAI', '#DB1', '#DBK', '#DPW', '#DTE', '#EON', '#FME', '#IFX', '#LHA', '#MUV2', '#RWE', '#SAP', '#SIE', '#VOW', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BTCUSD', 'ETHUSD', 'LTCUSD', 'AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'CADCHF', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNZD', 'EURPLN', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHKD', 'USDHUF', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDX', 'USDZAR', 'XAGUSD', 'XAUUSD', 'BRENT', 'WTI', 'AUS200', 'CHI50', 'ESP35', 'EU50', 'FRA40', 'GER30', 'HK50', 'HKCH50', 'IT40', 'JP225', 'NAS100', 'SPX500', 'UK100', 'US30', 'AUDUSD', 'EURUSD', 'GBPUSD', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', '#AAPL', '#AIG', '#AMZN', '#AXP', '#BA', '#BABA', '#BAC', '#BIDU', '#C', '#CAT', '#CL', '#CSCO', '#CVX', '#DIS', '#EBAY', '#F', '#FB', '#FDX', '#GE', '#GM', '#GOOG', '#GS', '#HPQ', '#IBM', '#INTC', '#JD', '#JNJ', '#JPM', '#KO', '#LMT', '#MA', '#MCD', '#MMM', '#MSFT', '#NFLX', '#NKE', '#NTES', '#ORCL', '#PFE', '#PG', '#QCOM', '#RACE', '#T', '#UBER', '#V', '#WB', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-03-05 13:41:11 Duration: 2s187ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
12 39ms 5s643ms 542ms 13 7s47ms copy ( select array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ?) as broker_ids, string_to_array(coalesce(replace(broker_symbol_mappings, ?, ?), ?), ?) as broker_symbol_mappings, replace(exchange, ?, ?) as exchange, symbol_id, replace(symbol, ?, ?) as symbol, replace(short_name, ?, ?) as short_name, replace(long_name, ?, ?) as long_name, interval, replace(timezone, ?, ?) as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ?) as search_groups, string_to_array(pattern_basegroupnames, ?) as base_groups, simulation from solr_fetch_results_bm_and_cc (?::character varying, current_timestamp::timestamp without time zone)) t) to ?;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Mar 05 13 13 7s47ms 542ms [ User: postgres - Total duration: 7s47ms - Times executed: 13 ]
[ Application: psql - Total duration: 7s47ms - Times executed: 13 ]
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-03-05 13:03:08 Duration: 5s643ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-03-05 13:01:02 Duration: 334ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
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COPY ( select /*_solr_fetch_results_bm_and_cc_*/ array_to_json(array_agg(row_to_json(t, false))) from ( select distinct pattern_type, uuid, string_to_array(broker_ids, ',') as broker_ids, string_to_array(COALESCE(replace(broker_symbol_mappings, '"', ''), ''), ',') as broker_symbol_mappings, replace(exchange, '"', '') as exchange,symbol_id,replace(symbol,'"','') as symbol, replace(short_name, '"', '') as short_name,replace(long_name,'"','') as long_name, interval, replace(timezone, '"', '') as timezone, timezoneoffset, pattern_gmt_timefound, result_uid, old_result_uid, pattern_id, direction, pattern_name, downloader_symbol, pattern_category, pattern_end_time, pattern_start_time, pattern_length, age, relevance, prediction_time_from, prediction_time_to, prediction_price_from, prediction_price_to, pattern_quality, pattern_start_price, pattern_end_price, breakout, pattern_cp_resx0, pattern_cp_resx1, pattern_cp_resy0, pattern_cp_resy1, pattern_cp_supportx0, pattern_cp_supportx1, pattern_cp_supporty0, pattern_cp_supporty1, pattern_cp_trend_change, pattern_cp_volume_increase, pattern_cp_uniformity, pattern_cp_initial_trend, pattern_clarity, pattern_fp_average_quality, pattern_fp_pricea, pattern_fp_priceb, pattern_fp_pricec, pattern_fp_pricex, pattern_fp_priced, pattern_fp_ratiosfound, pattern_fp_target_03, pattern_fp_target_05, pattern_fp_target_06, pattern_fp_target_07, pattern_fp_target_10, pattern_fp_target_12, pattern_fp_target_16, pattern_fp_timea, pattern_fp_timeb, pattern_fp_timec, pattern_fp_timed, pattern_fp_timequality, pattern_fp_timex, pattern_fp_ratioquality, pattern_kl_errormargin as pattern_kl_error_margin, pattern_kl_breakoutprice as pattern_kl_breakout_price, pattern_kl_breakoutbars as pattern_kl_breakout_bars, pattern_kl_stoplosslevel as pattern_kl_stoploss_level, pattern_kl_approaching_time as pattern_kl_approaching_time, pattern_kl_approachingregion as pattern_kl_approaching_region, pattern_kl_predictiontimebars as pattern_kl_prediction_time_bars, pattern_kl_x0 as pattern_kl_point_x0, pattern_kl_x1 as pattern_kl_point_x1, pattern_kl_x2 as pattern_kl_point_x2, pattern_kl_x3 as pattern_kl_point_x3, pattern_kl_x4 as pattern_kl_point_x4, pattern_kl_x5 as pattern_kl_point_x5, pattern_kl_x6 as pattern_kl_point_x6, pattern_kl_x7 as pattern_kl_point_x7, pattern_kl_x8 as pattern_kl_point_x8, pattern_kl_x9 as pattern_kl_point_x9, pattern_jc_initial_trend_strength, stats_hod_correct, stats_hod_percent, stats_hod_total, stats_pattern_hourofday, stats_pattern_name_correct, stats_pattern_name_percent, stats_pattern_name_total, stats_percent, stats_symbol_correct, stats_symbol_percent, stats_symbol_total, ig_derivativeid, ig_fullname, ig_isunderlying, ig_premium, ig_underlyingid, ig_epic, ig_id, pattern_bm_statistical_movement, pattern_bm_movement, pattern_bm_movement_percentile, pattern_cc_qty_consecutive_candles, pattern_cc_statistical_qty_candles, pattern_cc_consecutice_candles_percentile, pattern_st_to_price, pattern_st_from_price, string_to_array(pattern_groupnames_per_broker, ',') as search_groups, string_to_array(pattern_basegroupnames, ',') as base_groups, simulation from solr_fetch_results_bm_and_cc ('Autochartist'::character varying, current_timestamp::timestamp without time zone)) t) TO '/tmp/solr_inserts_bm_and_cc_acaweb_fx.json';
Date: 2025-03-05 13:18:02 Duration: 207ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: psql
13 135ms 1s472ms 312ms 195 1m 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 Mar 05 13 195 1m 312ms [ User: postgres - Total duration: 1m - Times executed: 195 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m - Times executed: 195 ]
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '621' 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 = '621' 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: 2025-03-05 13:00:05 Duration: 1s472ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '558' 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 = '558' 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: 2025-03-05 13:00:06 Duration: 864ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2025-03-05 13:52:18 Duration: 826ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
14 0ms 440ms 106ms 235 24s977ms with rar_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ), all_results as ( select bmr.resultuid as resultuid, ? 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, bmr.patternendtime as identified, bmr.patternlengthbars, dtt.timezone as timezone, g.basegroupname, case when rbr.age is not null then rbr.age when bmr.resultuid <= rm.resultuid then ? else ? end as age, case when rbr.relevant is not null then rbr.relevant when bmr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from bigmovement_results bmr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = bmr.symbolid inner join symbols s on bmr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on bmr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on bmr.symbolid = sg.symbolid inner 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_bigmovement_results rbr on rbr.resultuid = bmr.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 = ? where bmr.gmttimefound > now() - interval ? and s.deleted = ? and (bmr.simulation = ? or bmr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or bmr.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, interval desc;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Mar 05 13 235 24s977ms 106ms [ User: postgres - Total duration: 24s977ms - Times executed: 235 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 21s734ms - Times executed: 223 ]
[ Application: [unknown] - Total duration: 3s243ms - Times executed: 12 ]
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WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 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, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER 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_bigmovement_results rbr ON rbr.resultuid = bmr.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' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.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 bmr.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, interval DESC;
Date: 2025-03-05 13:01:15 Duration: 440ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 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, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER 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_bigmovement_results rbr ON rbr.resultuid = bmr.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' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.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 bmr.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, interval DESC;
Date: 2025-03-05 13:16:09 Duration: 381ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_bigmovement_results ORDER BY resultuid DESC LIMIT 1 ), all_results AS ( SELECT bmr.resultuid AS resultuid, 0 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, bmr.patternendtime AS identified, bmr.patternlengthbars, dtt.timezone AS timezone, g.basegroupname, CASE WHEN rbr.age IS NOT NULL THEN rbr.age WHEN bmr.resultuid <= rm.resultuid THEN 4 ELSE 0 END as age, CASE WHEN rbr.relevant IS NOT NULL THEN rbr.relevant WHEN bmr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM bigmovement_results bmr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '689' AND bsl.symbolid = bmr.symbolid INNER JOIN symbols s ON bmr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON bmr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on bmr.symbolid = sg.symbolid INNER 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_bigmovement_results rbr ON rbr.resultuid = bmr.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' WHERE bmr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (bmr.simulation = 0 OR bmr.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 bmr.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, interval DESC;
Date: 2025-03-05 13:41:12 Duration: 381ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
15 13ms 175ms 37ms 197 7s363ms 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 Mar 05 13 197 7s363ms 37ms [ User: postgres - Total duration: 7s363ms - Times executed: 197 ]
