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Global information
- Generated on Wed Nov 13 17:59:49 2024
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2024-11-13_190000.log
- Parsed 1,598,656 log entries in 48s
- Log start from 2024-11-13 19:00:00 to 2024-11-13 19:59:47
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Overview
Global Stats
- 164 Number of unique normalized queries
- 106,742 Number of queries
- 49m31s Total query duration
- 2024-11-13 19:00:00 First query
- 2024-11-13 19:59:47 Last query
- 3,321 queries/s at 2024-11-13 19:45:04 Query peak
- 49m31s Total query duration
- 4s80ms Prepare/parse total duration
- 34s395ms Bind total duration
- 48m53s Execute total duration
- 0 Number of events
- 0 Number of unique normalized events
- 0 Max number of times the same event was reported
- 0 Number of cancellation
- 36 Total number of automatic vacuums
- 58 Total number of automatic analyzes
- 380 Number temporary file
- 113.39 MiB Max size of temporary file
- 6.24 MiB Average size of temporary file
- 3,206 Total number of sessions
- 13 sessions at 2024-11-13 19:51:02 Session peak
- 2d17h54m13s Total duration of sessions
- 1m14s Average duration of sessions
- 33 Average queries per session
- 926ms Average queries duration per session
- 1m13s Average idle time per session
- 3,206 Total number of connections
- 32 connections/s at 2024-11-13 19:10:01 Connection peak
- 2 Total number of databases
SQL Traffic
Key values
- 3,321 queries/s Query Peak
- 2024-11-13 19:45:04 Date
SELECT Traffic
Key values
- 3,263 queries/s Query Peak
- 2024-11-13 19:45:04 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 124 queries/s Query Peak
- 2024-11-13 19:10:12 Date
Queries duration
Key values
- 49m31s 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) Nov 13 19 106,742 0ms 30s140ms 27ms 1m54s 2m17s 3m42s Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Nov 13 19 76,248 26 2ms 3s1ms 12s47ms 23s532ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Nov 13 19 22,131 3,040 16 96 1ms 554ms 719ms 1s413ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Nov 13 19 15,019 90,268 6.01 14.26% Day Hour Count Average / Second Nov 13 19 3,206 0.89/s Day Hour Count Average Duration Average idle time Nov 13 19 3,206 1m14s 1m13s -
Connections
Established Connections
Key values
- 32 connections Connection Peak
- 2024-11-13 19:10:01 Date
Connections per database
Key values
- acaweb_fx Main Database
- 3,206 connections Total
Connections per user
Key values
- postgres Main User
- 3,206 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 1610 connections
- 3,206 Total connections
Host Count 127.0.0.1 115 192.168.0.216 89 192.168.1.145 103 192.168.1.20 129 192.168.1.231 20 192.168.1.250 196 192.168.1.90 58 192.168.2.126 68 192.168.2.182 24 192.168.2.205 12 192.168.2.82 47 192.168.3.199 60 192.168.4.142 1,610 192.168.4.150 10 192.168.4.16 4 192.168.4.223 1 192.168.4.238 12 192.168.4.33 59 192.168.4.98 318 [local] 271 -
Sessions
Simultaneous sessions
Key values
- 13 sessions Session Peak
- 2024-11-13 19:51:02 Date
Histogram of session times
Key values
- 2,722 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 3,206 sessions Total
Sessions per user
Key values
- postgres Main User
- 3,206 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 3,206 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 115 7s183ms 62ms 192.168.0.216 89 11s129ms 125ms 192.168.1.145 103 4h2m36s 2m21s 192.168.1.20 129 17h25m37s 8m6s 192.168.1.231 20 9h55m20s 29m46s 192.168.1.250 196 14h2m51s 4m18s 192.168.1.90 58 35s546ms 612ms 192.168.2.126 68 6s327ms 93ms 192.168.2.182 24 19s348ms 806ms 192.168.2.205 12 349ms 29ms 192.168.2.82 47 16s248ms 345ms 192.168.3.199 60 883ms 14ms 192.168.4.142 1,610 11m9s 415ms 192.168.4.150 10 20h12m46s 2h1m16s 192.168.4.16 4 31ms 7ms 192.168.4.223 1 179ms 179ms 192.168.4.238 12 15s440ms 1s286ms 192.168.4.33 59 1s45ms 17ms 192.168.4.98 318 10s603ms 33ms [local] 271 1m45s 390ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 11,529 buffers Checkpoint Peak
- 2024-11-13 19:45:59 Date
- 210.042 seconds Highest write time
- 0.050 seconds Sync time
Checkpoints Wal files
Key values
- 4 files Wal files usage Peak
- 2024-11-13 19:15:59 Date
Checkpoints distance
Key values
- 135.85 Mo Distance Peak
- 2024-11-13 19:15:59 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Nov 13 19 76,886 2,465.903s 0.105s 2,466.219s Day Hour Added Removed Recycled Synced files Longest sync Average sync Nov 13 19 0 0 26 2,318 0.042s 0s Day Hour Count Avg time (sec) Nov 13 19 0 0s Day Hour Mean distance Mean estimate Nov 13 19 35,558.33 kB 55,357.00 kB -
Temporary Files
Size of temporary files
Key values
- 123.09 MiB Temp Files size Peak
- 2024-11-13 19:40:06 Date
Number of temporary files
Key values
- 30 per second Temp Files Peak
- 2024-11-13 19:17:09 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Nov 13 19 380 2.32 GiB 6.24 MiB Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 41 182.12 MiB 4.01 MiB 6.95 MiB 4.44 MiB with rar_max as ( ;-
WITH rar_max as ( ;
Date: 2024-11-13 19:00:17 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver
2 40 1.40 GiB 3.83 MiB 113.39 MiB 35.76 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), 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: 2024-11-13 19:00:11 Duration: 8s744ms 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: 2024-11-13 19:30:10 Duration: 7s678ms 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: 2024-11-13 19:10:07 Duration: 4s505ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown]
3 16 179.85 MiB 11.23 MiB 11.24 MiB 11.24 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: 2024-11-13 19:01:12 Duration: 596ms 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: 2024-11-13 19:31:11 Duration: 573ms 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: 2024-11-13 19:11:12 Duration: 569ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
4 16 373.58 MiB 23.34 MiB 23.35 MiB 23.35 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: 2024-11-13 19:01:14 Duration: 1s365ms 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: 2024-11-13 19:31:13 Duration: 1s356ms 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: 2024-11-13 19:41:13 Duration: 1s352ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
5 4 200.85 MiB 50.12 MiB 50.36 MiB 50.21 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2024-11-13 19:17:12 Duration: 10s513ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2024-11-13 19:02:13 Duration: 10s345ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2024-11-13 19:32:12 Duration: 10s156ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
6 1 4.42 MiB 4.42 MiB 4.42 MiB 4.42 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, $227, $228, $229, $230, $231, $232, $233, $234)) AND ($235 = 0 OR fr.pattern in ($236)) AND ($237 = 0 OR fr.patternlengthbars <= $238) AND ($239 = 0 OR ($240 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($241 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $242 OR relevant = 1) AND ($243 = 0 OR age <= $244) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2024-11-13 19:17:42 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 1 113.39 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2024-11-13 19:00:06 ]
2 99.92 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: 2024-11-13 19:20:04 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
3 95.53 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: 2024-11-13 19:10:06 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
4 88.79 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: 2024-11-13 19:30:05 ]
5 67.31 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 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: 2024-11-13 19:30:05 ]
6 66.38 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2024-11-13 19:40:04 ]
7 56.31 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 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: 2024-11-13 19:10:04 ]
8 55.95 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: 2024-11-13 19:50:06 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.90 - Application: [unknown] ]
9 52.66 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: 2024-11-13 19:40:04 ]
10 51.94 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: 2024-11-13 19:50:04 ]
11 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: 2024-11-13 19:40:05 ]
12 50.36 MiB select updateageforrelevantresults ();[ Date: 2024-11-13 19:17:04 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
13 50.23 MiB select updateageforrelevantresults ();[ Date: 2024-11-13 19:47:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
14 50.22 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: 2024-11-13 19:50:04 ]
15 50.14 MiB select updateageforrelevantresults ();[ Date: 2024-11-13 19:32:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
16 50.12 MiB select updateageforrelevantresults ();[ Date: 2024-11-13 19:02:05 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
17 49.20 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: 2024-11-13 19:40:04 ]
18 46.76 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2024-11-13 19:50:05 ]
19 45.22 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: 2024-11-13 19:30:05 ]
20 43.55 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: 2024-11-13 19:20:04 ]
-
Vacuums
Vacuums / Analyzes Distribution
Key values
- 0 sec Highest CPU-cost vacuum
Table
Database - Date
- 0 sec Highest CPU-cost analyze
Table
Database - Date
Analyzes per table
Key values
- public.solr_relevance_old (16) Main table analyzed (database acaweb_fx)
- 58 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 16 acaweb_fx.pg_catalog.pg_attribute 6 acaweb_fx.public.datafeeds_latestrun 4 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.pg_catalog.pg_depend 2 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.public.autochartist_symbolupdates 1 acaweb_fx.public.consecutivecandles_results 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.relevance_consecutivecandles_results 1 acaweb_fx.public.symbollatestupdatetime 1 acaweb_fx.public.relevance_bigmovement_results 1 Total 58 Vacuums per table
Key values
- public.solr_relevance_old (16) Main table vacuumed on database acaweb_fx
- 36 vacuums Total
Index Buffer usage Skipped WAL usage Table Vacuums scans hits misses dirtied pins frozen records full page bytes acaweb_fx.public.solr_relevance_old 16 16 13,645 0 48 0 0 8,512 16 1,637,639 acaweb_fx.public.datafeeds_latestrun 4 0 483 0 8 0 0 68 8 60,772 acaweb_fx.pg_catalog.pg_attribute 2 2 1,691 0 335 0 128 779 291 1,734,565 acaweb_fx.public.relevance_keylevels_results 2 2 8,302 0 289 2 187 2,139 1,147 3,343,508 acaweb_fx.public.relevance_autochartist_results 2 2 7,900 0 258 2 457 1,720 398 1,174,070 acaweb_fx.public.relevance_fibonacci_results 2 2 2,601 0 71 1 110 420 195 452,046 acaweb_fx.pg_catalog.pg_index 1 1 88 0 11 0 0 28 10 75,478 acaweb_fx.pg_toast.pg_toast_2619 1 1 133 0 26 0 0 102 25 102,014 acaweb_fx.pg_catalog.pg_type 1 1 136 0 24 0 0 57 20 108,974 acaweb_fx.public.autochartist_symbolupdates 1 1 26,514 0 5,314 0 36,096 9,584 4,348 1,658,989 acaweb_fx.public.relevance_bigmovement_results 1 1 175 0 8 0 0 48 15 66,304 acaweb_fx.pg_catalog.pg_depend 1 1 370 0 90 0 58 200 73 422,515 acaweb_fx.public.latest_t15_candle_view 1 1 65 0 1 0 0 6 1 9,031 acaweb_fx.pg_catalog.pg_class 1 1 359 0 25 0 47 120 26 150,340 Total 36 32 62,462 47,206 6,508 5 37,083 23,783 6,573 10,996,245 Tuples removed per table
Key values
- public.solr_relevance_old (16730) Main table with removed tuples on database acaweb_fx