[ Application: [unknown] - Total duration: 7s363ms - Times executed: 197 ]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-03-05 13:16:00 Duration: 175ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-03-05 13:01:04 Duration: 152ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT distinct a.symbolid, p.resultuid, case when a.breakout >= 0 then 1 else 2 end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient FROM relevance_autochartist_results p INNER JOIN autochartist_results a ON p.resultuid = a.resultuid INNER JOIN autochartist_stocklist asl ON a.symbolid = asl.symbolid WHERE asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2025-03-05 13:31:14 Duration: 150ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
16 0ms 51ms 3ms 32,402 1m37s 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 #16
Day Hour Count Duration Avg duration Mar 05 13 32,402 1m37s 3ms [ User: postgres - Total duration: 1m37s - Times executed: 32402 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m37s - Times executed: 32402 ]
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'SpotBrent' OR dss.downloadersymbol = 'SpotBrent') AND dss.enabled = 1;
Date: 2025-03-05 13:30:06 Duration: 51ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '558' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'GBPJPY' OR dss.downloadersymbol = 'GBPJPY') AND dss.enabled = 1;
Date: 2025-03-05 13:15:05 Duration: 45ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'BA.US' OR dss.downloadersymbol = 'BA.US') AND dss.enabled = 1;
Date: 2025-03-05 13:45:04 Duration: 38ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
17 1ms 4ms 1ms 1,078 1s589ms select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Mar 05 13 1,078 1s589ms 1ms [ User: postgres - Total duration: 1s589ms - Times executed: 1078 ]
[ Application: [unknown] - Total duration: 1s589ms - Times executed: 1078 ]
-
select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;
Date: 2025-03-05 13:56:05 Duration: 4ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
-
select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;
Date: 2025-03-05 13:09:18 Duration: 4ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
-
select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;
Date: 2025-03-05 13:56:12 Duration: 4ms Database: socialmedia User: postgres Remote: 192.168.1.127 Application: [unknown]
18 0ms 33ms 1ms 34,412 49s672ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, 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 #18
Day Hour Count Duration Avg duration Mar 05 13 34,412 49s672ms 1ms [ User: postgres - Total duration: 49s672ms - Times executed: 34412 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 49s672ms - Times executed: 34412 ]
-
SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243265160300';
Date: 2025-03-05 13:30:05 Duration: 33ms 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) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '558' AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '558' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840243225790300';
Date: 2025-03-05 13:00:04 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) coalesce(bim.code, s.symbol) as name, s.symbol as symbol, 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 = '515840249459042300';
Date: 2025-03-05 13:00:06 Duration: 29ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
19 0ms 8ms 1ms 1,959 2s496ms 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 Mar 05 13 1,959 2s496ms 1ms [ User: postgres - Total duration: 2s496ms - Times executed: 1959 ]
[ Application: [unknown] - Total duration: 2s496ms - Times executed: 1959 ]
-
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, 2, '2025-03-05 11:27:07'::timestamp without time zone, '', 0.500000000000000000000000000000, 4, 233, 1.129129999999999967000000000000, '2025-03-04 17:00:00', '2025-02-26 06:30:00', '2025-02-26 00:00:00', '2025-02-25 20:30:00', '', '', '', '', '', '', 582, 1.128452499999999858000000000000, '2025-03-05 13:00:00'::timestamp without time zone, '2025-03-05 13:00:00', 0.000000000000000000000000000000, 0.000695999999999996643000000000, 1, 515840245879097300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840245879097300|1.12913|2|2025-03-05 13:00:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-02-25 20:30:00', 1.129129999999999967000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-05 13:30:45 Duration: 8ms 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, '2025-03-05 11:27:58'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 47, 1.509370000000000100000000000000, '2025-03-05 12:00:00', '2025-03-04 20:30:00', '2025-03-04 12:30:00', '', '', '', '', '', '', '', 94, 1.509829000000000088000000000000, '2025-03-05 13:00:00'::timestamp without time zone, '2025-03-05 13:00:00', 0.000000000000000000000000000000, 0.000460000000000004892800000000, - 1, 515840216986682300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840216986682300|1.50937|1|2025-03-05 13:00:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-03-04 12:30:00', 1.511200000000000099000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-05 13:31:37 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (7.000000000000000000000000000000, - 1, 1, '2025-03-05 10:57:12'::timestamp without time zone, '', 0.500000000000000000000000000000, 4, 109, 104.378500000000002500000000000000, '2025-03-05 03:00:00', '2025-02-28 10:00:00', '2025-02-26 20:00:00', '2025-02-26 13:00:00', '', '', '', '', '', '', 272, 104.511674999999996770000000000000, '2025-03-05 12:00:00'::timestamp without time zone, '2025-03-05 12:00:00', 0.000000000000000000000000000000, 0.133174999999999960100000000000, - 1, 515840230444033300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840230444033300|104.3785|1|2025-03-05 12:00:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2025-02-26 13:00:00', 104.974000000000003750000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2025-03-05 13:00:50 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
20 0ms 34ms 1ms 5,904 7s435ms 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 #20
Day Hour Count Duration Avg duration Mar 05 13 5,904 7s435ms 1ms [ User: postgres - Total duration: 7s435ms - Times executed: 5904 ]
[ Application: [unknown] - Total duration: 7s435ms - Times executed: 5904 ]
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2025-03-05 12:45:00', '0.94829', '0.94878', '0.9481', '0.94856', '1821', '515840245870618300', '0', '2025-03-05 13:00:05.629', '2025-03-05 13:00:05.407') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.94829', high = '0.94878', low = '0.9481', close = '0.94856', volume = '1821', bsf = '0', sastdatetimewritten = '2025-03-05 13:00:05.629', sastdatetimereceived = '2025-03-05 13:00:05.407';
Date: 2025-03-05 13:00:05 Duration: 34ms 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 ('2025-03-05 12:45:00', '93.8635', '93.9185', '93.8085', '93.8415', '1818', '515840230426691300', '0', '2025-03-05 13:00:04.893', '2025-03-05 13:00:04.818') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '93.8635', high = '93.9185', low = '93.8085', close = '93.8415', volume = '1818', bsf = '0', sastdatetimewritten = '2025-03-05 13:00:04.893', sastdatetimereceived = '2025-03-05 13:00:04.818';
Date: 2025-03-05 13:00:04 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 ('2025-03-05 13:30:00', '0.88899', '0.88909', '0.8887', '0.88888', '741', '515840243869386300', '0', '2025-03-05 13:45:04.482', '2025-03-05 13:45:04.437') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.88899', high = '0.88909', low = '0.8887', close = '0.88888', volume = '741', bsf = '0', sastdatetimewritten = '2025-03-05 13:45:04.482', sastdatetimereceived = '2025-03-05 13:45:04.437';
Date: 2025-03-05 13:45:04 Duration: 25ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 2s811ms 3,200 0ms 14ms 0ms WITH rar_max as ( ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Mar 05 13 3,200 2s811ms 0ms [ User: postgres - Total duration: 1h27m46s - Times executed: 3200 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h27m46s - Times executed: 3181 ]
[ Application: [unknown] - Total duration: 28ms - Times executed: 19 ]
-
WITH rar_max as ( ;
Date: 2025-03-05 13:30:06 Duration: 14ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
WITH rar_max as ( ;
Date: 2025-03-05 13:22:03 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
WITH rar_max as ( ;
Date: 2025-03-05 13:46:29 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
2 2s515ms 5,731 0ms 25ms 0ms SELECT ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 13 5,731 2s515ms 0ms [ User: postgres - Total duration: 9s456ms - Times executed: 5731 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 9s261ms - Times executed: 4886 ]
[ Application: [unknown] - Total duration: 194ms - Times executed: 845 ]
-
SELECT ;
Date: 2025-03-05 13:30:06 Duration: 25ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
SELECT ;
Date: 2025-03-05 13:00:05 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
SELECT ;
Date: 2025-03-05 13:00:04 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
3 1s81ms 733 0ms 4ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 13 733 1s81ms 1ms [ User: postgres - Total duration: 1s603ms - Times executed: 733 ]
[ Application: [unknown] - Total duration: 1s603ms - Times executed: 733 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-03-05 13:30:04 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-03-05 13:00:03 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-03-05 13:01:14 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
4 706ms 2,352 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 2,352 706ms 0ms [ User: postgres - Total duration: 5s494ms - Times executed: 2352 ]
[ Application: [unknown] - Total duration: 5s494ms - Times executed: 2352 ]
-
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: 2025-03-05 13:45:04 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: 2025-03-05 13:30:06 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-03-05 13:16:35 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
5 340ms 3,302 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 3,302 340ms 0ms [ User: postgres - Total duration: 2s7ms - Times executed: 3302 ]
[ Application: [unknown] - Total duration: 2s7ms - Times executed: 3302 ]
-
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: 2025-03-05 13:31:00 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: 2025-03-05 13:00:48 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: 2025-03-05 13:40:40 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
6 245ms 2,070 0ms 0ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #6
Day Hour Count Duration Avg duration 13 2,070 245ms 0ms [ User: postgres - Total duration: 1s37ms - Times executed: 2070 ]
[ Application: [unknown] - Total duration: 1s37ms - Times executed: 2070 ]
-
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: 2025-03-05 13:01:02 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: 2025-03-05 13:10:37 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: 2025-03-05 13:00:38 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
7 175ms 1,311 0ms 2ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 13 1,311 175ms 0ms [ User: postgres - Total duration: 12ms - Times executed: 1311 ]
[ Application: [unknown] - Total duration: 12ms - Times executed: 1311 ]
-
SET extra_float_digits = 3;
Date: 2025-03-05 13:45:05 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
SET extra_float_digits = 3;
Date: 2025-03-05 13:01:28 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
SET extra_float_digits = 3;
Date: 2025-03-05 13:30:03 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
8 165ms 866 0ms 2ms 0ms SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;Times Reported Time consuming prepare #8
Day Hour Count Duration Avg duration 13 866 165ms 0ms [ User: postgres - Total duration: 9ms - Times executed: 866 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 9ms - Times executed: 866 ]
-
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: 2025-03-05 13:16:17 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.248
-
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: 2025-03-05 13:16:11 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.248
-
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: 2025-03-05 13:15:41 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.248
9 145ms 2,873 0ms 1ms 0ms select 1;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 13 2,873 145ms 0ms [ User: postgres - Total duration: 13ms - Times executed: 2873 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 13ms - Times executed: 2819 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 54 ]
-
select 1;
Date: 2025-03-05 13:53:32 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
select 1;
Date: 2025-03-05 13:45:05 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
select 1;
Date: 2025-03-05 13:17:16 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
10 66ms 66 0ms 3ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 13 66 66ms 1ms [ User: postgres - Total duration: 24s690ms - Times executed: 66 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 24s690ms - Times executed: 66 ]
-
WITH last_candle AS ( ;
Date: 2025-03-05 13:16:00 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
WITH last_candle AS ( ;
Date: 2025-03-05 13:48:11 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
WITH last_candle AS ( ;
Date: 2025-03-05 13:48:00 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
11 52ms 116 0ms 2ms 0ms WITH pre_symbols AS ( /* find relevant symbols */ ;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 13 116 52ms 0ms [ User: postgres - Total duration: 12s909ms - Times executed: 116 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12s909ms - Times executed: 116 ]
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-03-05 13:14:41 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.248
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-03-05 13:14:42 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.248
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-03-05 13:16:00 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.248
12 47ms 8 4ms 7ms 5ms with sym_info as ( ;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 13 8 47ms 5ms [ User: postgres - Total duration: 26s717ms - Times executed: 8 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 26s717ms - Times executed: 8 ]
-
with sym_info as ( ;
Date: 2025-03-05 13:21:45 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
-
with sym_info as ( ;
Date: 2025-03-05 13:06:43 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
-
with sym_info as ( ;
Date: 2025-03-05 13:06:50 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
13 44ms 18 1ms 3ms 2ms select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 13 18 44ms 2ms [ User: postgres - Total duration: 34ms - Times executed: 18 ]
[ Application: [unknown] - Total duration: 34ms - 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: 2025-03-05 13:41:01 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-03-05 13:31:01 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-03-05 13:31:01 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
14 27ms 14 0ms 3ms 1ms with wh_patitioned as ( ;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 13 14 27ms 1ms [ User: postgres - Total duration: 419ms - Times executed: 14 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 419ms - Times executed: 14 ]
-
with wh_patitioned as ( ;
Date: 2025-03-05 13:48:00 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
with wh_patitioned as ( ;
Date: 2025-03-05 13:02:09 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
with wh_patitioned as ( ;
Date: 2025-03-05 13:50:03 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
15 20ms 31 0ms 1ms 0ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming prepare #15
Day Hour Count Duration Avg duration 13 31 20ms 0ms [ User: postgres - Total duration: 0ms - Times executed: 31 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 0ms - Times executed: 31 ]
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-03-05 13:38:29 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-03-05 13:35:46 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-03-05 13:47:05 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
16 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 #16
Day Hour Count Duration Avg duration 13 6 18ms 3ms [ User: postgres - Total duration: 13ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 13ms - 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: 2025-03-05 13:10:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2025-03-05 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: 2025-03-05 13:00:06 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
17 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 #17
Day Hour Count Duration Avg duration 13 6 16ms 2ms [ User: postgres - Total duration: 34s57ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 34s57ms - 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: 2025-03-05 13:00:02 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-03-05 13:50:02 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: 2025-03-05 13:30:02 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
18 15ms 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 15ms 0ms [ User: postgres - Total duration: 60ms - Times executed: 24 ]
[ Application: [unknown] - Total duration: 60ms - Times executed: 24 ]
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-03-05 13:30:01 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: 2025-03-05 13:00:02 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: 2025-03-05 13:10:02 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
19 15ms 32 0ms 1ms 0ms SELECT pricedatetime, ;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 13 32 15ms 0ms [ User: postgres - Total duration: 4ms - Times executed: 32 ]
[ Application: [unknown] - Total duration: 4ms - Times executed: 32 ]
-
SELECT pricedatetime, ;
Date: 2025-03-05 13:17:31 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT pricedatetime, ;
Date: 2025-03-05 13:15:31 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT pricedatetime, ;
Date: 2025-03-05 13:16:30 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
20 15ms 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 15ms 1ms [ User: postgres - Total duration: 46ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 46ms - 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: 2025-03-05 13:46:20 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: 2025-03-05 13:41:19 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: 2025-03-05 13:11:13 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 36s657ms 85,594 0ms 33ms 0ms SELECT ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Mar 05 13 85,594 36s657ms 0ms [ User: postgres - Total duration: 2m47s - Times executed: 85594 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m47s - Times executed: 84719 ]
[ Application: [unknown] - Total duration: 206ms - Times executed: 875 ]
-
SELECT ;
Date: 2025-03-05 13:30:04 Duration: 33ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '515840243163260300'
-
SELECT ;
Date: 2025-03-05 13:00:04 Duration: 26ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '558', $3 = '515840243225790300'
-
SELECT ;
Date: 2025-03-05 13:00:05 Duration: 22ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '0', $2 = '0', $3 = '515840243194668300'
2 33s437ms 5,851 0ms 56ms 5ms WITH rar_max as ( ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 13 5,851 33s437ms 5ms [ User: postgres - Total duration: 1h53m5s - Times executed: 5851 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h45m49s - Times executed: 5767 ]
[ Application: [unknown] - Total duration: 7m16s - Times executed: 84 ]
-
WITH rar_max as ( ;
Date: 2025-03-05 13:16:11 Duration: 56ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '972', $2 = '5', $3 = '15', $4 = '30', $5 = '60', $6 = '240', $7 = '1440', $8 = '0', $9 = '', $10 = '98', $11 = 'AUDUSD', $12 = 'EURUSD', $13 = 'GBPUSD', $14 = 'USDCAD', $15 = 'USDCHF', $16 = 'USDJPY', $17 = 'AUDCAD', $18 = 'AUDCHF', $19 = 'AUDJPY', $20 = 'AUDNZD', $21 = 'CADCHF', $22 = 'CADJPY', $23 = 'CHFJPY', $24 = 'EURAUD', $25 = 'EURCAD', $26 = 'EURCHF', $27 = 'EURGBP', $28 = 'EURJPY', $29 = 'EURNZD', $30 = 'GBPAUD', $31 = 'GBPCAD', $32 = 'GBPCHF', $33 = 'GBPJPY', $34 = 'GBPNZD', $35 = 'NZDCAD', $36 = 'NZDCHF', $37 = 'NZDJPY', $38 = 'NZDUSD', $39 = 'USDSGD', $40 = 'AUDSGD', $41 = 'CHFSGD', $42 = 'EURDKK', $43 = 'EURHKD', $44 = 'EURNOK', $45 = 'EURPLN', $46 = 'EURSEK', $47 = 'EURSGD', $48 = 'EURTRY', $49 = 'EURZAR', $50 = 'GBPDKK', $51 = 'GBPNOK', $52 = 'GBPSEK', $53 = 'GBPSGD', $54 = 'NOKJPY', $55 = 'NOKSEK', $56 = 'SEKJPY', $57 = 'SGDJPY', $58 = 'USDCNH', $59 = 'USDCZK', $60 = 'USDDKK', $61 = 'USDHKD', $62 = 'USDHUF', $63 = 'USDMXN', $64 = 'USDNOK', $65 = 'USDPLN', $66 = 'USDRUB', $67 = 'USDSEK', $68 = 'USDTHB', $69 = 'USDTRY', $70 = 'USDZAR', $71 = 'BRENT_U7', $72 = 'BRENT_V7', $73 = 'Coffee_N7', $74 = 'Coffee_U7', $75 = 'Corn_N7', $76 = 'Corn_U7', $77 = 'Soybean_Q7', $78 = 'Soybean_U7', $79 = 'Sugar_N7', $80 = 'Sugar_V7', $81 = 'WTI_U7', $82 = 'WTI_V7', $83 = 'Wheat_N7', $84 = 'Wheat_U7', $85 = 'XBRUSD', $86 = 'XNGUSD', $87 = 'XTIUSD', $88 = 'XAGEUR', $89 = 'XAGUSD', $90 = 'XAUEUR', $91 = 'XAUUSD', $92 = 'XPDUSD', $93 = 'XPTUSD', $94 = 'AUS200', $95 = 'CHINA50', $96 = 'DE30', $97 = 'ES35', $98 = 'F40', $99 = 'HK50', $100 = 'IT40', $101 = 'JP225', $102 = 'STOXX50', $103 = 'UK100', $104 = 'US2000', $105 = 'US30', $106 = 'US500', $107 = 'USTEC', $108 = 'BTCUSD', $109 = '400', $110 = '400', $111 = 't', $112 = '10', $113 = '10'
-
WITH rar_max as ( ;