- 33344 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 16 16 16,730 95,960 0 0 3,357 acaweb_fx.public.autochartist_symbolupdates 1 1 5,720 62,743 0 0 40,691 acaweb_fx.public.relevance_keylevels_results 2 2 3,154 23,084 0 0 558 acaweb_fx.public.relevance_autochartist_results 2 2 3,017 16,093 0 0 760 acaweb_fx.pg_catalog.pg_attribute 2 2 2,934 18,882 0 0 484 acaweb_fx.public.relevance_fibonacci_results 2 2 469 2,285 0 0 204 acaweb_fx.pg_catalog.pg_depend 1 1 392 11,963 0 0 114 acaweb_fx.public.datafeeds_latestrun 4 0 254 56 0 0 64 acaweb_fx.public.relevance_bigmovement_results 1 1 210 1,174 0 0 25 acaweb_fx.pg_catalog.pg_type 1 1 177 1,334 0 0 38 acaweb_fx.pg_catalog.pg_class 1 1 140 1,832 0 0 150 acaweb_fx.pg_toast.pg_toast_2619 1 1 71 170 1 0 50 acaweb_fx.public.latest_t15_candle_view 1 1 59 14 0 0 1 acaweb_fx.pg_catalog.pg_index 1 1 17 813 0 0 22 Total 36 32 33,344 236,403 1 0 46,518 Pages removed per table
Key values
- unknown (0) Main table with removed pages on database unknown
- 0 pages Total removed
Pages removed per tables
NO DATASET
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_catalog.pg_index 1 1 17 0 acaweb_fx.pg_toast.pg_toast_2619 1 1 71 0 acaweb_fx.pg_catalog.pg_type 1 1 177 0 acaweb_fx.public.autochartist_symbolupdates 1 1 5720 0 acaweb_fx.public.datafeeds_latestrun 4 0 254 0 acaweb_fx.pg_catalog.pg_attribute 2 2 2934 0 acaweb_fx.public.relevance_bigmovement_results 1 1 210 0 acaweb_fx.pg_catalog.pg_depend 1 1 392 0 acaweb_fx.public.latest_t15_candle_view 1 1 59 0 acaweb_fx.public.relevance_keylevels_results 2 2 3154 0 acaweb_fx.pg_catalog.pg_class 1 1 140 0 acaweb_fx.public.solr_relevance_old 16 16 16730 0 acaweb_fx.public.relevance_autochartist_results 2 2 3017 0 acaweb_fx.public.relevance_fibonacci_results 2 2 469 0 Total 36 32 33,344 0 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Nov 13 19 36 58 - 0 sec Highest CPU-cost vacuum
-
Locks
Locks by types
Key values
- unknown Main Lock Type
- 0 locks Total
Most frequent waiting queries (N)
Rank Count Total time Min time Max time Avg duration Query NO DATASET
Queries that waited the most
Rank Wait time Query NO DATASET
-
Queries
Queries by type
Key values
- 76,248 Total read queries
- 29,043 Total write queries
Queries by database
Key values
- acaweb_fx Main database
- 106,683 Requests
- 48m53s (acaweb_fx)
- Main time consuming database
Queries by user
Key values
- postgres Main user
- 106,742 Requests
User Request type Count Duration postgres Total 106,742 48m53s copy from 96 7s544ms copy to 26 6s490ms cte 3,082 44m56s ddl 16 381ms delete 16 21ms insert 22,131 17s879ms others 1,451 6s177ms select 76,248 3m6s tcl 636 144ms update 3,040 11s587ms Duration by user
Key values
- 48m53s (postgres) Main time consuming user
User Request type Count Duration postgres Total 106,742 48m53s copy from 96 7s544ms copy to 26 6s490ms cte 3,082 44m56s ddl 16 381ms delete 16 21ms insert 22,131 17s879ms others 1,451 6s177ms select 76,248 3m6s tcl 636 144ms update 3,040 11s587ms Queries by host
Key values
- 192.168.1.20 Main host
- 32,966 Requests
- 13m28s (192.168.1.20)
- Main time consuming host
Host Request type Count Duration 127.0.0.1 Total 13,432 36s842ms copy to 26 6s490ms cte 24 244ms insert 10,336 7s642ms select 534 21s286ms update 2,512 1s177ms 182.165.1.42 Total 144 5m58s cte 60 5m58s select 84 43ms 192.168.0.216 Total 356 225ms others 178 13ms select 170 133ms update 8 77ms 192.168.0.239 Total 580 448ms select 580 448ms 192.168.0.42 Total 1,320 639ms insert 365 28ms select 955 610ms 192.168.1.135 Total 126 502ms cte 6 197ms select 120 305ms 192.168.1.145 Total 29,292 12m33s cte 597 11m50s others 206 2ms select 28,489 42s915ms 192.168.1.20 Total 32,966 13m28s cte 576 12m41s others 258 2ms select 32,132 46s825ms 192.168.1.201 Total 1,751 1s271ms select 1,751 1s271ms 192.168.1.23 Total 2,217 2s450ms select 2,217 2s450ms 192.168.1.231 Total 40 0ms others 40 0ms 192.168.1.250 Total 9,475 13m16s cte 1,704 13m13s others 392 3ms select 7,379 3s309ms 192.168.1.90 Total 66 33s672ms cte 6 33s631ms others 8 0ms select 52 40ms 192.168.2.126 Total 86 58ms others 18 0ms select 68 58ms 192.168.2.182 Total 96 560ms others 48 4ms select 24 18ms update 24 536ms 192.168.2.205 Total 137 127ms insert 89 7ms others 24 2ms select 20 19ms update 4 98ms 192.168.2.82 Total 948 1s427ms insert 578 747ms others 94 8ms select 168 83ms update 108 587ms 192.168.3.199 Total 240 209ms others 120 9ms select 108 86ms update 12 114ms 192.168.4.142 Total 12,043 10s202ms insert 10,763 9s452ms select 1,280 750ms 192.168.4.150 Total 22 918ms others 21 0ms select 1 917ms 192.168.4.16 Total 12 1ms others 8 0ms select 4 0ms 192.168.4.223 Total 3 40ms cte 1 40ms others 2 0ms 192.168.4.238 Total 36 14s778ms cte 12 14s778ms others 24 0ms 192.168.4.33 Total 59 62ms select 59 62ms 192.168.4.98 Total 960 6s600ms others 6 5s909ms select 6 22ms tcl 636 144ms update 312 524ms [local] Total 335 1m45s copy from 96 7s544ms cte 96 23s379ms ddl 16 381ms delete 16 21ms others 4 220ms select 47 1m5s update 60 8s470ms Queries by application
Key values
- PostgreSQL JDBC Driver Main application
- 77,365 Requests
- 39m39s (PostgreSQL JDBC Driver)
- Main time consuming application
Application Request type Count Duration PostgreSQL JDBC Driver Total 77,365 39m39s cte 2,896 38m insert 365 28ms others 476 4ms select 73,628 1m39s [unknown] Total 28,927 7m21s cte 66 6m32s insert 21,766 17s850ms others 971 5s952ms select 2,521 22s488ms tcl 636 144ms update 2,967 3s94ms psql Total 450 1m52s copy from 96 7s544ms copy to 26 6s490ms cte 120 23s624ms ddl 16 381ms delete 16 21ms others 4 220ms select 99 1m5s update 73 8s492ms Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2024-11-13 19:25:58 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 66,292 0-1ms duration
Slowest individual queries
Rank Duration Query 1 30s140ms 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: 2024-11-13 19:30:42 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
2 25s931ms 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: 2024-11-13 19:57:36 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
3 25s673ms 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: 2024-11-13 19:23:25 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
4 19s875ms 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#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: 2024-11-13 19:00:17 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
5 17s868ms 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: 2024-11-13 19:30:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
6 17s392ms 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: 2024-11-13 19:30:07 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
7 15s784ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2024-11-13 19:58:02 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
8 15s685ms 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#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: 2024-11-13 19:41:24 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
9 15s593ms 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#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: 2024-11-13 19:17:42 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
10 15s567ms 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#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: 2024-11-13 19:17:42 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
11 15s545ms 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#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: 2024-11-13 19:41:24 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
12 15s538ms 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#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: 2024-11-13 19:29:26 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
13 15s529ms 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#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: 2024-11-13 19:00:59 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
14 15s510ms 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#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: 2024-11-13 19:24:00 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
15 15s507ms WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = 't' THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = '627' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('0' = 0 OR coalesce(bim.code, s.symbol) in ('')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;[ Date: 2024-11-13 19:31:08 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.250 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
16 15s503ms 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#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: 2024-11-13 19:00:59 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.20 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
17 15s443ms 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#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: 2024-11-13 19:24:52 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
18 15s430ms 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#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: 2024-11-13 19:29:26 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
19 15s407ms 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#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: 2024-11-13 19:58:41 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.145 - Application: PostgreSQL JDBC Driver - Bind query: yes ]
20 15s359ms 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#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: 2024-11-13 19:54:34 - 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 21m8s 140 1s373ms 19s875ms 9s57ms 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 Nov 13 19 140 21m8s 9s57ms [ User: postgres - Total duration: 21m8s - Times executed: 140 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 18m13s - Times executed: 128 ]
[ Application: [unknown] - Total duration: 2m54s - 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#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: 2024-11-13 19:00:17 Duration: 19s875ms 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: 2024-11-13 19:30:11 Duration: 17s868ms 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 ('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: 2024-11-13 19:30:07 Duration: 17s392ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
2 14m37s 139 1s64ms 30s140ms 6s309ms 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 Nov 13 19 139 14m37s 6s309ms [ User: postgres - Total duration: 14m37s - Times executed: 139 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12m41s - Times executed: 127 ]
[ Application: [unknown] - Total duration: 1m55s - 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: 2024-11-13 19:30:42 Duration: 30s140ms 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: 2024-11-13 19:57:36 Duration: 25s931ms 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: 2024-11-13 19:23:25 Duration: 25s673ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
3 6m9s 139 565ms 5s502ms 2s659ms 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 Nov 13 19 139 6m9s 2s659ms [ User: postgres - Total duration: 6m9s - Times executed: 139 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 5m14s - Times executed: 127 ]
[ Application: [unknown] - Total duration: 55s448ms - 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: 2024-11-13 19:30:12 Duration: 5s502ms 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: 2024-11-13 19:25:50 Duration: 4s792ms 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 = '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: 2024-11-13 19:55:50 Duration: 4s771ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
4 1m 18,015 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 #4
Day Hour Count Duration Avg duration Nov 13 19 18,015 1m 3ms [ User: postgres - Total duration: 1m - Times executed: 18015 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m - Times executed: 18015 ]
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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 = 'WMT.US' OR dss.downloadersymbol = 'WMT.US') AND dss.enabled = 1;