Date: 2025-03-05 13:16:14 Duration: 49ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 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 = '0', $100 = '0', $101 = 't', $102 = '10', $103 = '10'
-
WITH rar_max as ( ;
Date: 2025-03-05 13:16:11 Duration: 44ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '972', $2 = '5', $3 = '15', $4 = '30', $5 = '60', $6 = '240', $7 = '1440', $8 = '0', $9 = '', $10 = '98', $11 = 'AUDUSD', $12 = 'EURUSD', $13 = 'GBPUSD', $14 = 'USDCAD', $15 = 'USDCHF', $16 = 'USDJPY', $17 = 'AUDCAD', $18 = 'AUDCHF', $19 = 'AUDJPY', $20 = 'AUDNZD', $21 = 'CADCHF', $22 = 'CADJPY', $23 = 'CHFJPY', $24 = 'EURAUD', $25 = 'EURCAD', $26 = 'EURCHF', $27 = 'EURGBP', $28 = 'EURJPY', $29 = 'EURNZD', $30 = 'GBPAUD', $31 = 'GBPCAD', $32 = 'GBPCHF', $33 = 'GBPJPY', $34 = 'GBPNZD', $35 = 'NZDCAD', $36 = 'NZDCHF', $37 = 'NZDJPY', $38 = 'NZDUSD', $39 = 'USDSGD', $40 = 'AUDSGD', $41 = 'CHFSGD', $42 = 'EURDKK', $43 = 'EURHKD', $44 = 'EURNOK', $45 = 'EURPLN', $46 = 'EURSEK', $47 = 'EURSGD', $48 = 'EURTRY', $49 = 'EURZAR', $50 = 'GBPDKK', $51 = 'GBPNOK', $52 = 'GBPSEK', $53 = 'GBPSGD', $54 = 'NOKJPY', $55 = 'NOKSEK', $56 = 'SEKJPY', $57 = 'SGDJPY', $58 = 'USDCNH', $59 = 'USDCZK', $60 = 'USDDKK', $61 = 'USDHKD', $62 = 'USDHUF', $63 = 'USDMXN', $64 = 'USDNOK', $65 = 'USDPLN', $66 = 'USDRUB', $67 = 'USDSEK', $68 = 'USDTHB', $69 = 'USDTRY', $70 = 'USDZAR', $71 = 'BRENT_U7', $72 = 'BRENT_V7', $73 = 'Coffee_N7', $74 = 'Coffee_U7', $75 = 'Corn_N7', $76 = 'Corn_U7', $77 = 'Soybean_Q7', $78 = 'Soybean_U7', $79 = 'Sugar_N7', $80 = 'Sugar_V7', $81 = 'WTI_U7', $82 = 'WTI_V7', $83 = 'Wheat_N7', $84 = 'Wheat_U7', $85 = 'XBRUSD', $86 = 'XNGUSD', $87 = 'XTIUSD', $88 = 'XAGEUR', $89 = 'XAGUSD', $90 = 'XAUEUR', $91 = 'XAUUSD', $92 = 'XPDUSD', $93 = 'XPTUSD', $94 = 'AUS200', $95 = 'CHINA50', $96 = 'DE30', $97 = 'ES35', $98 = 'F40', $99 = 'HK50', $100 = 'IT40', $101 = 'JP225', $102 = 'STOXX50', $103 = 'UK100', $104 = 'US2000', $105 = 'US30', $106 = 'US500', $107 = 'USTEC', $108 = 'BTCUSD', $109 = '400', $110 = '400', $111 = 't', $112 = '10', $113 = '10'
3 1s419ms 733 1ms 10ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 13 733 1s419ms 1ms [ User: postgres - Total duration: 1s603ms - Times executed: 733 ]
[ Application: [unknown] - Total duration: 1s603ms - Times executed: 733 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-03-05 13:00:05 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: 2025-03-05 13:30:06 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'FPMARKETS'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-03-05 13:01:12 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'AXIORY'
4 1s370ms 195 4ms 32ms 7ms WITH last_candle AS ( ;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 13 195 1s370ms 7ms [ User: postgres - Total duration: 1m - Times executed: 195 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m - Times executed: 195 ]
-
WITH last_candle AS ( ;
Date: 2025-03-05 13:00:05 Duration: 32ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2025-03-05 13:44:08 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '972', $2 = '972'
-
WITH last_candle AS ( ;
Date: 2025-03-05 13:56:09 Duration: 18ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '972', $2 = '972'
5 1s124ms 49 0ms 44ms 22ms with wh_patitioned as ( ;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 13 49 1s124ms 22ms [ User: postgres - Total duration: 1s237ms - Times executed: 49 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s237ms - Times executed: 49 ]
-
with wh_patitioned as ( ;
Date: 2025-03-05 13:48:00 Duration: 44ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '529', $2 = '529', $3 = '529', $4 = '529', $5 = '529', $6 = '529', $7 = '529', $8 = '529', $9 = '529'
-
with wh_patitioned as ( ;
Date: 2025-03-05 13:31:07 Duration: 43ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '627', $2 = '627', $3 = '627', $4 = '627', $5 = '627', $6 = '627', $7 = '627', $8 = '627', $9 = '627'
-
with wh_patitioned as ( ;
Date: 2025-03-05 13:02:09 Duration: 42ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '529', $2 = '529', $3 = '529', $4 = '529', $5 = '529', $6 = '529', $7 = '529', $8 = '529', $9 = '529'
6 1s51ms 60,408 0ms 16ms 0ms select 1;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 13 60,408 1s51ms 0ms [ User: postgres - Total duration: 291ms - Times executed: 60408 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 290ms - Times executed: 60207 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 201 ]
-
select 1;
Date: 2025-03-05 13:00:06 Duration: 16ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
select 1;
Date: 2025-03-05 13:45:05 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
select 1;
Date: 2025-03-05 13:00:03 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
7 602ms 5,904 0ms 25ms 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 #7
Day Hour Count Duration Avg duration 13 5,904 602ms 0ms [ User: postgres - Total duration: 7s435ms - Times executed: 5904 ]
[ Application: [unknown] - Total duration: 7s435ms - Times executed: 5904 ]
-
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: 2025-03-05 13:30:05 Duration: 25ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-03-05 13:15:00', $2 = '31.67', $3 = '31.71', $4 = '31.32', $5 = '31.5', $6 = '372', $7 = '515840247893280300', $8 = '0', $9 = '2025-03-05 13:30:05.448', $10 = '2025-03-05 13:30:05.258', $11 = '31.67', $12 = '31.71', $13 = '31.32', $14 = '31.5', $15 = '372', $16 = '0', $17 = '2025-03-05 13:30:05.448', $18 = '2025-03-05 13:30:05.258'
-
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: 2025-03-05 13:16:35 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-03-05 14:00:00', $2 = '70', $3 = '70.14', $4 = '69.94', $5 = '70.09', $6 = '208', $7 = '515840249389884300', $8 = '0', $9 = '2025-03-05 13:16:35.158', $10 = '2025-03-05 13:16:35.127', $11 = '70', $12 = '70.14', $13 = '69.94', $14 = '70.09', $15 = '208', $16 = '0', $17 = '2025-03-05 13:16:35.158', $18 = '2025-03-05 13:16:35.127'
-
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: 2025-03-05 13:00:04 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-03-05 13:30:00', $2 = '378.495', $3 = '380.575', $4 = '375.85', $5 = '376.715', $6 = '992', $7 = '515840249398052300', $8 = '0', $9 = '2025-03-05 13:00:04.615', $10 = '2025-03-05 13:00:04.518', $11 = '378.495', $12 = '380.575', $13 = '375.85', $14 = '376.715', $15 = '992', $16 = '0', $17 = '2025-03-05 13:00:04.615', $18 = '2025-03-05 13:00:04.518'
8 428ms 31 9ms 21ms 13ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 13 31 428ms 13ms [ User: postgres - Total duration: 0ms - Times executed: 31 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 0ms - Times executed: 31 ]
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-03-05 13:38:29 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-03-05 13:35:46 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 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: 2025-03-05 13:47:05 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
9 403ms 866 0ms 2ms 0ms SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 13 866 403ms 0ms [ User: postgres - Total duration: 9ms - Times executed: 866 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 9ms - Times executed: 866 ]
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-03-05 13:15:29 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.248
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-03-05 13:16:11 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.248
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-03-05 13:15:41 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.248
10 324ms 116 0ms 34ms 2ms WITH pre_symbols AS ( /* find relevant symbols */ ;Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 13 116 324ms 2ms [ User: postgres - Total duration: 12s909ms - Times executed: 116 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12s909ms - Times executed: 116 ]
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WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-03-05 13:16:05 Duration: 34ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.248 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: 2025-03-05 13:16:14 Duration: 33ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.248 parameters: $1 = '974', $2 = 'ICMARKETS-AU-MT5', $3 = 'AUDCAD', $4 = 'AUDCHF', $5 = 'AUDJPY', $6 = 'AUDNZD', $7 = 'AUDSGD', $8 = 'AUDUSD', $9 = 'AUS200', $10 = 'BRENT_F0', $11 = 'BRENT_F1', $12 = 'BRENT_F2', $13 = 'BRENT_F3', $14 = 'BRENT_F4', $15 = 'BRENT_F5', $16 = 'BRENT_F6', $17 = 'BRENT_F7', $18 = 'BRENT_F8', $19 = 'BRENT_F9', $20 = 'BRENT_G0', $21 = 'BRENT_G1', $22 = 'BRENT_G2', $23 = 'BRENT_G3', $24 = 'BRENT_G4', $25 = 'BRENT_G5', $26 = 'BRENT_G6', $27 = 'BRENT_G7', $28 = 'BRENT_G8', $29 = 'BRENT_G9', $30 = 'BRENT_H0', $31 = 'BRENT_H1', $32 = 'BRENT_H2', $33 = 'BRENT_H3', $34 = 'BRENT_H4', $35 = 'BRENT_H5', $36 = 'BRENT_H6', $37 = 'BRENT_H7', $38 = 'BRENT_H8', $39 = 'BRENT_H9', $40 = 'BRENT_J0', $41 = 'BRENT_J1', $42 = 'BRENT_J2', $43 = 'BRENT_J3', $44 = 'BRENT_J4', $45 = 'BRENT_J5', $46 = 'BRENT_J6', $47 = 'BRENT_J7', $48 = 'BRENT_J8', $49 = 'BRENT_J9', $50 = 'BRENT_K0', $51 = 'BRENT_K1', $52 = 'BRENT_K2', $53 = 'BRENT_K3', $54 = 'BRENT_K4', $55 = 'BRENT_K5', $56 = 'BRENT_K6', $57 = 'BRENT_K7', $58 = 'BRENT_K8', $59 = 'BRENT_K9', $60 = 'BRENT_M0', $61 = 'BRENT_M1', $62 = 'BRENT_M2', $63 = 'BRENT_M3', $64 = 'BRENT_M4', $65 = 'BRENT_M5', $66 = 'BRENT_M6', $67 = 'BRENT_M7', $68 = 'BRENT_M8', $69 = 'BRENT_M9', $70 = 'BRENT_N0', $71 = 'BRENT_N1', $72 = 'BRENT_N2', $73 = 'BRENT_N3', $74 = 'BRENT_N4', $75 = 'BRENT_N5', $76 = 'BRENT_N6', $77 = 'BRENT_N7', $78 = 'BRENT_N8', $79 = 'BRENT_N9', $80 = 'BRENT_Q0', $81 = 'BRENT_Q1', $82 = 'BRENT_Q2', $83 = 'BRENT_Q3', $84 = 'BRENT_Q4', $85 = 'BRENT_Q5', $86 = 'BRENT_Q6', $87 = 'BRENT_Q7', $88 = 'BRENT_Q8', $89 = 'BRENT_Q9', $90 = 'BRENT_U0', $91 = 'BRENT_U1', $92 = 'BRENT_U2', $93 = 'BRENT_U3', $94 = 'BRENT_U4', $95 = 'BRENT_U5', $96 = 'BRENT_U6', $97 = 'BRENT_U7', $98 = 'BRENT_U8', $99 = 'BRENT_U9', $100 = 'BRENT_V0', $101 = 'BRENT_V1', $102 = 'BRENT_V2', $103 = 'BRENT_V3', $104 = 'BRENT_V4', $105 = 'BRENT_V5', $106 = 'BRENT_V6', $107 = 'BRENT_V7', $108 = 'BRENT_V8', $109 = 'BRENT_V9', $110 = 'BRENT_X0', $111 = 'BRENT_X1', $112 = 'BRENT_X2', $113 = 'BRENT_X3', $114 = 'BRENT_X4', $115 = 'BRENT_X5', $116 = 'BRENT_X6', $117 = 'BRENT_X7', $118 = 'BRENT_X8', $119 = 'BRENT_X9', $120 = 'BRENT_Z0', $121 = 'BRENT_Z1', $122 = 'BRENT_Z2', $123 = 'BRENT_Z3', $124 = 'BRENT_Z4', $125 = 'BRENT_Z5', $126 = 'BRENT_Z6', $127 = 'BRENT_Z7', $128 = 'BRENT_Z8', $129 = 'BRENT_Z9', $130 = 'BTCUSD', $131 = 'CADCHF', $132 = 'CADJPY', $133 = 'CHFJPY', $134 = 'CHFSGD', $135 = 'CHINA50', $136 = 'Coffee_F0', $137 = 'Coffee_F1', $138 = 'Coffee_F2', $139 = 'Coffee_F3', $140 = 'Coffee_F4', $141 = 'Coffee_F5', $142 = 'Coffee_F6', $143 = 'Coffee_F7', $144 = 'Coffee_F8', $145 = 'Coffee_F9', $146 = 'Coffee_G0', $147 = 'Coffee_G1', $148 = 'Coffee_G2', $149 = 'Coffee_G3', $150 = 'Coffee_G4', $151 = 'Coffee_G5', $152 = 'Coffee_G6', $153 = 'Coffee_G7', $154 = 'Coffee_G8', $155 = 'Coffee_G9', $156 = 'Coffee_H0', $157 = 'Coffee_H1', $158 = 'Coffee_H2', $159 = 'Coffee_H3', $160 = 'Coffee_H4', $161 = 'Coffee_H5', $162 = 'Coffee_H6', $163 = 'Coffee_H7', $164 = 'Coffee_H8', $165 = 'Coffee_H9', $166 = 'Coffee_J0', $167 = 'Coffee_J1', $168 = 'Coffee_J2', $169 = 'Coffee_J3', $170 = 'Coffee_J4', $171 = 'Coffee_J5', $172 = 'Coffee_J6', $173 = 'Coffee_J7', $174 = 'Coffee_J8', $175 = 'Coffee_J9', $176 = 'Coffee_K0', $177 = 'Coffee_K1', $178 = 'Coffee_K2', $179 = 'Coffee_K3', $180 = 'Coffee_K4', $181 = 'Coffee_K5', $182 = 'Coffee_K6', $183 = 'Coffee_K7', $184 = 'Coffee_K8', $185 = 'Coffee_K9', $186 = 'Coffee_M0', $187 = 'Coffee_M1', $188 = 'Coffee_M2', $189 = 'Coffee_M3', $190 = 'Coffee_M4', $191 = 'Coffee_M5', $192 = 'Coffee_M6', $193 = 'Coffee_M7', $194 = 'Coffee_M8', $195 = 'Coffee_M9', $196 = 'Coffee_N0', $197 = 'Coffee_N1', $198 = 'Coffee_N2', $199 = 'Coffee_N3', $200 = 'Coffee_N4', $201 = 'Coffee_N5', $202 = 'Coffee_N6', $203 = 'Coffee_N7', $204 = 'Coffee_N8', $205 = 'Coffee_N9', $206 = 'Coffee_Q0', $207 = 'Coffee_Q1', $208 = 'Coffee_Q2', $209 = 'Coffee_Q3', $210 = 'Coffee_Q4', $211 = 'Coffee_Q5', $212 = 'Coffee_Q6', $213 = 'Coffee_Q7', $214 = 'Coffee_Q8', $215 = 'Coffee_Q9', $216 = 'Coffee_U0', $217 = 'Coffee_U1', $218 = 'Coffee_U2', $219 = 'Coffee_U3', $220 = 'Coffee_U4', $221 = 'Coffee_U5', $222 = 'Coffee_U6', $223 = 'Coffee_U7', $224 = 'Coffee_U8', $225 = 'Coffee_U9', $226 = 'Coffee_V0', $227 = 'Coffee_V1', $228 = 'Coffee_V2', $229 = 'Coffee_V3', $230 = 'Coffee_V4', $231 = 'Coffee_V5', $232 = 'Coffee_V6', $233 = 'Coffee_V7', $234 = 'Coffee_V8', $235 = 'Coffee_V9', $236 = 'Coffee_X0', $237 = 'Coffee_X1', $238 = 'Coffee_X2', $239 = 'Coffee_X3', $240 = 'Coffee_X4', $241 = 'Coffee_X5', $242 = 'Coffee_X6', $243 = 'Coffee_X7', $244 = 'Coffee_X8', $245 = 'Coffee_X9', $246 = 'Coffee_Z0', $247 = 'Coffee_Z1', $248 = 'Coffee_Z2', $249 = 'Coffee_Z3', $250 = 'Coffee_Z4', $251 = 'Coffee_Z5', $252 = 'Coffee_Z6', $253 = 'Coffee_Z7', $254 = 'Coffee_Z8', $255 = 'Coffee_Z9', $256 = 'Corn_F0', $257 = 'Corn_F1', $258 = 'Corn_F2', $259 = 'Corn_F3', $260 = 'Corn_F4', $261 = 'Corn_F5', $262 = 'Corn_F6', $263 = 'Corn_F7', $264 = 'Corn_F8', $265 = 'Corn_F9', $266 = 'Corn_G0', $267 = 'Corn_G1', $268 = 'Corn_G2', $269 = 'Corn_G3', $270 = 'Corn_G4', $271 = 'Corn_G5', $272 = 'Corn_G6', $273 = 'Corn_G7', $274 = 'Corn_G8', $275 = 'Corn_G9', $276 = 'Corn_H0', $277 = 'Corn_H1', $278 = 'Corn_H2', $279 = 'Corn_H3', $280 = 'Corn_H4', $281 = 'Corn_H5', $282 = 'Corn_H6', $283 = 'Corn_H7', $284 = 'Corn_H8', $285 = 'Corn_H9', $286 = 'Corn_J0', $287 = 'Corn_J1', $288 = 'Corn_J2', $289 = 'Corn_J3', $290 = 'Corn_J4', $291 = 'Corn_J5', $292 = 'Corn_J6', $293 = 'Corn_J7', $294 = 'Corn_J8', $295 = 'Corn_J9', $296 = 'Corn_K0', $297 = 'Corn_K1', $298 = 'Corn_K2', $299 = 'Corn_K3', $300 = 'Corn_K4', $301 = 'Corn_K5', $302 = 'Corn_K6', $303 = 'Corn_K7', $304 = 'Corn_K8', $305 = 'Corn_K9', $306 = 'Corn_M0', $307 = 'Corn_M1', $308 = 'Corn_M2', $309 = 'Corn_M3', $310 = 'Corn_M4', $311 = 'Corn_M5', $312 = 'Corn_M6', $313 = 'Corn_M7', $314 = 'Corn_M8', $315 = 'Corn_M9', $316 = 'Corn_N0', $317 = 'Corn_N1', $318 = 'Corn_N2', $319 = 'Corn_N3', $320 = 'Corn_N4', $321 = 'Corn_N5', $322 = 'Corn_N6', $323 = 'Corn_N7', $324 = 'Corn_N8', $325 = 'Corn_N9', $326 = 'Corn_Q0', $327 = 'Corn_Q1', $328 = 'Corn_Q2', $329 = 'Corn_Q3', $330 = 'Corn_Q4', $331 = 'Corn_Q5', $332 = 'Corn_Q6', $333 = 'Corn_Q7', $334 = 'Corn_Q8', $335 = 'Corn_Q9', $336 = 'Corn_U0', $337 = 'Corn_U1', $338 = 'Corn_U2', $339 = 'Corn_U3', $340 = 'Corn_U4', $341 = 'Corn_U5', $342 = 'Corn_U6', $343 = 'Corn_U7', $344 = 'Corn_U8', $345 = 'Corn_U9', $346 = 'Corn_V0', $347 = 'Corn_V1', $348 = 'Corn_V2', $349 = 'Corn_V3', $350 = 'Corn_V4', $351 = 'Corn_V5', $352 = 'Corn_V6', $353 = 'Corn_V7', $354 = 'Corn_V8', $355 = 'Corn_V9', $356 = 'Corn_X0', $357 = 'Corn_X1', $358 = 'Corn_X2', $359 = 'Corn_X3', $360 = 'Corn_X4', $361 = 'Corn_X5', $362 = 'Corn_X6', $363 = 'Corn_X7', $364 = 'Corn_X8', $365 = 'Corn_X9', $366 = 'Corn_Z0', $367 = 'Corn_Z1', $368 = 'Corn_Z2', $369 = 'Corn_Z3', $370 = 'Corn_Z4', $371 = 'Corn_Z5', $372 = 'Corn_Z6', $373 = 'Corn_Z7', $374 = 'Corn_Z8', $375 = 'Corn_Z9', $376 = 'DE30', $377 = 'ES35', $378 = 'EURAUD', $379 = 'EURCAD', $380 = 'EURCHF', $381 = 'EURDKK', $382 = 'EURGBP', $383 = 'EURHKD', $384 = 'EURJPY', $385 = 'EURNOK', $386 = 'EURNZD', $387 = 'EURPLN', $388 = 'EURSEK', $389 = 'EURSGD', $390 = 'EURTRY', $391 = 'EURUSD', $392 = 'EURZAR', $393 = 'F40', $394 = 'GBPAUD', $395 = 'GBPCAD', $396 = 'GBPCHF', $397 = 'GBPDKK', $398 = 'GBPJPY', $399 = 'GBPNOK', $400 = 'GBPNZD', $401 = 'GBPSEK', $402 = 'GBPSGD', $403 = 'GBPUSD', $404 = 'HK50', $405 = 'IT40', $406 = 'JP225', $407 = 'NOKJPY', $408 = 'NOKSEK', $409 = 'NZDCAD', $410 = 'NZDCHF', $411 = 'NZDJPY', $412 = 'NZDUSD', $413 = 'SEKJPY', $414 = 'SGDJPY', $415 = 'STOXX50', $416 = 'Soybean_F0', $417 = 'Soybean_F1', $418 = 'Soybean_F2', $419 = 'Soybean_F3', $420 = 'Soybean_F4', $421 = 'Soybean_F5', $422 = 'Soybean_F6', $423 = 'Soybean_F7', $424 = 'Soybean_F8', $425 = 'Soybean_F9', $426 = 'Soybean_G0', $427 = 'Soybean_G1', $428 = 'Soybean_G2', $429 = 'Soybean_G3', $430 = 'Soybean_G4', $431 = 'Soybean_G5', $432 = 'Soybean_G6', $433 = 'Soybean_G7', $434 = 'Soybean_G8', $435 = 'Soybean_G9', $436 = 'Soybean_H0', $437 = 'Soybean_H1', $438 = 'Soybean_H2', $439 = 'Soybean_H3', $440 = 'Soybean_H4', $441 = 'Soybean_H5', $442 = 'Soybean_H6', $443 = 'Soybean_H7', $444 = 'Soybean_H8', $445 = 'Soybean_H9', $446 = 'Soybean_J0', $447 = 'Soybean_J1', $448 = 'Soybean_J2', $449 = 'Soybean_J3', $450 = 'Soybean_J4', $451 = 'Soybean_J5', $452 = 'Soybean_J6', $453 = 'Soybean_J7', $454 = 'Soybean_J8', $455 = 'Soybean_J9', $456 = 'Soybean_K0', $457 = 'Soybean_K1', $458 = 'Soybean_K2', $459 = 'Soybean_K3', $460 = 'Soybean_K4', $461 = 'Soybean_K5', $462 = 'Soybean_K6', $463 = 'Soybean_K7', $464 = 'Soybean_K8', $465 = 'Soybean_K9', $466 = 'Soybean_M0', $467 = 'Soybean_M1', $468 = 'Soybean_M2', $469 = 'Soybean_M3', $470 = 'Soybean_M4', $471 = 'Soybean_M5', $472 = 'Soybean_M6', $473 = 'Soybean_M7', $474 = 'Soybean_M8', $475 = 'Soybean_M9', $476 = 'Soybean_N0', $477 = 'Soybean_N1', $478 = 'Soybean_N2', $479 = 'Soybean_N3', $480 = 'Soybean_N4', $481 = 'Soybean_N5', $482 = 'Soybean_N6', $483 = 'Soybean_N7', $484 = 'Soybean_N8', $485 = 'Soybean_N9', $486 = 'Soybean_Q0', $487 = 'Soybean_Q1', $488 = 'Soybean_Q2', $489 = 'Soybean_Q3', $490 = 'Soybean_Q4', $491 = 'Soybean_Q5', $492 = 'Soybean_Q6', $493 = 'Soybean_Q7', $494 = 'Soybean_Q8', $495 = 'Soybean_Q9', $496 = 'Soybean_U0', $497 = 'Soybean_U1', $498 = 'Soybean_U2', $499 = 'Soybean_U3', $500 = 'Soybean_U4', $501 = 'Soybean_U5', $502 = 'Soybean_U6', $503 = 'Soybean_U7', $504 = 'Soybean_U8', $505 = 'Soybean_U9', $506 = 'Soybean_V0', $507 = 'Soybean_V1', $508 = 'Soybean_V2', $509 = 'Soybean_V3', $510 = 'Soybean_V4', $511 = 'Soybean_V5', $512 = 'Soybean_V6', $513 = 'Soybean_V7', $514 = 'Soybean_V8', $515 = 'Soybean_V9', $516 = 'Soybean_X0', $517 = 'Soybean_X1', $518 = 'Soybean_X2', $519 = 'Soybean_X3', $520 = 'Soybean_X4', $521 = 'Soybean_X5', $522 = 'Soybean_X6', $523 = 'Soybean_X7', $524 = 'Soybean_X8', $525 = 'Soybean_X9', $526 = 'Soybean_Z0', $527 = 'Soybean_Z1', $528 = 'Soybean_Z2', $529 = 'Soybean_Z3', $530 = 'Soybean_Z4', $531 = 'Soybean_Z5', $532 = 'Soybean_Z6', $533 = 'Soybean_Z7', $534 = 'Soybean_Z8', $535 = 'Soybean_Z9', $536 = 'Sugar_F0', $537 = 'Sugar_F1', $538 = 'Sugar_F2', $539 = 'Sugar_F3', $540 = 'Sugar_F4', $541 = 'Sugar_F5', $542 = 'Sugar_F6', $543 = 'Sugar_F7', $544 = 'Sugar_F8', $545 = 'Sugar_F9', $546 = 'Sugar_G0', $547 = 'Sugar_G1', $548 = 'Sugar_G2', $549 = 'Sugar_G3', $550 = 'Sugar_G4', $551 = 'Sugar_G5', $552 = 'Sugar_G6', $553 = 'Sugar_G7', $554 = 'Sugar_G8', $555 = 'Sugar_G9', $556 = 'Sugar_H0', $557 = 'Sugar_H1', $558 = 'Sugar_H2', $559 = 'Sugar_H3', $560 = 'Sugar_H4', $561 = 'Sugar_H5', $562 = 'Sugar_H6', $563 = 'Sugar_H7', $564 = 'Sugar_H8', $565 = 'Sugar_H9', $566 = 'Sugar_J0', $567 = 'Sugar_J1', $568 = 'Sugar_J2', $569 = 'Sugar_J3', $570 = 'Sugar_J4', $571 = 'Sugar_J5', $572 = 'Sugar_J6', $573 = 'Sugar_J7', $574 = 'Sugar_J8', $575 = 'Sugar_J9', $576 = 'Sugar_K0', $577 = 'Sugar_K1', $578 = 'Sugar_K2', $579 = 'Sugar_K3', $580 = 'Sugar_K4', $581 = 'Sugar_K5', $582 = 'Sugar_K6', $583 = 'Sugar_K7', $584 = 'Sugar_K8', $585 = 'Sugar_K9', $586 = 'Sugar_M0', $587 = 'Sugar_M1', $588 = 'Sugar_M2', $589 = 'Sugar_M3', $590 = 'Sugar_M4', $591 = 'Sugar_M5', $592 = 'Sugar_M6', $593 = 'Sugar_M7', $594 = 'Sugar_M8', $595 = 'Sugar_M9', $596 = 'Sugar_N0', $597 = 'Sugar_N1', $598 = 'Sugar_N2', $599 = 'Sugar_N3', $600 = 'Sugar_N4', $601 = 'Sugar_N5', $602 = 'Sugar_N6', $603 = 'Sugar_N7', $604 = 'Sugar_N8', $605 = 'Sugar_N9', $606 = 'Sugar_Q0', $607 = 'Sugar_Q1', $608 = 'Sugar_Q2', $609 = 'Sugar_Q3', $610 = 'Sugar_Q4', $611 = 'Sugar_Q5', $612 = 'Sugar_Q6', $613 = 'Sugar_Q7', $614 = 'Sugar_Q8', $615 = 'Sugar_Q9', $616 = 'Sugar_U0', $617 = 'Sugar_U1', $618 = 'Sugar_U2', $619 = 'Sugar_U3', $620 = 'Sugar_U4', $621 = 'Sugar_U5', $622 = 'Sugar_U6', $623 = 'Sugar_U7', $624 = 'Sugar_U8', $625 = 'Sugar_U9', $626 = 'Sugar_V0', $627 = 'Sugar_V1', $628 = 'Sugar_V2', $629 = 'Sugar_V3', $630 = 'Sugar_V4', $631 = 'Sugar_V5', $632 = 'Sugar_V6', $633 = 'Sugar_V7', $634 = 'Sugar_V8', $635 = 'Sugar_V9', $636 = 'Sugar_X0', $637 = 'Sugar_X1', $638 = 'Sugar_X2', $639 = 'Sugar_X3', $640 = 'Sugar_X4', $641 = 'Sugar_X5', $642 = 'Sugar_X6', $643 = 'Sugar_X7', $644 = 'Sugar_X8', $645 = 'Sugar_X9', $646 = 'Sugar_Z0', $647 = 'Sugar_Z1', $648 = 'Sugar_Z2', $649 = 'Sugar_Z3', $650 = 'Sugar_Z4', $651 = 'Sugar_Z5', $652 = 'Sugar_Z6', $653 = 'Sugar_Z7', $654 = 'Sugar_Z8', $655 = 'Sugar_Z9', $656 = 'UK100', $657 = 'US2000', $658 = 'US30', $659 = 'US500', $660 = 'USDCAD', $661 = 'USDCHF', $662 = 'USDCNH', $663 = 'USDCZK', $664 = 'USDDKK', $665 = 'USDHKD', $666 = 'USDHUF', $667 = 'USDJPY', $668 = 'USDMXN', $669 = 'USDNOK', $670 = 'USDPLN', $671 = 'USDRUB', $672 = 'USDSEK', $673 = 'USDSGD', $674 = 'USDTHB', $675 = 'USDTRY', $676 = 'USDZAR', $677 = 'USTEC', $678 = 'WTI_F0', $679 = 'WTI_F1', $680 = 'WTI_F2', $681 = 'WTI_F3', $682 = 'WTI_F4', $683 = 'WTI_F5', $684 = 'WTI_F6', $685 = 'WTI_F7', $686 = 'WTI_F8', $687 = 'WTI_F9', $688 = 'WTI_G0', $689 = 'WTI_G1', $690 = 'WTI_G2', $691 = 'WTI_G3', $692 = 'WTI_G4', $693 = 'WTI_G5', $694 = 'WTI_G6', $695 = 'WTI_G7', $696 = 'WTI_G8', $697 = 'WTI_G9', $698 = 'WTI_H0', $699 = 'WTI_H1', $700 = 'WTI_H2', $701 = 'WTI_H3', $702 = 'WTI_H4', $703 = 'WTI_H5', $704 = 'WTI_H6', $705 = 'WTI_H7', $706 = 'WTI_H8', $707 = 'WTI_H9', $708 = 'WTI_J0', $709 = 'WTI_J1', $710 = 'WTI_J2', $711 = 'WTI_J3', $712 = 'WTI_J4', $713 = 