Date: 2024-11-13 19:30:05 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 = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'AUDUSD' OR dss.downloadersymbol = 'AUDUSD') AND dss.enabled = 1;
Date: 2024-11-13 19:30:05 Duration: 32ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'GBPCHF' OR dss.downloadersymbol = 'GBPCHF') AND dss.enabled = 1;
Date: 2024-11-13 19:00:06 Duration: 30ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
5 59s939ms 114 31ms 996ms 525ms with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Nov 13 19 114 59s939ms 525ms [ User: postgres - Total duration: 59s939ms - Times executed: 114 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 48s740ms - Times executed: 102 ]
[ Application: [unknown] - Total duration: 11s198ms - 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: 2024-11-13 19:01:01 Duration: 996ms 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: 2024-11-13 19:31:02 Duration: 972ms 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 = '627' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2024-11-13 19:25:06 Duration: 959ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
6 41s144ms 4 10s129ms 10s513ms 10s286ms select updateageforrelevantresults ();Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Nov 13 19 4 41s144ms 10s286ms [ User: postgres - Total duration: 41s144ms - Times executed: 4 ]
[ Application: psql - Total duration: 41s144ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2024-11-13 19:17:12 Duration: 10s513ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2024-11-13 19:02:13 Duration: 10s345ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2024-11-13 19:32:12 Duration: 10s156ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
7 35s294ms 90 249ms 852ms 392ms with last_candle as ( select acs.symbolid as symbolid, acs.latestpricedatetime as latest_candle_time, bsl.brokerid as broker_id, coalesce(bim.code, s.symbol) as symbol, bim.code as symbol_mapping, s.exchange as exchange, s.timegranularity as timegranularity from autochartist_symbolupdates acs inner join brokersymbollist bsl on acs.symbolid = bsl.symbolid inner join symbols s on acs.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where bsl.brokerid = ? and s.deleted = ? and s.nonliquid = ? and acs.latestpricedatetime is not null ) select * from ( select lc.broker_id as brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / ?) + ? as sast_hh, mod(cast(psp.fromtime as int), ?) as sast_mm, current_timestamp as datetime, (powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice as closingprice, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / ?.?) as low_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / ?.?) as high_15, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / ?.?) as low_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / ?.?) as high_30, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / ?.?) as low_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / ?.?) as high_60, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / ?.?) as low_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / ?.?) as high_240, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / ?.?) as low_1440, ((powerstatslatestprfprice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / ?.?) as high_1440, dtt.absolutetimezoneoffset as datafeedtimezoneoffset, dtt.timezone as datafeedtimezonename, (round((cast(? as float) - rank) / ? * ?)) as rank_rounded, ((cast(? as float) - rank) / ? * ?) as rank from last_candle lc inner join downloadersymbolsettings dss on lc.symbolid = dss.symbolid inner join datafeedstimetable dtt on trim(dss.classname) = trim(dtt.classname) and dtt.dayofweek = ? -- assuming timezone is same for whole week. inner join powerstats_symboldata psd on psd.symbolid = lc.symbolid left outer join powerstats_trumpet psp on psd.trumpetsymbolid = psp.symbolid and psp.dayofweek = extract(dow from lc.latest_candle_time) and psp.fromtime = cast(extract(? from lc.latest_candle_time) as integer) * ? + extract(? from (cast(extract(? from lc.latest_candle_time) as integer) / ?) * ? * interval ?) inner join prfsymboltree prf on psd.symbolid = prf.symbolid and date_trunc(?, prf.enddate) = date_trunc(?, psp.enddate) left join lateral ( select ph.hour, (ave + stddev) as volatility, rank() over (order by (ave + stddev) desc) as rank from powerstats_hourly ph where ph.symbolid = psd.hourlysymbolid and date_trunc(?,ph.enddate) = date_trunc(?, prf.enddate) ) rank_query on true where prf.brokerid = ? and rank_query.hour = floor((psp.fromtime) / ?) and volatility > ? order by rank desc, rank_rounded desc, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Nov 13 19 90 35s294ms 392ms [ User: postgres - Total duration: 35s294ms - Times executed: 90 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 35s294ms - Times executed: 90 ]
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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: 2024-11-13 19:24:00 Duration: 852ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2024-11-13 19:24:00 Duration: 845ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2024-11-13 19:00:00 Duration: 823ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
8 33s631ms 6 4s101ms 8s744ms 5s605ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Nov 13 19 6 33s631ms 5s605ms [ User: postgres - Total duration: 33s631ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 33s631ms - 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: 2024-11-13 19:00:11 Duration: 8s744ms 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: 2024-11-13 19:30:10 Duration: 7s678ms 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: 2024-11-13 19:10:07 Duration: 4s505ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
9 28s958ms 21,085 0ms 35ms 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 #9
Day Hour Count Duration Avg duration Nov 13 19 21,085 28s958ms 1ms [ User: postgres - Total duration: 28s958ms - Times executed: 21085 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 28s958ms - Times executed: 21085 ]
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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 = '515840243250333300';
Date: 2024-11-13 19:00:03 Duration: 35ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) 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 = '515840243158623300';
Date: 2024-11-13 19:30:05 Duration: 27ms 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 = '515840243255822300';
Date: 2024-11-13 19:00:02 Duration: 26ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
10 21s438ms 16 1s325ms 1s365ms 1s339ms 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 Nov 13 19 16 21s438ms 1s339ms [ User: postgres - Total duration: 21s438ms - Times executed: 16 ]
[ Application: psql - Total duration: 21s438ms - 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: 2024-11-13 19:01:14 Duration: 1s365ms 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: 2024-11-13 19:31:13 Duration: 1s356ms 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: 2024-11-13 19:41:13 Duration: 1s352ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 17s968ms 31 11ms 3s527ms 579ms select fixcandlegaps (?, false);Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Nov 13 19 31 17s968ms 579ms [ User: postgres - Total duration: 17s968ms - Times executed: 31 ]
[ Application: psql - Total duration: 17s968ms - Times executed: 31 ]
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select fixcandlegaps ('ATFX', false);
Date: 2024-11-13 19:06:08 Duration: 3s527ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('PEPPERSTONE', false);
Date: 2024-11-13 19:06:15 Duration: 2s647ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ICMARKETS', false);
Date: 2024-11-13 19:06:13 Duration: 2s457ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
12 14s778ms 12 1s98ms 1s511ms 1s231ms 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 #12
Day Hour Count Duration Avg duration Nov 13 19 12 14s778ms 1s231ms [ User: postgres - Total duration: 14s778ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14s778ms - Times executed: 12 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '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: 2024-11-13 19:36:48 Duration: 1s511ms 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: 2024-11-13 19:06:49 Duration: 1s407ms 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: 2024-11-13 19:51:47 Duration: 1s374ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
13 12s393ms 114 11ms 243ms 108ms 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 #13
Day Hour Count Duration Avg duration Nov 13 19 114 12s393ms 108ms [ User: postgres - Total duration: 12s393ms - Times executed: 114 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 10s50ms - Times executed: 102 ]
[ Application: [unknown] - Total duration: 2s343ms - 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: 2024-11-13 19:16:02 Duration: 243ms 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: 2024-11-13 19:11:02 Duration: 240ms 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 = '627' 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('400' = 0 OR 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: 2024-11-13 19:17:56 Duration: 233ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
14 11s500ms 181 15ms 255ms 63ms 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 #14
Day Hour Count Duration Avg duration Nov 13 19 181 11s500ms 63ms [ User: postgres - Total duration: 11s500ms - Times executed: 181 ]
[ Application: [unknown] - Total duration: 11s500ms - Times executed: 181 ]
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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 'PEPPERSTONE - 1';
Date: 2024-11-13 19:25:39 Duration: 255ms 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 'PEPPERSTONE - 1';
Date: 2024-11-13 19:24:44 Duration: 165ms 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 'PEPPERSTONE - 1';
Date: 2024-11-13 19:55:39 Duration: 164ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
15 9s661ms 181 14ms 154ms 53ms select distinct k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid from relevance_keylevels_results p inner join keylevels_results k on p.resultuid = k.resultuid inner join autochartist_stocklist asl on k.symbolid = asl.symbolid where k.patternclassid in (...) and asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Nov 13 19 181 9s661ms 53ms [ User: postgres - Total duration: 9s661ms - Times executed: 181 ]
[ Application: [unknown] - Total duration: 9s661ms - Times executed: 181 ]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2024-11-13 19:25:43 Duration: 154ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'FPMARKETS - 1';
Date: 2024-11-13 19:25:40 Duration: 153ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2024-11-13 19:54:42 Duration: 145ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
16 8s93ms 16 471ms 596ms 505ms update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Nov 13 19 16 8s93ms 505ms [ User: postgres - Total duration: 8s93ms - Times executed: 16 ]
[ Application: psql - Total duration: 8s93ms - 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: 2024-11-13 19:01:12 Duration: 596ms 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: 2024-11-13 19:31:11 Duration: 573ms 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: 2024-11-13 19:11:12 Duration: 569ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
17 7s303ms 5,976 0ms 21ms 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 Nov 13 19 5,976 7s303ms 1ms [ User: postgres - Total duration: 7s303ms - Times executed: 5976 ]
[ Application: [unknown] - Total duration: 7s303ms - Times executed: 5976 ]