'WTI_J5', $714 = 'WTI_J6', $715 = 'WTI_J7', $716 = 'WTI_J8', $717 = 'WTI_J9', $718 = 'WTI_K0', $719 = 'WTI_K1', $720 = 'WTI_K2', $721 = 'WTI_K3', $722 = 'WTI_K4', $723 = 'WTI_K5', $724 = 'WTI_K6', $725 = 'WTI_K7', $726 = 'WTI_K8', $727 = 'WTI_K9', $728 = 'WTI_M0', $729 = 'WTI_M1', $730 = 'WTI_M2', $731 = 'WTI_M3', $732 = 'WTI_M4', $733 = 'WTI_M5', $734 = 'WTI_M6', $735 = 'WTI_M7', $736 = 'WTI_M8', $737 = 'WTI_M9', $738 = 'WTI_N0', $739 = 'WTI_N1', $740 = 'WTI_N2', $741 = 'WTI_N3', $742 = 'WTI_N4', $743 = 'WTI_N5', $744 = 'WTI_N6', $745 = 'WTI_N7', $746 = 'WTI_N8', $747 = 'WTI_N9', $748 = 'WTI_Q0', $749 = 'WTI_Q1', $750 = 'WTI_Q2', $751 = 'WTI_Q3', $752 = 'WTI_Q4', $753 = 'WTI_Q5', $754 = 'WTI_Q6', $755 = 'WTI_Q7', $756 = 'WTI_Q8', $757 = 'WTI_Q9', $758 = 'WTI_U0', $759 = 'WTI_U1', $760 = 'WTI_U2', $761 = 'WTI_U3', $762 = 'WTI_U4', $763 = 'WTI_U5', $764 = 'WTI_U6', $765 = 'WTI_U7', $766 = 'WTI_U8', $767 = 'WTI_U9', $768 = 'WTI_V0', $769 = 'WTI_V1', $770 = 'WTI_V2', $771 = 'WTI_V3', $772 = 'WTI_V4', $773 = 'WTI_V5', $774 = 'WTI_V6', $775 = 'WTI_V7', $776 = 'WTI_V8', $777 = 'WTI_V9', $778 = 'WTI_X0', $779 = 'WTI_X1', $780 = 'WTI_X2', $781 = 'WTI_X3', $782 = 'WTI_X4', $783 = 'WTI_X5', $784 = 'WTI_X6', $785 = 'WTI_X7', $786 = 'WTI_X8', $787 = 'WTI_X9', $788 = 'WTI_Z0', $789 = 'WTI_Z1', $790 = 'WTI_Z2', $791 = 'WTI_Z3', $792 = 'WTI_Z4', $793 = 'WTI_Z5', $794 = 'WTI_Z6', $795 = 'WTI_Z7', $796 = 'WTI_Z8', $797 = 'WTI_Z9', $798 = 'Wheat_F0', $799 = 'Wheat_F1', $800 = 'Wheat_F2', $801 = 'Wheat_F3', $802 = 'Wheat_F4', $803 = 'Wheat_F5', $804 = 'Wheat_F6', $805 = 'Wheat_F7', $806 = 'Wheat_F8', $807 = 'Wheat_F9', $808 = 'Wheat_G0', $809 = 'Wheat_G1', $810 = 'Wheat_G2', $811 = 'Wheat_G3', $812 = 'Wheat_G4', $813 = 'Wheat_G5', $814 = 'Wheat_G6', $815 = 'Wheat_G7', $816 = 'Wheat_G8', $817 = 'Wheat_G9', $818 = 'Wheat_H0', $819 = 'Wheat_H1', $820 = 'Wheat_H2', $821 = 'Wheat_H3', $822 = 'Wheat_H4', $823 = 'Wheat_H5', $824 = 'Wheat_H6', $825 = 'Wheat_H7', $826 = 'Wheat_H8', $827 = 'Wheat_H9', $828 = 'Wheat_J0', $829 = 'Wheat_J1', $830 = 'Wheat_J2', $831 = 'Wheat_J3', $832 = 'Wheat_J4', $833 = 'Wheat_J5', $834 = 'Wheat_J6', $835 = 'Wheat_J7', $836 = 'Wheat_J8', $837 = 'Wheat_J9', $838 = 'Wheat_K0', $839 = 'Wheat_K1', $840 = 'Wheat_K2', $841 = 'Wheat_K3', $842 = 'Wheat_K4', $843 = 'Wheat_K5', $844 = 'Wheat_K6', $845 = 'Wheat_K7', $846 = 'Wheat_K8', $847 = 'Wheat_K9', $848 = 'Wheat_M0', $849 = 'Wheat_M1', $850 = 'Wheat_M2', $851 = 'Wheat_M3', $852 = 'Wheat_M4', $853 = 'Wheat_M5', $854 = 'Wheat_M6', $855 = 'Wheat_M7', $856 = 'Wheat_M8', $857 = 'Wheat_M9', $858 = 'Wheat_N0', $859 = 'Wheat_N1', $860 = 'Wheat_N2', $861 = 'Wheat_N3', $862 = 'Wheat_N4', $863 = 'Wheat_N5', $864 = 'Wheat_N6', $865 = 'Wheat_N7', $866 = 'Wheat_N8', $867 = 'Wheat_N9', $868 = 'Wheat_Q0', $869 = 'Wheat_Q1', $870 = 'Wheat_Q2', $871 = 'Wheat_Q3', $872 = 'Wheat_Q4', $873 = 'Wheat_Q5', $874 = 'Wheat_Q6', $875 = 'Wheat_Q7', $876 = 'Wheat_Q8', $877 = 'Wheat_Q9', $878 = 'Wheat_U0', $879 = 'Wheat_U1', $880 = 'Wheat_U2', $881 = 'Wheat_U3', $882 = 'Wheat_U4', $883 = 'Wheat_U5', $884 = 'Wheat_U6', $885 = 'Wheat_U7', $886 = 'Wheat_U8', $887 = 'Wheat_U9', $888 = 'Wheat_V0', $889 = 'Wheat_V1', $890 = 'Wheat_V2', $891 = 'Wheat_V3', $892 = 'Wheat_V4', $893 = 'Wheat_V5', $894 = 'Wheat_V6', $895 = 'Wheat_V7', $896 = 'Wheat_V8', $897 = 'Wheat_V9', $898 = 'Wheat_X0', $899 = 'Wheat_X1', $900 = 'Wheat_X2', $901 = 'Wheat_X3', $902 = 'Wheat_X4', $903 = 'Wheat_X5', $904 = 'Wheat_X6', $905 = 'Wheat_X7', $906 = 'Wheat_X8', $907 = 'Wheat_X9', $908 = 'Wheat_Z0', $909 = 'Wheat_Z1', $910 = 'Wheat_Z2', $911 = 'Wheat_Z3', $912 = 'Wheat_Z4', $913 = 'Wheat_Z5', $914 = 'Wheat_Z6', $915 = 'Wheat_Z7', $916 = 'Wheat_Z8', $917 = 'Wheat_Z9', $918 = 'XAGEUR', $919 = 'XAGUSD', $920 = 'XAUEUR', $921 = 'XAUUSD', $922 = 'XBRUSD', $923 = 'XNGUSD', $924 = 'XPDUSD', $925 = 'XPTUSD', $926 = 'XTIUSD', $927 = 'AUDCAD', $928 = 'AUDCHF', $929 = 'AUDJPY', $930 = 'AUDNZD', $931 = 'AUDSGD', $932 = 'AUDUSD', $933 = 'AUS200', $934 = 'BRENT_F0', $935 = 'BRENT_F1', $936 = 'BRENT_F2', $937 = 'BRENT_F3', $938 = 'BRENT_F4', $939 = 'BRENT_F5', $940 = 'BRENT_F6', $941 = 'BRENT_F7', $942 = 'BRENT_F8', $943 = 'BRENT_F9', $944 = 'BRENT_G0', $945 = 'BRENT_G1', $946 = 'BRENT_G2', $947 = 'BRENT_G3', $948 = 'BRENT_G4', $949 = 'BRENT_G5', $950 = 'BRENT_G6', $951 = 'BRENT_G7', $952 = 'BRENT_G8', $953 = 'BRENT_G9', $954 = 'BRENT_H0', $955 = 'BRENT_H1', $956 = 'BRENT_H2', $957 = 'BRENT_H3', $958 = 'BRENT_H4', $959 = 'BRENT_H5', $960 = 'BRENT_H6', $961 = 'BRENT_H7', $962 = 'BRENT_H8', $963 = 'BRENT_H9', $964 = 'BRENT_J0', $965 = 'BRENT_J1', $966 = 'BRENT_J2', $967 = 'BRENT_J3', $968 = 'BRENT_J4', $969 = 'BRENT_J5', $970 = 'BRENT_J6', $971 = 'BRENT_J7', $972 = 'BRENT_J8', $973 = 'BRENT_J9', $974 = 'BRENT_K0', $975 = 'BRENT_K1', $976 = 'BRENT_K2', $977 = 'BRENT_K3', $978 = 'BRENT_K4', $979 = 'BRENT_K5', $980 = 'BRENT_K6', $981 = 'BRENT_K7', $982 = 'BRENT_K8', $983 = 'BRENT_K9', $984 = 'BRENT_M0', $985 = 'BRENT_M1', $986 = 'BRENT_M2', $987 = 'BRENT_M3', $988 = 'BRENT_M4', $989 = 'BRENT_M5', $990 = 'BRENT_M6', $991 = 'BRENT_M7', $992 = 'BRENT_M8', $993 = 'BRENT_M9', $994 = 'BRENT_N0', $995 = 'BRENT_N1', $996 = 'BRENT_N2', $997 = 'BRENT_N3', $998 = 'BRENT_N4', $999 = 'BRENT_N5', $1000 = 'BRENT_N6', $1001 = 'BRENT_N7', $1002 = 'BRENT_N8', $1003 = 'BRENT_N9', $1004 = 'BRENT_Q0', $1005 = 'BRENT_Q1', $1006 = 'BRENT_Q2', $1007 = 'BRENT_Q3', $1008 = 'BRENT_Q4', $1009 = 'BRENT_Q5', $1010 = 'BRENT_Q6', $1011 = 'BRENT_Q7', $1012 = 'BRENT_Q8', $1013 = 'BRENT_Q9', $1014 = 'BRENT_U0', $1015 = 'BRENT_U1', $1016 = 'BRENT_U2', $1017 = 'BRENT_U3', $1018 = 'BRENT_U4', $1019 = 'BRENT_U5', $1020 = 'BRENT_U6', $1021 = 'BRENT_U7', $1022 = 'BRENT_U8', $1023 = 'BRENT_U9', $1024 = 'BRENT_V0', $1025 = 'BRENT_V1', $1026 = 'BRENT_V2', $1027 = 'BRENT_V3', $1028 = 'BRENT_V4', $1029 = 'BRENT_V5', $1030 = 'BRENT_V6', $1031 = 'BRENT_V7', $1032 = 'BRENT_V8', $1033 = 'BRENT_V9', $1034 = 'BRENT_X0', $1035 = 'BRENT_X1', $1036 = 'BRENT_X2', $1037 = 'BRENT_X3', $1038 = 'BRENT_X4', $1039 = 'BRENT_X5', $1040 = 'BRENT_X6', $1041 = 'BRENT_X7', $1042 = 'BRENT_X8', $1043 = 'BRENT_X9', $1044 = 'BRENT_Z0', $1045 = 'BRENT_Z1', $1046 = 'BRENT_Z2', $1047 = 'BRENT_Z3', $1048 = 'BRENT_Z4', $1049 = 'BRENT_Z5', $1050 = 'BRENT_Z6', $1051 = 'BRENT_Z7', $1052 = 'BRENT_Z8', $1053 = 'BRENT_Z9', $1054 = 'BTCUSD', $1055 = 'CADCHF', $1056 = 'CADJPY', $1057 = 'CHFJPY', $1058 = 'CHFSGD', $1059 = 'CHINA50', $1060 = 'Coffee_F0', $1061 = 'Coffee_F1', $1062 = 'Coffee_F2', $1063 = 'Coffee_F3', $1064 = 'Coffee_F4', $1065 = 'Coffee_F5', $1066 = 'Coffee_F6', $1067 = 'Coffee_F7', $1068 = 'Coffee_F8', $1069 = 'Coffee_F9', $1070 = 'Coffee_G0', $1071 = 'Coffee_G1', $1072 = 'Coffee_G2', $1073 = 'Coffee_G3', $1074 = 'Coffee_G4', $1075 = 'Coffee_G5', $1076 = 'Coffee_G6', $1077 = 'Coffee_G7', $1078 = 'Coffee_G8', $1079 = 'Coffee_G9', $1080 = 'Coffee_H0', $1081 = 'Coffee_H1', $1082 = 'Coffee_H2', $1083 = 'Coffee_H3', $1084 = 'Coffee_H4', $1085 = 'Coffee_H5', $1086 = 'Coffee_H6', $1087 = 'Coffee_H7', $1088 = 'Coffee_H8', $1089 = 'Coffee_H9', $1090 = 'Coffee_J0', $1091 = 'Coffee_J1', $1092 = 'Coffee_J2', $1093 = 'Coffee_J3', $1094 = 'Coffee_J4', $1095 = 'Coffee_J5', $1096 = 'Coffee_J6', $1097 = 'Coffee_J7', $1098 = 'Coffee_J8', $1099 = 'Coffee_J9', $1100 = 'Coffee_K0', $1101 = 'Coffee_K1', $1102 = 'Coffee_K2', $1103 = 'Coffee_K3', $1104 = 'Coffee_K4', $1105 = 'Coffee_K5', $1106 = 'Coffee_K6', $1107 = 'Coffee_K7', $1108 = 'Coffee_K8', $1109 = 'Coffee_K9', $1110 = 'Coffee_M0', $1111 = 'Coffee_M1', $1112 = 'Coffee_M2', $1113 = 'Coffee_M3', $1114 = 'Coffee_M4', $1115 = 'Coffee_M5', $1116 = 'Coffee_M6', $1117 = 'Coffee_M7', $1118 = 'Coffee_M8', $1119 = 'Coffee_M9', $1120 = 'Coffee_N0', $1121 = 'Coffee_N1', $1122 = 'Coffee_N2', $1123 = 'Coffee_N3', $1124 = 'Coffee_N4', $1125 = 'Coffee_N5', $1126 = 'Coffee_N6', $1127 = 'Coffee_N7', $1128 = 'Coffee_N8', $1129 = 'Coffee_N9', $1130 = 'Coffee_Q0', $1131 = 'Coffee_Q1', $1132 = 'Coffee_Q2', $1133 = 'Coffee_Q3', $1134 = 'Coffee_Q4', $1135 = 'Coffee_Q5', $1136 = 'Coffee_Q6', $1137 = 'Coffee_Q7', $1138 = 'Coffee_Q8', $1139 = 'Coffee_Q9', $1140 = 'Coffee_U0', $1141 = 'Coffee_U1', $1142 = 'Coffee_U2', $1143 = 'Coffee_U3', $1144 = 'Coffee_U4', $1145 = 'Coffee_U5', $1146 = 'Coffee_U6', $1147 = 'Coffee_U7', $1148 = 'Coffee_U8', $1149 = 'Coffee_U9', $1150 = 'Coffee_V0', $1151 = 'Coffee_V1', $1152 = 'Coffee_V2', $1153 = 'Coffee_V3', $1154 = 'Coffee_V4', $1155 = 'Coffee_V5', $1156 = 'Coffee_V6', $1157 = 'Coffee_V7', $1158 = 'Coffee_V8', $1159 = 'Coffee_V9', $1160 = 'Coffee_X0', $1161 = 'Coffee_X1', $1162 = 'Coffee_X2', $1163 = 'Coffee_X3', $1164 = 'Coffee_X4', $1165 = 'Coffee_X5', $1166 = 'Coffee_X6', $1167 = 'Coffee_X7', $1168 = 'Coffee_X8', $1169 = 'Coffee_X9', $1170 = 'Coffee_Z0', $1171 = 'Coffee_Z1', $1172 = 'Coffee_Z2', $1173 = 'Coffee_Z3', $1174 = 'Coffee_Z4', $1175 = 'Coffee_Z5', $1176 = 'Coffee_Z6', $1177 = 'Coffee_Z7', $1178 = 'Coffee_Z8', $1179 = 'Coffee_Z9', $1180 = 'Corn_F0', $1181 = 'Corn_F1', $1182 = 'Corn_F2', $1183 = 'Corn_F3', $1184 = 'Corn_F4', $1185 = 'Corn_F5', $1186 = 'Corn_F6', $1187 = 'Corn_F7', $1188 = 'Corn_F8', $1189 = 'Corn_F9', $1190 = 'Corn_G0', $1191 = 'Corn_G1', $1192 = 'Corn_G2', $1193 = 'Corn_G3', $1194 = 'Corn_G4', $1195 = 'Corn_G5', $1196 = 'Corn_G6', $1197 = 'Corn_G7', $1198 = 'Corn_G8', $1199 = 'Corn_G9', $1200 = 'Corn_H0', $1201 = 'Corn_H1', $1202 = 'Corn_H2', $1203 = 'Corn_H3', $1204 = 'Corn_H4', $1205 = 'Corn_H5', $1206 = 'Corn_H6', $1207 = 'Corn_H7', $1208 = 'Corn_H8', $1209 = 'Corn_H9', $1210 = 'Corn_J0', $1211 = 'Corn_J1', $1212 = 'Corn_J2', $1213 = 'Corn_J3', $1214 = 'Corn_J4', $1215 = 'Corn_J5', $1216 = 'Corn_J6', $1217 = 'Corn_J7', $1218 = 'Corn_J8', $1219 = 'Corn_J9', $1220 = 'Corn_K0', $1221 = 'Corn_K1', $1222 = 'Corn_K2', $1223 = 'Corn_K3', $1224 = 'Corn_K4', $1225 = 'Corn_K5', $1226 = 'Corn_K6', $1227 = 'Corn_K7', $1228 = 'Corn_K8', $1229 = 'Corn_K9', $1230 = 'Corn_M0', $1231 = 'Corn_M1', $1232 = 'Corn_M2', $1233 = 'Corn_M3', $1234 = 'Corn_M4', $1235 = 'Corn_M5', $1236 = 'Corn_M6', $1237 = 'Corn_M7', $1238 = 'Corn_M8', $1239 = 'Corn_M9', $1240 = 'Corn_N0', $1241 = 'Corn_N1', $1242 = 'Corn_N2', $1243 = 'Corn_N3', $1244 = 'Corn_N4', $1245 = 'Corn_N5', $1246 = 'Corn_N6', $1247 = 'Corn_N7', $1248 = 'Corn_N8', $1249 = 'Corn_N9', $1250 = 'Corn_Q0', $1251 = 'Corn_Q1', $1252 = 'Corn_Q2', $1253 = 'Corn_Q3', $1254 = 'Corn_Q4', $1255 = 'Corn_Q5', $1256 = 'Corn_Q6', $1257 = 'Corn_Q7', $1258 = 'Corn_Q8', $1259 = 'Corn_Q9', $1260 = 'Corn_U0', $1261 = 'Corn_U1', $1262 = 'Corn_U2', $1263 = 'Corn_U3', $1264 = 'Corn_U4', $1265 = 'Corn_U5', $1266 = 'Corn_U6', $1267 = 'Corn_U7', $1268 = 'Corn_U8', $1269 = 'Corn_U9', $1270 = 'Corn_V0', $1271 = 'Corn_V1', $1272 = 'Corn_V2', $1273 = 'Corn_V3', $1274 = 'Corn_V4', $1275 = 'Corn_V5', $1276 = 'Corn_V6', $1277 = 'Corn_V7', $1278 = 'Corn_V8', $1279 = 'Corn_V9', $1280 = 