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2024-11-13 19:15:00', '0.93508', '0.93534', '0.93502', '0.93505', '1027', '515840236501271300', '0', '2024-11-13 19:30:05.227', '2024-11-13 19:30:04.335') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.93508', high = '0.93534', low = '0.93502', close = '0.93505', volume = '1027', bsf = '0', sastdatetimewritten = '2024-11-13 19:30:05.227', sastdatetimereceived = '2024-11-13 19:30:04.335';
Date: 2024-11-13 19:30:05 Duration: 21ms 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 ('2024-11-13 18:45:00', '68.667', '68.682', '68.256', '68.377', '815', '515840234773718300', '0', '2024-11-13 19:00:08.396', '2024-11-13 19:00:08.356') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '68.667', high = '68.682', low = '68.256', close = '68.377', volume = '815', bsf = '0', sastdatetimewritten = '2024-11-13 19:00:08.396', sastdatetimereceived = '2024-11-13 19:00:08.356';
Date: 2024-11-13 19:00:08 Duration: 11ms 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 ('2024-11-13 19:00:00', '0.88489', '0.88526', '0.88434', '0.88437', '2535', '515840245855569300', '0', '2024-11-13 19:24:47.661', '2024-11-13 19:24:47.592') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.88489', high = '0.88526', low = '0.88434', close = '0.88437', volume = '2535', bsf = '0', sastdatetimewritten = '2024-11-13 19:24:47.661', sastdatetimereceived = '2024-11-13 19:24:47.592';
Date: 2024-11-13 19:24:47 Duration: 8ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
18 7s 80 8ms 647ms 87ms copy solr_relevance_old (uuid, relevant, age, result_uid) from stdin with ( format csv, header);Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Nov 13 19 80 7s 87ms [ User: postgres - Total duration: 7s - Times executed: 80 ]
[ Application: psql - Total duration: 7s - Times executed: 80 ]
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COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2024-11-13 19:48:13 Duration: 647ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2024-11-13 19:03:13 Duration: 607ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2024-11-13 19:26:13 Duration: 299ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
19 5s909ms 6 969ms 1s5ms 984ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Nov 13 19 6 5s909ms 984ms [ User: postgres - Total duration: 5s909ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 5s909ms - Times executed: 6 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2024-11-13 19:31:17 Duration: 1s5ms 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: 2024-11-13 19:01:17 Duration: 998ms 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: 2024-11-13 19:46:17 Duration: 983ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
20 4s729ms 8 534ms 735ms 591ms select updateresultsmaterializedview ();Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Nov 13 19 8 4s729ms 591ms [ User: postgres - Total duration: 4s729ms - Times executed: 8 ]
[ Application: psql - Total duration: 4s729ms - Times executed: 8 ]
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select updateresultsmaterializedview ();
Date: 2024-11-13 19:17:13 Duration: 735ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2024-11-13 19:32:13 Duration: 623ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
-
select updateresultsmaterializedview ();
Date: 2024-11-13 19:02:13 Duration: 606ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 29,328 156ms 0ms 12ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Nov 13 19 29,328 156ms 0ms [ User: postgres - Total duration: 156ms - Times executed: 29328 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 147ms - Times executed: 29136 ]
[ Application: [unknown] - Total duration: 8ms - Times executed: 192 ]
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select 1;
Date: 2024-11-13 19:30:04 Duration: 12ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2024-11-13 19:30:06 Duration: 10ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2024-11-13 19:30:03 Duration: 10ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
2 21,085 28s958ms 0ms 35ms 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 Nov 13 19 21,085 28s958ms 1ms [ User: postgres - Total duration: 28s958ms - Times executed: 21085 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 28s958ms - Times executed: 21085 ]
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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 = '515840243250333300';
Date: 2024-11-13 19:00:03 Duration: 35ms 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) 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 = '515840243158623300';
Date: 2024-11-13 19:30:05 Duration: 27ms 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 = '515840243255822300';
Date: 2024-11-13 19:00:02 Duration: 26ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
3 18,015 1m 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 Nov 13 19 18,015 1m 3ms [ User: postgres - Total duration: 1m - Times executed: 18015 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m - Times executed: 18015 ]
-
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 = 'WMT.US' OR dss.downloadersymbol = 'WMT.US') AND dss.enabled = 1;
Date: 2024-11-13 19:30:05 Duration: 51ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'AUDUSD' OR dss.downloadersymbol = 'AUDUSD') AND dss.enabled = 1;
Date: 2024-11-13 19:30:05 Duration: 32ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'GBPCHF' OR dss.downloadersymbol = 'GBPCHF') AND dss.enabled = 1;
Date: 2024-11-13 19:00:06 Duration: 30ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
4 6,100 4s344ms 0ms 12ms 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 #4
Day Hour Count Duration Avg duration Nov 13 19 6,100 4s344ms 0ms [ User: postgres - Total duration: 4s344ms - Times executed: 6100 ]
[ Application: [unknown] - Total duration: 4s344ms - Times executed: 6100 ]
-
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 ('515840249536005300-1|45561.3333|45602.6667|45552.3333|45586.5|190.44|181.11|169.5|168.655', 515840249536005300, 10.000000000000000000000000000000, 'Descending Triangle', 4, '2024-11-13 17:15:31'::timestamp without time zone, - 1, 0.333960220109496386200000000000, - 1.000000000000000000000000000000, 0.220298419577634740900000000000, 1.000000000000000000000000000000, 0.586696266310105740700000000000, 164.565681269749404700000000000000, 169.064008862395581900000000000000, '2024-11-13 08:00:00'::timestamp without time zone, '2024-12-11 20:00:00'::timestamp without time zone, '2024-08-30 08:00:00'::timestamp without time zone, '2024-11-13 08:00:00'::timestamp without time zone, 190.689999999999997700000000000000, 171.289999999999992000000000000000, '2024-09-26 08:00:00'::timestamp without time zone, '2024-11-06 16:00:00'::timestamp without time zone, '2024-09-17 08:00:00'::timestamp without time zone, '2024-10-21 12:00:00'::timestamp without time zone, 190.439999999999997700000000000000, 181.110000000000013600000000000000, 169.500000000000000000000000000000, 168.655000000000001100000000000000, - 0.009285714285714273888000000000, - 0.084818181818181667680000000000, 1.442763054977065362000000000000, 0.306885495473200709000000000000, 'Continuation', 0.000000000000000000000000000000, '2024-11-13 08:00:00'::timestamp without time zone, 172.277099999999990100000000000000, 153, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2024-11-13 19:17:04 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('515840245946804300-1|45603.9167|45609.6667|45602.6667|45608.7917|101.03|92.8|94.48|90.99', 515840245946804300, 2.000000000000000000000000000000, 'Falling Wedge', 4, '2024-11-13 17:05:40'::timestamp without time zone, - 1, 0.187738429948615226400000000000, - 1.000000000000000000000000000000, 0.000000000000000000000000000000, 1.000000000000000000000000000000, 0.325447915915869856400000000000, 89.915451773835059160000000000000, 90.699771572431274080000000000000, '2024-11-13 18:00:00'::timestamp without time zone, '2024-11-17 07:00:00'::timestamp without time zone, '2024-11-05 16:00:00'::timestamp without time zone, '2024-11-13 18:00:00'::timestamp without time zone, 101.019999999999996020000000000000, 91.189999999999997720000000000000, '2024-11-07 22:00:00'::timestamp without time zone, '2024-11-13 16:00:00'::timestamp without time zone, '2024-11-06 16:00:00'::timestamp without time zone, '2024-11-12 19:00:00'::timestamp without time zone, 101.030000000000001140000000000000, 92.799999999999997160000000000000, 94.480000000000003980000000000000, 90.989999999999994880000000000000, - 0.112580645161290612800000000000, - 0.374090909090909251600000000000, 1.206363007944349919000000000000, 0.171062115288161703500000000000, 'Continuation', 0.000000000000000000000000000000, '2024-11-13 18:00:00'::timestamp without time zone, 91.260000000000005120000000000000, 37, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2024-11-13 19:07:13 Duration: 12ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO Autochartist_Results (ResultID, SymbolID, Bandwidth, Pattern, QtyTP, GMTTimeFound, Direction, InitialTrend, Breakout, VolumeIncrease, Noise, Symmetry, PredictionPriceFrom, PredictionPriceTo, PredictionTimeFrom, PredictionTimeTo, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, Resx0, Resx1, Supportx0, Supportx1, Resy0, Resy1, Supporty0, Supporty1, SupportGradient, ResGradient, RiskReward, PatternQuality, TrendChange, MaxMovementAfterBreakout, LatestBarAtBreakoutTime, LatestBarAtBreakoutPrice, PatternLengthBars, TemporaryPattern, relevancestartdistance, simulation, writtendatetime) VALUES ('515840221146482300-1|45594.1667|45603.5|45596.8333|45608.6667|8304|8343|8076|8170', 515840221146482300, 5.000000000000000000000000000000, 'Rising Wedge', 4, '2024-11-13 17:15:33'::timestamp without time zone, 1, 0.126560104087909935900000000000, - 1.000000000000000000000000000000, 0.796948579125429490400000000000, 0.313063252706855976700000000000, 0.427181756263397494100000000000, 8305.145787090488738000000000000000, 8371.149889017173336000000000000000, '2024-11-13 08:00:00'::timestamp without time zone, '2024-11-20 22:00:00'::timestamp without time zone, '2024-10-22 04:00:00'::timestamp without time zone, '2024-11-13 08:00:00'::timestamp without time zone, 8200.000000000000000000000000000000, 8265.000000000000000000000000000000, '2024-10-29 04:00:00'::timestamp without time zone, '2024-11-07 12:00:00'::timestamp without time zone, '2024-10-31 20:00:00'::timestamp without time zone, '2024-11-12 16:00:00'::timestamp without time zone, 8304.000000000000000000000000000000, 8343.000000000000000000000000000000, 8076.000000000000000000000000000000, 8170.000000000000000000000000000000, 2.000000000000000000000000000000, 0.886363636363636353600000000000, 1.705202933946771138000000000000, 0.413559535881483808500000000000, 'Continuation', 0.000000000000000000000000000000, '2024-11-13 08:00:00'::timestamp without time zone, 8258.000000000000000000000000000000, 67, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2024-11-13 19:17:06 Duration: 10ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
5 5,976 7s303ms 0ms 21ms 1ms insert into t15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Nov 13 19 5,976 7s303ms 1ms [ User: postgres - Total duration: 7s303ms - Times executed: 5976 ]
[ Application: [unknown] - Total duration: 7s303ms - Times executed: 5976 ]
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2024-11-13 19:15:00', '0.93508', '0.93534', '0.93502', '0.93505', '1027', '515840236501271300', '0', '2024-11-13 19:30:05.227', '2024-11-13 19:30:04.335') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.93508', high = '0.93534', low = '0.93502', close = '0.93505', volume = '1027', bsf = '0', sastdatetimewritten = '2024-11-13 19:30:05.227', sastdatetimereceived = '2024-11-13 19:30:04.335';
Date: 2024-11-13 19:30:05 Duration: 21ms 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 ('2024-11-13 18:45:00', '68.667', '68.682', '68.256', '68.377', '815', '515840234773718300', '0', '2024-11-13 19:00:08.396', '2024-11-13 19:00:08.356') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '68.667', high = '68.682', low = '68.256', close = '68.377', volume = '815', bsf = '0', sastdatetimewritten = '2024-11-13 19:00:08.396', sastdatetimereceived = '2024-11-13 19:00:08.356';
Date: 2024-11-13 19:00:08 Duration: 11ms 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 ('2024-11-13 19:00:00', '0.88489', '0.88526', '0.88434', '0.88437', '2535', '515840245855569300', '0', '2024-11-13 19:24:47.661', '2024-11-13 19:24:47.592') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.88489', high = '0.88526', low = '0.88434', close = '0.88437', volume = '2535', bsf = '0', sastdatetimewritten = '2024-11-13 19:24:47.661', sastdatetimereceived = '2024-11-13 19:24:47.592';
Date: 2024-11-13 19:24:47 Duration: 8ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
6 3,008 1s461ms 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 #6
Day Hour Count Duration Avg duration Nov 13 19 3,008 1s461ms 0ms [ User: postgres - Total duration: 1s461ms - Times executed: 3008 ]
[ Application: [unknown] - Total duration: 1s461ms - Times executed: 3008 ]
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2024-11-13 19:00:00', '162.1', '162.45', '161.98', '162.15', '426', '515840247929431300', '0', '2024-11-13 19:40:03.226', '2024-11-13 19:40:03.144') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '162.1', high = '162.45', low = '161.98', close = '162.15', volume = '426', bsf = '0', sastdatetimewritten = '2024-11-13 19:40:03.226', sastdatetimereceived = '2024-11-13 19:40:03.144';
Date: 2024-11-13 19:40:03 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 ('2024-11-13 18:30:00', '4.10393', '4.11023', '4.10333', '4.10793', '2213', '515840247873808300', '0', '2024-11-13 19:10:32.412', '2024-11-13 19:10:32.347') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '4.10393', high = '4.11023', low = '4.10333', close = '4.10793', volume = '2213', bsf = '0', sastdatetimewritten = '2024-11-13 19:10:32.412', sastdatetimereceived = '2024-11-13 19:10:32.347';
Date: 2024-11-13 19:10:32 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 ('2024-11-13 19:00:00', '69.34', '69.54', '69.3', '69.43', '3691', '515840247879231300', '0', '2024-11-13 19:40:01.12', '2024-11-13 19:40:01.075') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '69.34', high = '69.54', low = '69.3', close = '69.43', volume = '3691', bsf = '0', sastdatetimewritten = '2024-11-13 19:40:01.12', sastdatetimereceived = '2024-11-13 19:40:01.075';
Date: 2024-11-13 19:40:01 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
7 2,499 1s155ms 0ms 6ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Nov 13 19 2,499 1s155ms 0ms [ User: postgres - Total duration: 1s155ms - Times executed: 2499 ]
[ Application: [unknown] - Total duration: 1s155ms - Times executed: 2499 ]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2024-11-13 19:00:00', reason = 'Emerging pattern formed a completed pattern.' WHERE uniqueIndex = 'ABCD|-1|2024-11-13 07:00:00|8198.9|-1|4|62|BC=0.786*AB (0.806)|0|515840233373443300|1899-12-29 00:00:00|2024-11-13 08:30:00|2024-11-13 15:30:00|2024-11-13 17:00:00|1899-12-29 00:00:00' and relevant = 1;
Date: 2024-11-13 19:25:40 Duration: 6ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2024-11-13 17:00:00', reason = 'Approaching pattern wick broke through price level.' WHERE uniqueIndex = '|515840249744213300|111.107|1|2024-11-13 15:30:00|2024-11-13 15:30:00|1|-1' and relevant = 1;
Date: 2024-11-13 19:31:03 Duration: 6ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2024-11-13 17:00:00', reason = 'Approaching pattern wick broke through price level.' WHERE uniqueIndex = '|515840249744213300|111.107|1|2024-11-13 15:00:00|2024-11-13 15:00:00|1|-1' and relevant = 1;
Date: 2024-11-13 19:31:03 Duration: 5ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
8 2,260 2s239ms 0ms 7ms 0ms 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 #8
Day Hour Count Duration Avg duration Nov 13 19 2,260 2s239ms 0ms [ User: postgres - Total duration: 2s239ms - Times executed: 2260 ]
[ Application: [unknown] - Total duration: 2s239ms - Times executed: 2260 ]
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INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (10.000000000000000000000000000000, - 1, 1, '2024-11-13 16:59:42'::timestamp without time zone, '', 0.500000000000000000000000000000, 5, 185, 1.803730000000000056000000000000, '2024-11-07 15:00:00', '2024-11-05 11:00:00', '2024-11-04 22:00:00', '2024-10-29 08:00:00', '2024-10-28 21:00:00', '', '', '', '', '', 554, 1.804953500000000100000000000000, '2024-11-13 16:00:00'::timestamp without time zone, '2024-11-13 16:00:00', 0.000000000000000000000000000000, 0.001223499999999999761000000000, - 1, 515840249723905300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249723905300|1.80373|1|2024-11-13 16:00:00|-1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2024-10-28 21:00:00', 1.815129999999999910000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2024-11-13 19:01:15 Duration: 7ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (6.000000000000000000000000000000, - 1, 1, '2024-11-13 17:09:38'::timestamp without time zone, '2024-11-13 18:45:00', 1.070000000000003393000000000000, 3, 215, 225.555000000000006800000000000000, '2024-11-12 18:15:00', '2024-11-06 18:30:00', '2024-11-01 17:00:00', '', '', '', '', '', '', '', 374, 225.945500000000009800000000000000, '2024-11-13 18:45:00'::timestamp without time zone, '2024-11-13 18:45:00', 224.555000000000006800000000000000, 0.390500000000000013800000000000, 1, 515840249419417300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249419417300|225.555|1|2024-11-13 18:45:00|2024-11-13 18:45:00|1|-1', 224.078400000000016200000000000000, 1.476599999999990587000000000000, 2, '2024-11-01 17:00:00', 222.775000000000005700000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2024-11-13 19:11:11 Duration: 6ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (7.000000000000000000000000000000, - 1, 2, '2024-11-13 17:09:38'::timestamp without time zone, '', 0.500000000000000000000000000000, 5, 136, 222.544999999999987500000000000000, '2024-11-13 16:45:00', '2024-11-11 16:45:00', '2024-11-06 22:45:00', '2024-11-05 22:00:00', '2024-11-05 21:45:00', '', '', '', '', '', 408, 222.209499999999991400000000000000, '2024-11-13 18:45:00'::timestamp without time zone, '2024-11-13 18:45:00', 0.000000000000000000000000000000, 0.335500000000000409000000000000, 1, 515840249419417300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840249419417300|222.545|2|2024-11-13 18:45:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2024-11-05 21:45:00', 221.210000000000008000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2024-11-13 19:11:11 Duration: 6ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
9 1,788 718ms 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 #9
Day Hour Count Duration Avg duration Nov 13 19 1,788 718ms 0ms [ User: postgres - Total duration: 718ms - Times executed: 1788 ]
[ Application: [unknown] - Total duration: 718ms - Times executed: 1788 ]
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INSERT INTO Fibonacci_Results (Bandwidth, Pattern, GMTTimeFound, Direction, PatternStartTime, PatternEndTime, PatternStartPrice, PatternEndPrice, QtyTP, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, PatternLengthBars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) VALUES (2.000000000000000000000000000000, '3 Point Extension', '2024-11-13 17:07:15'::timestamp without time zone, 1, '2024-11-11 08:00:00'::timestamp without time zone, '2024-11-13 16:00:00'::timestamp without time zone, 612.759999999999990900000000000000, 630.950000000000045400000000000000, 3, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 612.759999999999990900000000000000, '2024-11-11 08:00:00'::timestamp without time zone, 665.470000000000027300000000000000, '2024-11-12 00:00:00'::timestamp without time zone, 599.480000000000018200000000000000, '2024-11-13 08:00:00'::timestamp without time zone, 0.367676865307528966100000000000, - 1.000000000000000000000000000000, 0.315640516491700662300000000000, 12, 665.470000000000027300000000000000, 640.264062914313058200000000000000, 706.254062914313067200000000000000, 651.358129421021999400000000000000, 683.420576670505056400000000000000, 632.475000000000022800000000000000, 624.685937085686987300000000000000, 515840248624023300, 0.580286785876642730000000000000, 'CD=1.272*BC (1.252) ', 0, '3 Point Extension|1|2024-11-11 08:00:00|612.76|630.95|3|12|CD=1.272*BC (1.252)|0|515840248624023300|1899-12-29 00:00:00|1899-12-29 00:00:00|2024-11-11 08:00:00|2024-11-12 00:00:00|2024-11-13 08:00:00', 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2024-11-13 19:08:48 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 (3.000000000000000000000000000000, 'Butterfly', '2024-11-13 17:05:30'::timestamp without time zone, - 1, '2024-11-06 16:00:00'::timestamp without time zone, '2024-11-13 18:00:00'::timestamp without time zone, 62.539999999999999140000000000000, - 1.000000000000000000000000000000, 5, 62.539999999999999140000000000000, '2024-11-06 16:00:00'::timestamp without time zone, 60.259999999999998010000000000000, '2024-11-06 20:00:00'::timestamp without time zone, 62.820000000000000280000000000000, '2024-11-11 19:00:00'::timestamp without time zone, 60.869999999999997440000000000000, '2024-11-13 17:00:00'::timestamp without time zone, 63.949117494235999000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.933318629616012751500000000000, - 1.000000000000000000000000000000, 8.564651777014542944000000000000, 55, 60.869999999999997440000000000000, 62.046118227597375500000000000000, 58.967000733361373930000000000000, 61.528465033734285330000000000000, 60.032419538448600350000000000000, 62.409558747117998220000000000000, 62.772999266638620950000000000000, 515840233343198300, 0.133362740767974552500000000000, 'BC=0.786*AB (0.762) ', 0, 'Butterfly|-1|2024-11-06 16:00:00|62.54|-1|5|55|BC=0.786*AB (0.762)|0|515840233343198300|2024-11-06 16:00:00|2024-11-06 20:00:00|2024-11-11 19:00:00|2024-11-13 17:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2024-11-13 19:07:03 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', '2024-11-13 16:59:44'::timestamp without time zone, 1, '2024-11-13 10:30:00'::timestamp without time zone, '2024-11-13 16:45:00'::timestamp without time zone, 175.365000000000009100000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 175.805000000000006800000000000000, '2024-11-13 13:30:00'::timestamp without time zone, 175.135999999999995700000000000000, '2024-11-13 14:45:00'::timestamp without time zone, 175.638000000000005200000000000000, '2024-11-13 16:15:00'::timestamp without time zone, 174.968999999999994100000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.765104393214426137200000000000, - 1.000000000000000000000000000000, 18.680961158129225200000000000000, 16, 175.638000000000005200000000000000, 175.382464738440290800000000000000, 176.051464738440302000000000000000, 175.494935271748204300000000000000, 175.819981145515498600000000000000, 175.303499999999985400000000000000, 175.224535261559708500000000000000, 515840249731876300, 0.469791213571147836600000000000, 'BC=0.786*AB (0.75) ', 0, 'ABCD|1|2024-11-13 10:30:00|175.365|-1|4|16|BC=0.786*AB (0.75)|0|515840249731876300|1899-12-29 00:00:00|2024-11-13 13:30:00|2024-11-13 14:45:00|2024-11-13 16:15:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2024-11-13 19:01:17 Duration: 6ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
10 1,607 616ms 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 #10
Day Hour Count Duration Avg duration Nov 13 19 1,607 616ms 0ms [ User: postgres - Total duration: 616ms - Times executed: 1607 ]
[ Application: [unknown] - Total duration: 616ms - Times executed: 1607 ]