'Corn_X0', $1281 = 'Corn_X1', $1282 = 'Corn_X2', $1283 = 'Corn_X3', $1284 = 'Corn_X4', $1285 = 'Corn_X5', $1286 = 'Corn_X6', $1287 = 'Corn_X7', $1288 = 'Corn_X8', $1289 = 'Corn_X9', $1290 = 'Corn_Z0', $1291 = 'Corn_Z1', $1292 = 'Corn_Z2', $1293 = 'Corn_Z3', $1294 = 'Corn_Z4', $1295 = 'Corn_Z5', $1296 = 'Corn_Z6', $1297 = 'Corn_Z7', $1298 = 'Corn_Z8', $1299 = 'Corn_Z9', $1300 = 'DE30', $1301 = 'ES35', $1302 = 'EURAUD', $1303 = 'EURCAD', $1304 = 'EURCHF', $1305 = 'EURDKK', $1306 = 'EURGBP', $1307 = 'EURHKD', $1308 = 'EURJPY', $1309 = 'EURNOK', $1310 = 'EURNZD', $1311 = 'EURPLN', $1312 = 'EURSEK', $1313 = 'EURSGD', $1314 = 'EURTRY', $1315 = 'EURUSD', $1316 = 'EURZAR', $1317 = 'F40', $1318 = 'GBPAUD', $1319 = 'GBPCAD', $1320 = 'GBPCHF', $1321 = 'GBPDKK', $1322 = 'GBPJPY', $1323 = 'GBPNOK', $1324 = 'GBPNZD', $1325 = 'GBPSEK', $1326 = 'GBPSGD', $1327 = 'GBPUSD', $1328 = 'HK50', $1329 = 'IT40', $1330 = 'JP225', $1331 = 'NOKJPY', $1332 = 'NOKSEK', $1333 = 'NZDCAD', $1334 = 'NZDCHF', $1335 = 'NZDJPY', $1336 = 'NZDUSD', $1337 = 'SEKJPY', $1338 = 'SGDJPY', $1339 = 'STOXX50', $1340 = 'Soybean_F0', $1341 = 'Soybean_F1', $1342 = 'Soybean_F2', $1343 = 'Soybean_F3', $1344 = 'Soybean_F4', $1345 = 'Soybean_F5', $1346 = 'Soybean_F6', $1347 = 'Soybean_F7', $1348 = 'Soybean_F8', $1349 = 'Soybean_F9', $1350 = 'Soybean_G0', $1351 = 'Soybean_G1', $1352 = 'Soybean_G2', $1353 = 'Soybean_G3', $1354 = 'Soybean_G4', $1355 = 'Soybean_G5', $1356 = 'Soybean_G6', $1357 = 'Soybean_G7', $1358 = 'Soybean_G8', $1359 = 'Soybean_G9', $1360 = 'Soybean_H0', $1361 = 'Soybean_H1', $1362 = 'Soybean_H2', $1363 = 'Soybean_H3', $1364 = 'Soybean_H4', $1365 = 'Soybean_H5', $1366 = 'Soybean_H6', $1367 = 'Soybean_H7', $1368 = 'Soybean_H8', $1369 = 'Soybean_H9', $1370 = 'Soybean_J0', $1371 = 'Soybean_J1', $1372 = 'Soybean_J2', $1373 = 'Soybean_J3', $1374 = 'Soybean_J4', $1375 = 'Soybean_J5', $1376 = 'Soybean_J6', $1377 = 'Soybean_J7', $1378 = 'Soybean_J8', $1379 = 'Soybean_J9', $1380 = 'Soybean_K0', $1381 = 'Soybean_K1', $1382 = 'Soybean_K2', $1383 = 'Soybean_K3', $1384 = 'Soybean_K4', $1385 = 'Soybean_K5', $1386 = 'Soybean_K6', $1387 = 'Soybean_K7', $1388 = 'Soybean_K8', $1389 = 'Soybean_K9', $1390 = 'Soybean_M0', $1391 = 'Soybean_M1', $1392 = 'Soybean_M2', $1393 = 'Soybean_M3', $1394 = 'Soybean_M4', $1395 = 'Soybean_M5', $1396 = 'Soybean_M6', $1397 = 'Soybean_M7', $1398 = 'Soybean_M8', $1399 = 'Soybean_M9', $1400 = 'Soybean_N0', $1401 = 'Soybean_N1', $1402 = 'Soybean_N2', $1403 = 'Soybean_N3', $1404 = 'Soybean_N4', $1405 = 'Soybean_N5', $1406 = 'Soybean_N6', $1407 = 'Soybean_N7', $1408 = 'Soybean_N8', $1409 = 'Soybean_N9', $1410 = 'Soybean_Q0', $1411 = 'Soybean_Q1', $1412 = 'Soybean_Q2', $1413 = 'Soybean_Q3', $1414 = 'Soybean_Q4', $1415 = 'Soybean_Q5', $1416 = 'Soybean_Q6', $1417 = 'Soybean_Q7', $1418 = 'Soybean_Q8', $1419 = 'Soybean_Q9', $1420 = 'Soybean_U0', $1421 = 'Soybean_U1', $1422 = 'Soybean_U2', $1423 = 'Soybean_U3', $1424 = 'Soybean_U4', $1425 = 'Soybean_U5', $1426 = 'Soybean_U6', $1427 = 'Soybean_U7', $1428 = 'Soybean_U8', $1429 = 'Soybean_U9', $1430 = 'Soybean_V0', $1431 = 'Soybean_V1', $1432 = 'Soybean_V2', $1433 = 'Soybean_V3', $1434 = 'Soybean_V4', $1435 = 'Soybean_V5', $1436 = 'Soybean_V6', $1437 = 'Soybean_V7', $1438 = 'Soybean_V8', $1439 = 'Soybean_V9', $1440 = 'Soybean_X0', $1441 = 'Soybean_X1', $1442 = 'Soybean_X2', $1443 = 'Soybean_X3', $1444 = 'Soybean_X4', $1445 = 'Soybean_X5', $1446 = 'Soybean_X6', $1447 = 'Soybean_X7', $1448 = 'Soybean_X8', $1449 = 'Soybean_X9', $1450 = 'Soybean_Z0', $1451 = 'Soybean_Z1', $1452 = 'Soybean_Z2', $1453 = 'Soybean_Z3', $1454 = 'Soybean_Z4', $1455 = 'Soybean_Z5', $1456 = 'Soybean_Z6', $1457 = 'Soybean_Z7', $1458 = 'Soybean_Z8', $1459 = 'Soybean_Z9', $1460 = 'Sugar_F0', $1461 = 'Sugar_F1', $1462 = 'Sugar_F2', $1463 = 'Sugar_F3', $1464 = 'Sugar_F4', $1465 = 'Sugar_F5', $1466 = 'Sugar_F6', $1467 = 'Sugar_F7', $1468 = 'Sugar_F8', $1469 = 'Sugar_F9', $1470 = 'Sugar_G0', $1471 = 'Sugar_G1', $1472 = 'Sugar_G2', $1473 = 'Sugar_G3', $1474 = 'Sugar_G4', $1475 = 'Sugar_G5', $1476 = 'Sugar_G6', $1477 = 'Sugar_G7', $1478 = 'Sugar_G8', $1479 = 'Sugar_G9', $1480 = 'Sugar_H0', $1481 = 'Sugar_H1', $1482 = 'Sugar_H2', $1483 = 'Sugar_H3', $1484 = 'Sugar_H4', $1485 = 'Sugar_H5', $1486 = 'Sugar_H6', $1487 = 'Sugar_H7', $1488 = 'Sugar_H8', $1489 = 'Sugar_H9', $1490 = 'Sugar_J0', $1491 = 'Sugar_J1', $1492 = 'Sugar_J2', $1493 = 'Sugar_J3', $1494 = 'Sugar_J4', $1495 = 'Sugar_J5', $1496 = 'Sugar_J6', $1497 = 'Sugar_J7', $1498 = 'Sugar_J8', $1499 = 'Sugar_J9', $1500 = 'Sugar_K0', $1501 = 'Sugar_K1', $1502 = 'Sugar_K2', $1503 = 'Sugar_K3', $1504 = 'Sugar_K4', $1505 = 'Sugar_K5', $1506 = 'Sugar_K6', $1507 = 'Sugar_K7', $1508 = 'Sugar_K8', $1509 = 'Sugar_K9', $1510 = 'Sugar_M0', $1511 = 'Sugar_M1', $1512 = 'Sugar_M2', $1513 = 'Sugar_M3', $1514 = 'Sugar_M4', $1515 = 'Sugar_M5', $1516 = 'Sugar_M6', $1517 = 'Sugar_M7', $1518 = 'Sugar_M8', $1519 = 'Sugar_M9', $1520 = 'Sugar_N0', $1521 = 'Sugar_N1', $1522 = 'Sugar_N2', $1523 = 'Sugar_N3', $1524 = 'Sugar_N4', $1525 = 'Sugar_N5', $1526 = 'Sugar_N6', $1527 = 'Sugar_N7', $1528 = 'Sugar_N8', $1529 = 'Sugar_N9', $1530 = 'Sugar_Q0', $1531 = 'Sugar_Q1', $1532 = 'Sugar_Q2', $1533 = 'Sugar_Q3', $1534 = 'Sugar_Q4', $1535 = 'Sugar_Q5', $1536 = 'Sugar_Q6', $1537 = 'Sugar_Q7', $1538 = 'Sugar_Q8', $1539 = 'Sugar_Q9', $1540 = 'Sugar_U0', $1541 = 'Sugar_U1', $1542 = 'Sugar_U2', $1543 = 'Sugar_U3', $1544 = 'Sugar_U4', $1545 = 'Sugar_U5', $1546 = 'Sugar_U6', $1547 = 'Sugar_U7', $1548 = 'Sugar_U8', $1549 = 'Sugar_U9', $1550 = 'Sugar_V0', $1551 = 'Sugar_V1', $1552 = 'Sugar_V2', $1553 = 'Sugar_V3', $1554 = 'Sugar_V4', $1555 = 'Sugar_V5', $1556 = 'Sugar_V6', $1557 = 'Sugar_V7', $1558 = 'Sugar_V8', $1559 = 'Sugar_V9', $1560 = 'Sugar_X0', $1561 = 'Sugar_X1', $1562 = 'Sugar_X2', $1563 = 'Sugar_X3', $1564 = 'Sugar_X4', $1565 = 'Sugar_X5', $1566 = 'Sugar_X6', $1567 = 'Sugar_X7', $1568 = 'Sugar_X8', $1569 = 'Sugar_X9', $1570 = 'Sugar_Z0', $1571 = 'Sugar_Z1', $1572 = 'Sugar_Z2', $1573 = 'Sugar_Z3', $1574 = 'Sugar_Z4', $1575 = 'Sugar_Z5', $1576 = 'Sugar_Z6', $1577 = 'Sugar_Z7', $1578 = 'Sugar_Z8', $1579 = 'Sugar_Z9', $1580 = 'UK100', $1581 = 'US2000', $1582 = 'US30', $1583 = 'US500', $1584 = 'USDCAD', $1585 = 'USDCHF', $1586 = 'USDCNH', $1587 = 'USDCZK', $1588 = 'USDDKK', $1589 = 'USDHKD', $1590 = 'USDHUF', $1591 = 'USDJPY', $1592 = 'USDMXN', $1593 = 'USDNOK', $1594 = 'USDPLN', $1595 = 'USDRUB', $1596 = 'USDSEK', $1597 = 'USDSGD', $1598 = 'USDTHB', $1599 = 'USDTRY', $1600 = 'USDZAR', $1601 = 'USTEC', $1602 = 'WTI_F0', $1603 = 'WTI_F1', $1604 = 'WTI_F2', $1605 = 'WTI_F3', $1606 = 'WTI_F4', $1607 = 'WTI_F5', $1608 = 'WTI_F6', $1609 = 'WTI_F7', $1610 = 'WTI_F8', $1611 = 'WTI_F9', $1612 = 'WTI_G0', $1613 = 'WTI_G1', $1614 = 'WTI_G2', $1615 = 'WTI_G3', $1616 = 'WTI_G4', $1617 = 'WTI_G5', $1618 = 'WTI_G6', $1619 = 'WTI_G7', $1620 = 'WTI_G8', $1621 = 'WTI_G9', $1622 = 'WTI_H0', $1623 = 'WTI_H1', $1624 = 'WTI_H2', $1625 = 'WTI_H3', $1626 = 'WTI_H4', $1627 = 'WTI_H5', $1628 = 'WTI_H6', $1629 = 'WTI_H7', $1630 = 'WTI_H8', $1631 = 'WTI_H9', $1632 = 'WTI_J0', $1633 = 'WTI_J1', $1634 = 'WTI_J2', $1635 = 'WTI_J3', $1636 = 'WTI_J4', $1637 = 'WTI_J5', $1638 = 'WTI_J6', $1639 = 'WTI_J7', $1640 = 'WTI_J8', $1641 = 'WTI_J9', $1642 = 'WTI_K0', $1643 = 'WTI_K1', $1644 = 'WTI_K2', $1645 = 'WTI_K3', $1646 = 'WTI_K4', $1647 = 'WTI_K5', $1648 = 'WTI_K6', $1649 = 'WTI_K7', $1650 = 'WTI_K8', $1651 = 'WTI_K9', $1652 = 'WTI_M0', $1653 = 'WTI_M1', $1654 = 'WTI_M2', $1655 = 'WTI_M3', $1656 = 'WTI_M4', $1657 = 'WTI_M5', $1658 = 'WTI_M6', $1659 = 'WTI_M7', $1660 = 'WTI_M8', $1661 = 'WTI_M9', $1662 = 'WTI_N0', $1663 = 'WTI_N1', $1664 = 'WTI_N2', $1665 = 'WTI_N3', $1666 = 'WTI_N4', $1667 = 'WTI_N5', $1668 = 'WTI_N6', $1669 = 'WTI_N7', $1670 = 'WTI_N8', $1671 = 'WTI_N9', $1672 = 'WTI_Q0', $1673 = 'WTI_Q1', $1674 = 'WTI_Q2', $1675 = 'WTI_Q3', $1676 = 'WTI_Q4', $1677 = 'WTI_Q5', $1678 = 'WTI_Q6', $1679 = 'WTI_Q7', $1680 = 'WTI_Q8', $1681 = 'WTI_Q9', $1682 = 'WTI_U0', $1683 = 'WTI_U1', $1684 = 'WTI_U2', $1685 = 'WTI_U3', $1686 = 'WTI_U4', $1687 = 'WTI_U5', $1688 = 'WTI_U6', $1689 = 'WTI_U7', $1690 = 'WTI_U8', $1691 = 'WTI_U9', $1692 = 'WTI_V0', $1693 = 'WTI_V1', $1694 = 'WTI_V2', $1695 = 'WTI_V3', $1696 = 'WTI_V4', $1697 = 'WTI_V5', $1698 = 'WTI_V6', $1699 = 'WTI_V7', $1700 = 'WTI_V8', $1701 = 'WTI_V9', $1702 = 'WTI_X0', $1703 = 'WTI_X1', $1704 = 'WTI_X2', $1705 = 'WTI_X3', $1706 = 'WTI_X4', $1707 = 'WTI_X5', $1708 = 'WTI_X6', $1709 = 'WTI_X7', $1710 = 'WTI_X8', $1711 = 'WTI_X9', $1712 = 'WTI_Z0', $1713 = 'WTI_Z1', $1714 = 'WTI_Z2', $1715 = 'WTI_Z3', $1716 = 'WTI_Z4', $1717 = 'WTI_Z5', $1718 = 'WTI_Z6', $1719 = 'WTI_Z7', $1720 = 'WTI_Z8', $1721 = 'WTI_Z9', $1722 = 'Wheat_F0', $1723 = 'Wheat_F1', $1724 = 'Wheat_F2', $1725 = 'Wheat_F3', $1726 = 'Wheat_F4', $1727 = 'Wheat_F5', $1728 = 'Wheat_F6', $1729 = 'Wheat_F7', $1730 = 'Wheat_F8', $1731 = 'Wheat_F9', $1732 = 'Wheat_G0', $1733 = 'Wheat_G1', $1734 = 'Wheat_G2', $1735 = 'Wheat_G3', $1736 = 'Wheat_G4', $1737 = 'Wheat_G5', $1738 = 'Wheat_G6', $1739 = 'Wheat_G7', $1740 = 'Wheat_G8', $1741 = 'Wheat_G9', $1742 = 'Wheat_H0', $1743 = 'Wheat_H1', $1744 = 'Wheat_H2', $1745 = 'Wheat_H3', $1746 = 'Wheat_H4', $1747 = 'Wheat_H5', $1748 = 'Wheat_H6', $1749 = 'Wheat_H7', $1750 = 'Wheat_H8', $1751 = 'Wheat_H9', $1752 = 'Wheat_J0', $1753 = 'Wheat_J1', $1754 = 'Wheat_J2', $1755 = 'Wheat_J3', $1756 = 'Wheat_J4', $1757 = 'Wheat_J5', $1758 = 'Wheat_J6', $1759 = 'Wheat_J7', $1760 = 'Wheat_J8', $1761 = 'Wheat_J9', $1762 = 'Wheat_K0', $1763 = 'Wheat_K1', $1764 = 'Wheat_K2', $1765 = 'Wheat_K3', $1766 = 'Wheat_K4', $1767 = 'Wheat_K5', $1768 = 'Wheat_K6', $1769 = 'Wheat_K7', $1770 = 'Wheat_K8', $1771 = 'Wheat_K9', $1772 = 'Wheat_M0', $1773 = 'Wheat_M1', $1774 = 'Wheat_M2', $1775 = 'Wheat_M3', $1776 = 'Wheat_M4', $1777 = 'Wheat_M5', $1778 = 'Wheat_M6', $1779 = 'Wheat_M7', $1780 = 'Wheat_M8', $1781 = 'Wheat_M9', $1782 = 'Wheat_N0', $1783 = 'Wheat_N1', $1784 = 'Wheat_N2', $1785 = 'Wheat_N3', $1786 = 'Wheat_N4', $1787 = 'Wheat_N5', $1788 = 'Wheat_N6', $1789 = 'Wheat_N7', $1790 = 'Wheat_N8', $1791 = 'Wheat_N9', $1792 = 'Wheat_Q0', $1793 = 'Wheat_Q1', $1794 = 'Wheat_Q2', $1795 = 'Wheat_Q3', $1796 = 'Wheat_Q4', $1797 = 'Wheat_Q5', $1798 = 'Wheat_Q6', $1799 = 'Wheat_Q7', $1800 = 'Wheat_Q8', $1801 = 'Wheat_Q9', $1802 = 'Wheat_U0', $1803 = 'Wheat_U1', $1804 = 'Wheat_U2', $1805 = 'Wheat_U3', $1806 = 'Wheat_U4', $1807 = 'Wheat_U5', $1808 = 'Wheat_U6', $1809 = 'Wheat_U7', $1810 = 'Wheat_U8', $1811 = 'Wheat_U9', $1812 = 'Wheat_V0', $1813 = 'Wheat_V1', $1814 = 'Wheat_V2', $1815 = 'Wheat_V3', $1816 = 'Wheat_V4', $1817 = 'Wheat_V5', $1818 = 'Wheat_V6', $1819 = 'Wheat_V7', $1820 = 'Wheat_V8', $1821 = 'Wheat_V9', $1822 = 'Wheat_X0', $1823 = 'Wheat_X1', $1824 = 'Wheat_X2', $1825 = 'Wheat_X3', $1826 = 'Wheat_X4', $1827 = 'Wheat_X5', $1828 = 'Wheat_X6', $1829 = 'Wheat_X7', $1830 = 'Wheat_X8', $1831 = 'Wheat_X9', $1832 = 'Wheat_Z0', $1833 = 'Wheat_Z1', $1834 = 'Wheat_Z2', $1835 = 'Wheat_Z3', $1836 = 'Wheat_Z4', $1837 = 'Wheat_Z5', $1838 = 'Wheat_Z6', $1839 = 'Wheat_Z7', $1840 = 'Wheat_Z8', $1841 = 'Wheat_Z9', $1842 = 'XAGEUR', $1843 = 'XAGUSD', $1844 = 'XAUEUR', $1845 = 'XAUUSD', $1846 = 'XBRUSD', $1847 = 'XNGUSD', $1848 = 'XPDUSD', $1849 = 'XPTUSD', $1850 = 'XTIUSD'