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2024-11-13 18:00:00', '2605.33', '2605.89', '2584.62', '2585.73', '15979', '515840247906886300', '0', '2024-11-13 19:10:34.507', '2024-11-13 19:10:34.447') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '2605.33', high = '2605.89', low = '2584.62', close = '2585.73', volume = '15979', bsf = '0', sastdatetimewritten = '2024-11-13 19:10:34.507', sastdatetimereceived = '2024-11-13 19:10:34.447';
Date: 2024-11-13 19:10:34 Duration: 7ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2024-11-13 18:00:00', '0.549', '0.5512', '0.543', '0.546', '638', '515840247923246300', '0', '2024-11-13 19:10:16.137', '2024-11-13 19:10:16.059') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0.549', high = '0.5512', low = '0.543', close = '0.546', volume = '638', bsf = '0', sastdatetimewritten = '2024-11-13 19:10:16.137', sastdatetimereceived = '2024-11-13 19:10:16.059';
Date: 2024-11-13 19:10:16 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2024-11-13 18:00:00', '7.03963', '7.05638', '7.0374', '7.05397', '1192', '515840247894566300', '0', '2024-11-13 19:10:30.396', '2024-11-13 19:10:30.355') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '7.03963', high = '7.05638', low = '7.0374', close = '7.05397', volume = '1192', bsf = '0', sastdatetimewritten = '2024-11-13 19:10:30.396', sastdatetimereceived = '2024-11-13 19:10:30.355';
Date: 2024-11-13 19:10:30 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
11 1,125 742ms 0ms 22ms 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 #11
Day Hour Count Duration Avg duration Nov 13 19 1,125 742ms 0ms [ User: postgres - Total duration: 742ms - Times executed: 1125 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 742ms - Times executed: 1125 ]
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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 = '605084348889191301' 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 = '605084348889191301' OR a.resultuid = '605084348889191301') AND dtt.dayofweek = 3;
Date: 2024-11-13 19:30:03 Duration: 22ms 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 = '604796511643480301' 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 = '604796511643480301' OR a.resultuid = '604796511643480301') AND dtt.dayofweek = 3;
Date: 2024-11-13 19:40:15 Duration: 9ms 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 ) 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 = '604796275021945301' 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 = '604796275021945301' OR a.resultuid = '604796275021945301') AND dtt.dayofweek = 3;
Date: 2024-11-13 19:40:15 Duration: 9ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
12 914 297ms 0ms 3ms 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 #12
Day Hour Count Duration Avg duration Nov 13 19 914 297ms 0ms [ User: postgres - Total duration: 297ms - Times executed: 914 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 297ms - Times executed: 914 ]
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '604796512409766303' 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 = '604796512409766303' OR a.resultuid = '604796512409766303') AND dtt.dayofweek = 3;
Date: 2024-11-13 19:40:14 Duration: 3ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '604794861516251303' 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 = '604794861516251303' OR a.resultuid = '604794861516251303') AND dtt.dayofweek = 3;
Date: 2024-11-13 19:40:15 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = '604796275566735303' 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 = '604796275566735303' OR a.resultuid = '604796275566735303') AND dtt.dayofweek = 3;
Date: 2024-11-13 19:40:15 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
13 635 157ms 0ms 2ms 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 #13
Day Hour Count Duration Avg duration Nov 13 19 635 157ms 0ms [ User: postgres - Total duration: 157ms - Times executed: 635 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 157ms - Times executed: 635 ]
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SELECT CASE WHEN a.old_resultuid = '605085530518566301' 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 = '605085530518566301' OR a.resultuid = '605085530518566301') AND dtt.dayofweek = 3;
Date: 2024-11-13 19:21:14 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '605085460600365301' 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 = '605085460600365301' OR a.resultuid = '605085460600365301') AND dtt.dayofweek = 3;
Date: 2024-11-13 19:01:00 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT CASE WHEN a.old_resultuid = '605085481019400301' 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 = '605085481019400301' OR a.resultuid = '605085481019400301') AND dtt.dayofweek = 3;
Date: 2024-11-13 19:35:51 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
14 628 669ms 0ms 2ms 1ms select s.symbolid, dss.downloadfrequency, dss.downloadersymbol from downloadersymbolsettings dss inner join symbols s on dss.symbolid = s.symbolid where dss.classname = ? and s.deleted = ? and dss.enabled = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Nov 13 19 628 669ms 1ms [ User: postgres - Total duration: 669ms - Times executed: 628 ]
[ Application: [unknown] - Total duration: 669ms - Times executed: 628 ]
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'PEPPERSTONE' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2024-11-13 19:54:35 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'PEPPERSTONE' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2024-11-13 19:25:33 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol FROM downloadersymbolsettings dss INNER JOIN symbols s ON dss.symbolid = s.symbolid WHERE dss.classname = 'HOTFOREX' AND s.deleted = 0 AND dss.enabled = 1;
Date: 2024-11-13 19:24:50 Duration: 2ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
15 628 76ms 0ms 0ms 0ms select downloadersymbol, spike_threshold from price_datafeed_spike_threshold where classname = ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Nov 13 19 628 76ms 0ms [ User: postgres - Total duration: 76ms - Times executed: 628 ]
[ Application: [unknown] - Total duration: 76ms - Times executed: 628 ]
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SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'PEPPERSTONE';
Date: 2024-11-13 19:25:33 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'AXIORY';
Date: 2024-11-13 19:30:22 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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SELECT downloadersymbol, spike_threshold FROM price_datafeed_spike_threshold WHERE classname = 'ATFX';
Date: 2024-11-13 19:54:37 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
16 604 18ms 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 #16
Day Hour Count Duration Avg duration Nov 13 19 604 18ms 0ms [ User: postgres - Total duration: 18ms - Times executed: 604 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 18ms - Times executed: 604 ]
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = '500991628275951200' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2024-11-13 19:02:18 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.239 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 = '515840241658676300' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2024-11-13 19:18:03 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 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 = '515840243244148300' GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2024-11-13 19:48:18 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
17 501 4ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Nov 13 19 501 4ms 0ms [ User: postgres - Total duration: 4ms - Times executed: 501 ]
[ Application: [unknown] - Total duration: 4ms - Times executed: 501 ]
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SET extra_float_digits = 3;
Date: 2024-11-13 19:00:05 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2024-11-13 19:45:04 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2024-11-13 19:30:03 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: [unknown] Bind query: yes
18 497 1s239ms 0ms 31ms 2ms select * from powerstatslatestprfprice (?, ?);Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Nov 13 19 497 1s239ms 2ms [ User: postgres - Total duration: 1s239ms - Times executed: 497 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s220ms - Times executed: 491 ]
[ Application: [unknown] - Total duration: 18ms - Times executed: 6 ]
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select * from PowerStatsLatestPRFPrice ('515840233449464300', '15');
Date: 2024-11-13 19:54:55 Duration: 31ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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select * from PowerStatsLatestPRFPrice ('515840243252176300', '15');
Date: 2024-11-13 19:24:59 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
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select * from PowerStatsLatestPRFPrice ('500991627549886200', '15');
Date: 2024-11-13 19:16:52 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.0.239 Application: PostgreSQL JDBC Driver Bind query: yes
19 475 4ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Nov 13 19 475 4ms 0ms [ User: postgres - Total duration: 4ms - Times executed: 475 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 4ms - Times executed: 475 ]
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2024-11-13 19:45:03 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: 2024-11-13 19:30:06 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2024-11-13 19:41:30 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
20 452 36ms 0ms 0ms 0ms 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 = ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Nov 13 19 452 36ms 0ms [ User: postgres - Total duration: 36ms - Times executed: 452 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 36ms - Times executed: 452 ]
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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 = '605085526550429301';
Date: 2024-11-13 19:16:35 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
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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 = '605085424842526301';
Date: 2024-11-13 19:20:04 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
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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 = '605084817783330301';
Date: 2024-11-13 19:32:59 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 10s129ms 10s513ms 10s286ms 4 41s144ms select updateageforrelevantresults ();Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Nov 13 19 4 41s144ms 10s286ms [ User: postgres - Total duration: 41s144ms - Times executed: 4 ]
[ Application: psql - Total duration: 41s144ms - Times executed: 4 ]
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select updateageforrelevantresults ();
Date: 2024-11-13 19:17:12 Duration: 10s513ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2024-11-13 19:02:13 Duration: 10s345ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2024-11-13 19:32:12 Duration: 10s156ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
2 1s373ms 19s875ms 9s57ms 140 21m8s 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 Nov 13 19 140 21m8s 9s57ms [ User: postgres - Total duration: 21m8s - Times executed: 140 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 18m13s - Times executed: 128 ]
[ Application: [unknown] - Total duration: 2m54s - 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#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: 2024-11-13 19:00:17 Duration: 19s875ms 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: 2024-11-13 19:30:11 Duration: 17s868ms 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 ('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: 2024-11-13 19:30:07 Duration: 17s392ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
3 1s64ms 30s140ms 6s309ms 139 14m37s 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 Nov 13 19 139 14m37s 6s309ms [ User: postgres - Total duration: 14m37s - Times executed: 139 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12m41s - Times executed: 127 ]
[ Application: [unknown] - Total duration: 1m55s - 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: 2024-11-13 19:30:42 Duration: 30s140ms 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: 2024-11-13 19:57:36 Duration: 25s931ms 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: 2024-11-13 19:23:25 Duration: 25s673ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
4 4s101ms 8s744ms 5s605ms 6 33s631ms 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 Nov 13 19 6 33s631ms 5s605ms [ User: postgres - Total duration: 33s631ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 33s631ms - 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: 2024-11-13 19:00:11 Duration: 8s744ms 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: 2024-11-13 19:30:10 Duration: 7s678ms 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: 2024-11-13 19:10:07 Duration: 4s505ms Database: acaweb_fx User: postgres Remote: 192.168.1.90 Application: [unknown] Bind query: yes
5 565ms 5s502ms 2s659ms 139 6m9s with rar_max as ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ? ), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end ), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp))) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Nov 13 19 139 6m9s 2s659ms [ User: postgres - Total duration: 6m9s - Times executed: 139 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 5m14s - Times executed: 127 ]
[ Application: [unknown] - Total duration: 55s448ms - 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: 2024-11-13 19:30:12 Duration: 5s502ms 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: 2024-11-13 19:25:50 Duration: 4s792ms 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 = '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: 2024-11-13 19:55:50 Duration: 4s771ms Database: acaweb_fx User: postgres Remote: 182.165.1.42 Application: [unknown] Bind query: yes
6 1s325ms 1s365ms 1s339ms 16 21s438ms with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Nov 13 19 16 21s438ms 1s339ms [ User: postgres - Total duration: 21s438ms - Times executed: 16 ]
[ Application: psql - Total duration: 21s438ms - 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: 2024-11-13 19:01:14 Duration: 1s365ms 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: 2024-11-13 19:31:13 Duration: 1s356ms 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: 2024-11-13 19:41:13 Duration: 1s352ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
7 1s98ms 1s511ms 1s231ms 12 14s778ms 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 #7
Day Hour Count Duration Avg duration Nov 13 19 12 14s778ms 1s231ms [ User: postgres - Total duration: 14s778ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14s778ms - Times executed: 12 ]
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with sym_info as ( select s.symbol as og_symbol, s.symbolid, coalesce(bim.code, s.symbol) as symbol, s.timegranularity, s.exchange, s.longname as symbolname, g.basegroupname, bg.brokerid, dft.absolutetimezoneoffset from symbols s inner join symbolgroup sg on sg.symbolid = s.symbolid inner join brokergroups bg on bg.groupid = sg.groupid inner join groups g on g.groupid = bg.groupid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dft on dft.classname = dss.classname and dft.dayofweek = 3 LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bg.brokerid AND bim.TYPE = 'OUTBOUND' where bg.brokerid = '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: 2024-11-13 19:36:48 Duration: 1s511ms 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: 2024-11-13 19:06:49 Duration: 1s407ms 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: 2024-11-13 19:51:47 Duration: 1s374ms Database: acaweb_fx User: postgres Remote: 192.168.4.238 Application: PostgreSQL JDBC Driver Bind query: yes
8 969ms 1s5ms 984ms 6 5s909ms refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Nov 13 19 6 5s909ms 984ms [ User: postgres - Total duration: 5s909ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 5s909ms - Times executed: 6 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2024-11-13 19:31:17 Duration: 1s5ms 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: 2024-11-13 19:01:17 Duration: 998ms 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: 2024-11-13 19:46:17 Duration: 983ms Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
9 534ms 735ms 591ms 8 4s729ms select updateresultsmaterializedview ();Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Nov 13 19 8 4s729ms 591ms [ User: postgres - Total duration: 4s729ms - Times executed: 8 ]
[ Application: psql - Total duration: 4s729ms - Times executed: 8 ]
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select updateresultsmaterializedview ();
Date: 2024-11-13 19:17:13 Duration: 735ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2024-11-13 19:32:13 Duration: 623ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2024-11-13 19:02:13 Duration: 606ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
10 11ms 3s527ms 579ms 31 17s968ms select fixcandlegaps (?, false);Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Nov 13 19 31 17s968ms 579ms [ User: postgres - Total duration: 17s968ms - Times executed: 31 ]
[ Application: psql - Total duration: 17s968ms - Times executed: 31 ]
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select fixcandlegaps ('ATFX', false);
Date: 2024-11-13 19:06:08 Duration: 3s527ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('PEPPERSTONE', false);
Date: 2024-11-13 19:06:15 Duration: 2s647ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select fixcandlegaps ('ICMARKETS', false);
Date: 2024-11-13 19:06:13 Duration: 2s457ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 31ms 996ms 525ms 114 59s939ms 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 Nov 13 19 114 59s939ms 525ms [ User: postgres - Total duration: 59s939ms - Times executed: 114 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 48s740ms - Times executed: 102 ]
[ Application: [unknown] - Total duration: 11s198ms - 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: 2024-11-13 19:01:01 Duration: 996ms 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: 2024-11-13 19:31:02 Duration: 972ms 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 = '627' AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('400' = 0 OR ccr.patternlengthbars <= '400') ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2024-11-13 19:25:06 Duration: 959ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
12 471ms 596ms 505ms 16 8s93ms update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Nov 13 19 16 8s93ms 505ms [ User: postgres - Total duration: 8s93ms - Times executed: 16 ]
[ Application: psql - Total duration: 8s93ms - 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: 2024-11-13 19:01:12 Duration: 596ms 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: 2024-11-13 19:31:11 Duration: 573ms 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: 2024-11-13 19:11:12 Duration: 569ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
13 249ms 852ms 392ms 90 35s294ms 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 Nov 13 19 90 35s294ms 392ms [ User: postgres - Total duration: 35s294ms - Times executed: 90 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 35s294ms - Times executed: 90 ]
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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: 2024-11-13 19:24:00 Duration: 852ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2024-11-13 19:24:00 Duration: 845ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH last_candle AS ( SELECT acs.symbolid AS symbolid, acs.latestpricedatetime AS latest_candle_time, bsl.brokerid AS broker_id, coalesce(bim.code, s.symbol) AS symbol, bim.code AS symbol_mapping, s.exchange AS exchange, s.timegranularity AS timegranularity FROM autochartist_symbolupdates acs INNER JOIN brokersymbollist bsl ON acs.symbolid = bsl.symbolid INNER JOIN symbols s ON acs.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE bsl.brokerid = '529' AND s.deleted = 0 AND s.nonliquid = 0 AND acs.latestpricedatetime IS NOT NULL ) SELECT * FROM ( SELECT lc.broker_id AS brokerid, prf.groupid, psp.symbolid, prf.longname, psd.hourlysymbolid, lc.symbol, lc.exchange, psp.enddate, psp.dayofweek, psp.fromtime, floor(psp.fromtime / 60) + 6 as SAST_HH, mod(cast(psp.fromtime as int), 60) as SAST_MM, current_timestamp AS datetime, (PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice AS closingprice, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_15 + psp.stddev_15) / 2.0) AS low_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_15 + psp.stddev_15) / 2.0) AS high_15, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_30 + psp.stddev_30) / 2.0) AS low_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_30 + psp.stddev_30) / 2.0) AS high_30, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_60 + psp.stddev_60) / 2.0) AS low_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_60 + psp.stddev_60) / 2.0) AS high_60, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_240 + psp.stddev_240) / 2.0) AS low_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_240 + psp.stddev_240) / 2.0) AS high_240, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice - (psp.ave_1440 + psp.stddev_1440) / 2.0) AS low_1440, ((PowerStatsLatestPRFPrice (cast(psp.symbolid as bigint), psd.trumpettimegranularity)).closingprice + (psp.ave_1440 + psp.stddev_1440) / 2.0) AS high_1440, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, (round((cast(25 as float) - rank) / 24 * 10)) as rank_rounded, ((cast(25 as float) - rank) / 24 * 10) as rank FROM last_candle lc INNER JOIN downloadersymbolsettings dss ON lc.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON TRIM(dss.classname) = TRIM(dtt.classname) and dtt.dayofweek = 3 -- assuming timezone is same for whole week. INNER JOIN powerstats_symboldata psd ON psd.symbolid = lc.symbolid LEFT OUTER JOIN powerstats_trumpet psp ON psd.trumpetsymbolid = psp.symbolid AND psp.dayofweek = extract(dow from lc.latest_candle_time) AND psp.fromtime = cast(extract('hour' from lc.latest_candle_time) as integer) * 60 + extract('minute' from (cast(extract('minute' from lc.latest_candle_time) as integer) / 15) * 15 * interval '1 minutes') INNER JOIN prfsymboltree prf ON psd.symbolid = prf.symbolid and DATE_TRUNC('day', prf.enddate) = DATE_TRUNC('day', psp.enddate) LEFT JOIN LATERAL ( SELECT ph.hour, (ave + stddev) AS volatility, rank() over (ORDER BY (ave + stddev) DESC) AS rank FROM powerstats_hourly ph WHERE ph.symbolid = psd.hourlysymbolid AND DATE_TRUNC('day', ph.enddate) = DATE_TRUNC('day', prf.enddate)) rank_query ON true WHERE prf.brokerid = '529' AND rank_query.hour = floor((psp.fromtime) / 60) AND volatility > 0 ORDER BY rank DESC, rank_rounded DESC, exchange, symbol, groupid) sub order by brokerid, groupid, symbolid;
Date: 2024-11-13 19:00:00 Duration: 823ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
14 11ms 243ms 108ms 114 12s393ms 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 Nov 13 19 114 12s393ms 108ms [ User: postgres - Total duration: 12s393ms - Times executed: 114 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 10s50ms - Times executed: 102 ]