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-03-05 13:16:10 Duration: 33ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.248 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'
11 301ms 3,418 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 #11
Day Hour Count Duration Avg duration 13 3,418 301ms 0ms [ User: postgres - Total duration: 2s88ms - Times executed: 3418 ]
[ Application: [unknown] - Total duration: 2s88ms - Times executed: 3418 ]
-
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: 2025-03-05 13:30:59 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-03-05 13:00:00', $2 = '1410.29', $3 = '1411.89', $4 = '1409.66', $5 = '1411.89', $6 = '112', $7 = '515840247175848300', $8 = '0', $9 = '2025-03-05 13:30:59.21', $10 = '2025-03-05 13:30:59.21', $11 = '1410.29', $12 = '1411.89', $13 = '1409.66', $14 = '1411.89', $15 = '112', $16 = '0', $17 = '2025-03-05 13:30:59.21', $18 = '2025-03-05 13:30:59.21'
-
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: 2025-03-05 13:41:57 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-03-05 13:00:00', $2 = '5812.25', $3 = '5813.75', $4 = '5807.75', $5 = '5809.87', $6 = '1572', $7 = '515840248032224300', $8 = '0', $9 = '2025-03-05 13:41:57.53', $10 = '2025-03-05 13:41:57.448', $11 = '5812.25', $12 = '5813.75', $13 = '5807.75', $14 = '5809.87', $15 = '1572', $16 = '0', $17 = '2025-03-05 13:41:57.53', $18 = '2025-03-05 13:41:57.448'
-
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: 2025-03-05 13:41:59 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-03-05 13:00:00', $2 = '42743.9', $3 = '42768.65', $4 = '42728.9', $5 = '42738.65', $6 = '2496', $7 = '515840248000726300', $8 = '0', $9 = '2025-03-05 13:41:59.512', $10 = '2025-03-05 13:41:59.476', $11 = '42743.9', $12 = '42768.65', $13 = '42728.9', $14 = '42738.65', $15 = '2496', $16 = '0', $17 = '2025-03-05 13:41:59.512', $18 = '2025-03-05 13:41:59.476'
12 262ms 8 27ms 43ms 32ms with sym_info as ( ;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 13 8 262ms 32ms [ User: postgres - Total duration: 26s717ms - Times executed: 8 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 26s717ms - Times executed: 8 ]
-
with sym_info as ( ;
Date: 2025-03-05 13:06:50 Duration: 43ms 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: 2025-03-05 13:06:43 Duration: 38ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
-
with sym_info as ( ;
Date: 2025-03-05 13:51:47 Duration: 36ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
13 208ms 2,184 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 2,184 208ms 0ms [ User: postgres - Total duration: 1s98ms - Times executed: 2184 ]
[ Application: [unknown] - Total duration: 1s98ms - Times executed: 2184 ]
-
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: 2025-03-05 13:01:15 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-03-05 13:00:00', $2 = '0.2023285', $3 = '0.20662', $4 = '0.2018825', $5 = '0.20477', $6 = '22018', $7 = '515840249471575300', $8 = '0', $9 = '2025-03-05 13:01:15.187', $10 = '2025-03-05 13:01:15.186', $11 = '0.2023285', $12 = '0.20662', $13 = '0.2018825', $14 = '0.20477', $15 = '22018', $16 = '0', $17 = '2025-03-05 13:01:15.187', $18 = '2025-03-05 13:01:15.186'
-
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: 2025-03-05 13:11:39 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-03-04 21:00:00', $2 = '108.03', $3 = '108.95', $4 = '107.97', $5 = '108.72', $6 = '3409', $7 = '515840247963296300', $8 = '0', $9 = '2025-03-05 13:11:39.978', $10 = '2025-03-05 13:11:39.944', $11 = '108.03', $12 = '108.95', $13 = '107.97', $14 = '108.72', $15 = '3409', $16 = '0', $17 = '2025-03-05 13:11:39.978', $18 = '2025-03-05 13:11:39.944'
-
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: 2025-03-05 13:11:31 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2025-03-04 21:00:00', $2 = '72.98', $3 = '73.84', $4 = '72.74', $5 = '73.5', $6 = '7407', $7 = '515840247879403300', $8 = '0', $9 = '2025-03-05 13:11:31.962', $10 = '2025-03-05 13:11:31.888', $11 = '72.98', $12 = '73.84', $13 = '72.74', $14 = '73.5', $15 = '7407', $16 = '0', $17 = '2025-03-05 13:11:31.962', $18 = '2025-03-05 13:11:31.888'
14 188ms 204 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 13 204 188ms 0ms [ User: postgres - Total duration: 1s295ms - Times executed: 204 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s259ms - Times executed: 200 ]
[ Application: [unknown] - Total duration: 35ms - Times executed: 4 ]
-
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: 2025-03-05 13:52:59 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: 2025-03-05 13:03:45 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42 parameters: $1 = '538', $2 = 'XAUUSDr', $3 = '538'
-
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: 2025-03-05 13:32:02 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '558', $2 = 'EURGBP', $3 = '558'
15 61ms 13 3ms 6ms 4ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 13 13 61ms 4ms [ User: postgres - Total duration: 2s585ms - Times executed: 13 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s585ms - Times executed: 13 ]
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-03-05 13:23:59 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '667', $2 = '667'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-03-05 13:41:19 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '972', $2 = '972'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-03-05 13:26:00 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '627', $2 = '627'
16 53ms 714 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 13 714 53ms 0ms [ User: postgres - Total duration: 57ms - Times executed: 714 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 57ms - Times executed: 714 ]
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2025-03-05 13:05:47 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '605718149940581301'
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2025-03-05 13:31:36 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '605718090096079301'
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2025-03-05 13:17:54 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.239 parameters: $1 = '605718205239949301'
17 48ms 1 48ms 48ms 48ms with maxwhid as ( ;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 13 1 48ms 48ms [ User: postgres - Total duration: 35ms - Times executed: 1 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 35ms - Times executed: 1 ]
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with maxwhid as ( ;
Date: 2025-03-05 13:22:20 Duration: 48ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.66 parameters: $1 = '335', $2 = '621', $3 = '637', $4 = '642', $5 = '660', $6 = '666', $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 29ms 194 0ms 0ms 0ms SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T30 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 13 194 29ms 0ms [ User: postgres - Total duration: 737ms - Times executed: 194 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 737ms - Times executed: 194 ]
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T30 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2025-03-05 13:32:52 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42 parameters: $1 = '515840243868141300'
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T30 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2025-03-05 13:03:20 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '515840248621279300'
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T30 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2025-03-05 13:32:46 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42 parameters: $1 = '515840243882092300'
19 28ms 778 0ms 0ms 0ms SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 13 778 28ms 0ms [ User: postgres - Total duration: 25ms - Times executed: 778 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 25ms - Times executed: 778 ]
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-03-05 13:17:38 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.239 parameters: $1 = '500991628202730200'
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-03-05 13:18:12 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '515840233916163300'
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2025-03-05 13:20:04 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '515840243266602300'
20 23ms 76 0ms 0ms 0ms SELECT DISTINCT ;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 13 76 23ms 0ms [ User: postgres - Total duration: 311ms - Times executed: 76 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 311ms - Times executed: 76 ]
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SELECT DISTINCT ;
Date: 2025-03-05 13:30:06 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '529', $2 = '529'
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SELECT DISTINCT ;
Date: 2025-03-05 13:30:06 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529'
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SELECT DISTINCT ;
Date: 2025-03-05 13:16:05 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.248 parameters: $1 = '605679104126087300', $2 = '3', $3 = '3', $4 = '720'
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Events
Log levels
Key values
- 622,646 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 8 ERROR entries
- 0 WARNING entries
Most Frequent Errors/Events
Key values
- 8 Max number of times the same event was reported
- 8 Total events found
Rank Times reported Error 1 8 ERROR: more than one row returned by a subquery used as an expression
Times Reported Most Frequent Error / Event #1
Day Hour Count Mar 05 13 8 - ERROR: more than one row returned by a subquery used as an expression
Statement: 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 = $1 and basegroupname = $2 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 = $3 and acs.brokerid = $4)) OR (klresultuid > (SELECT COALESCE(MAX(klresultuid),0) FROM correlating_signals acs where acs.basegroupname = $5 and acs.brokerid = $6))) -- maximum per day and ( select count(distinct cs.cpresultuid) -- count for today from correlating_signals cs where cs.brokerid = $7 and cs.basegroupname = $8 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 = $9 ) 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: 2025-03-05 13:07:08 Database: acaweb_fx Application: PostgreSQL JDBC Driver User: postgres Remote: 192.168.4.238