[ Application: [unknown] - Total duration: 2s343ms - 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: 2024-11-13 19:16:02 Duration: 243ms 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: 2024-11-13 19:11:02 Duration: 240ms 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 = '627' 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 ('221' = 0 OR coalesce(bim.code, s.symbol) in ('#ADBE', '#AIRF', '#ALVG', '#AMZN', '#APPL', '#BA', '#BABA', '#BAYGn', '#BMWG', '#BNPP', '#BP', '#CAT', '#CBKG', '#DAIGn', '#DBKGn', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#META', '#MSFT', '#NFLX', '#RDSa', '#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', '#BP', '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', '#AIRF', '#ALVG', '#BAYGn', '#BMWG', '#BNPP', '#CBKG', '#DAIGn', '#DBKGn', '#RDSa', '#VOWG', 'AUS_200', 'ESP_35', 'EUR_50', 'FRA_40', 'GBR_100', 'HKG_50', 'NAS100', 'SPX500', 'US30', '#ADBE', '#AMZN', '#APPL', '#BA', '#BABA', '#CAT', '#DIS', '#EA', '#FB', '#FDX', '#GE', '#GM', '#GOOGL', '#GS', '#INTC', '#JPM', '#KO', '#MSFT', '#NFLX', '#TSLA', '#WMT', '#XOM')) AND ('400' = 0 OR 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: 2024-11-13 19:17:56 Duration: 233ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
15 8ms 647ms 87ms 80 7s copy solr_relevance_old (uuid, relevant, age, result_uid) from stdin with ( format csv, header);Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Nov 13 19 80 7s 87ms [ User: postgres - Total duration: 7s - Times executed: 80 ]
[ Application: psql - Total duration: 7s - Times executed: 80 ]
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COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2024-11-13 19:48:13 Duration: 647ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2024-11-13 19:03:13 Duration: 607ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
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COPY solr_relevance_old (uuid, relevant, age, result_uid) FROM STDIN WITH ( FORMAT csv, HEADER);
Date: 2024-11-13 19:26:13 Duration: 299ms Database: acaweb_fx User: postgres Remote: [local] Application: psql
16 15ms 255ms 63ms 181 11s500ms select distinct a.symbolid, p.resultuid, case when a.breakout >= ? then ? else ? end as type, a.resultid, a.bandwidth, a.patternlengthbars, a.patternendtime, a.resy0, a.supporty0, a.resy1, a.supporty1, a.direction, a.predictionpriceto, a.patternendprice, a.predictionpricefrom, a.resx0, a.supportx0, a.resgradient, a.supportgradient from relevance_autochartist_results p inner join autochartist_results a on p.resultuid = a.resultuid inner join autochartist_stocklist asl on a.symbolid = asl.symbolid where asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Nov 13 19 181 11s500ms 63ms [ User: postgres - Total duration: 11s500ms - Times executed: 181 ]
[ Application: [unknown] - Total duration: 11s500ms - Times executed: 181 ]
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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 'PEPPERSTONE - 1';
Date: 2024-11-13 19:25:39 Duration: 255ms 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 'PEPPERSTONE - 1';
Date: 2024-11-13 19:24:44 Duration: 165ms 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 'PEPPERSTONE - 1';
Date: 2024-11-13 19:55:39 Duration: 164ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
17 14ms 154ms 53ms 181 9s661ms select distinct k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid from relevance_keylevels_results p inner join keylevels_results k on p.resultuid = k.resultuid inner join autochartist_stocklist asl on k.symbolid = asl.symbolid where k.patternclassid in (...) and asl.enabled = ? and asl.recognitionengine ilike ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Nov 13 19 181 9s661ms 53ms [ User: postgres - Total duration: 9s661ms - Times executed: 181 ]
[ Application: [unknown] - Total duration: 9s661ms - Times executed: 181 ]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'ICMARKETS - 1';
Date: 2024-11-13 19:25:43 Duration: 154ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'FPMARKETS - 1';
Date: 2024-11-13 19:25:40 Duration: 153ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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SELECT DISTINCT k.symbolid, p.resultuid, k.symbolid, k.bandwidth, k.direction, k.patternendtime, k.patternprice, k.patternlengthbars, k.breakoutbars, k.uniquepointsvalue, k.predictionpricefrom, k.predictionpriceto, k.furthestprice, k.patternclassid FROM relevance_keylevels_results p INNER JOIN keylevels_results k ON p.resultuid = k.resultuid INNER JOIN autochartist_stocklist asl ON k.symbolid = asl.symbolid WHERE k.patternclassid in (1, 2) AND asl.enabled = 1 AND asl.recognitionengine ILIKE 'ATFX - 1';
Date: 2024-11-13 19:54:42 Duration: 145ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
18 0ms 51ms 3ms 18,015 1m select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Nov 13 19 18,015 1m 3ms [ User: postgres - Total duration: 1m - Times executed: 18015 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m - Times executed: 18015 ]
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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 = 'WMT.US' OR dss.downloadersymbol = 'WMT.US') AND dss.enabled = 1;
Date: 2024-11-13 19:30:05 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 = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'AUDUSD' OR dss.downloadersymbol = 'AUDUSD') AND dss.enabled = 1;
Date: 2024-11-13 19:30:05 Duration: 32ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT s.symbolid AS id, s.symbol AS name, s.exchange AS exchange, s.timegranularity AS interval, dtt.timezone AS timezone FROM symbols s INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid WHERE bsl.brokerid = '529' AND ('0' = 0 OR s.timegranularity = '0') AND (s.symbol = 'GBPCHF' OR dss.downloadersymbol = 'GBPCHF') AND dss.enabled = 1;
Date: 2024-11-13 19:00:06 Duration: 30ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
19 0ms 31ms 2ms 497 1s239ms select * from powerstatslatestprfprice (?, ?);Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Nov 13 19 497 1s239ms 2ms [ User: postgres - Total duration: 1s239ms - Times executed: 497 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s220ms - Times executed: 491 ]
[ Application: [unknown] - Total duration: 18ms - Times executed: 6 ]
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select * from PowerStatsLatestPRFPrice ('515840233449464300', '15');
Date: 2024-11-13 19:54:55 Duration: 31ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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select * from PowerStatsLatestPRFPrice ('515840243252176300', '15');
Date: 2024-11-13 19:24:59 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
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select * from PowerStatsLatestPRFPrice ('500991627549886200', '15');
Date: 2024-11-13 19:16:52 Duration: 5ms Database: acaweb_fx User: postgres Remote: 192.168.0.239 Application: PostgreSQL JDBC Driver Bind query: yes
20 0ms 35ms 1ms 21,085 28s958ms 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 #20
Day Hour Count Duration Avg duration Nov 13 19 21,085 28s958ms 1ms [ User: postgres - Total duration: 28s958ms - Times executed: 21085 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 28s958ms - Times executed: 21085 ]
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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 = '515840243250333300';
Date: 2024-11-13 19:00:03 Duration: 35ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT DISTINCT ON (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) 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 = '515840243158623300';
Date: 2024-11-13 19:30:05 Duration: 27ms 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 = '515840243255822300';
Date: 2024-11-13 19:00:02 Duration: 26ms Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 1s23ms 3,427 0ms 17ms 0ms SELECT ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Nov 13 19 3,427 1s23ms 0ms [ User: postgres - Total duration: 6s205ms - Times executed: 3427 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 6s125ms - Times executed: 2775 ]
[ Application: [unknown] - Total duration: 80ms - Times executed: 652 ]
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SELECT ;
Date: 2024-11-13 19:30:05 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
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SELECT ;
Date: 2024-11-13 19:30:05 Duration: 11ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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SELECT ;
Date: 2024-11-13 19:30:04 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
2 850ms 1,071 0ms 5ms 0ms WITH rar_max as ( ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 19 1,071 850ms 0ms [ User: postgres - Total duration: 33m59s - Times executed: 1071 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 33m59s - Times executed: 1071 ]
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WITH rar_max as ( ;
Date: 2024-11-13 19:40:09 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
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WITH rar_max as ( ;
Date: 2024-11-13 19:59:20 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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WITH rar_max as ( ;
Date: 2024-11-13 19:40:15 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
3 720ms 2,870 0ms 16ms 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 #3
Day Hour Count Duration Avg duration 19 2,870 720ms 0ms [ User: postgres - Total duration: 5s765ms - Times executed: 2870 ]
[ Application: [unknown] - Total duration: 5s765ms - Times executed: 2870 ]
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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: 2024-11-13 19:00:08 Duration: 16ms 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: 2024-11-13 19:24:37 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2024-11-13 19:55:46 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
4 676ms 628 0ms 1ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 19 628 676ms 1ms [ User: postgres - Total duration: 669ms - Times executed: 628 ]
[ Application: [unknown] - Total duration: 669ms - Times executed: 628 ]
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2024-11-13 19:30:06 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2024-11-13 19:41:13 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2024-11-13 19:25:31 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
5 250ms 2,864 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 19 2,864 250ms 0ms [ User: postgres - Total duration: 1s389ms - Times executed: 2864 ]
[ Application: [unknown] - Total duration: 1s389ms - Times executed: 2864 ]
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2024-11-13 19:10:32 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2024-11-13 19:40:03 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2024-11-13 19:41:29 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
6 150ms 1,488 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 19 1,488 150ms 0ms [ User: postgres - Total duration: 560ms - Times executed: 1488 ]
[ Application: [unknown] - Total duration: 560ms - Times executed: 1488 ]
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2024-11-13 19:10:34 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2024-11-13 19:10:58 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2024-11-13 19:11:02 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
7 78ms 501 0ms 12ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 19 501 78ms 0ms [ User: postgres - Total duration: 4ms - Times executed: 501 ]
[ Application: [unknown] - Total duration: 4ms - Times executed: 501 ]
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SET extra_float_digits = 3;
Date: 2024-11-13 19:00:05 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
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SET extra_float_digits = 3;
Date: 2024-11-13 19:40:09 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
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SET extra_float_digits = 3;
Date: 2024-11-13 19:30:03 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
8 57ms 12 4ms 5ms 4ms with sym_info as ( ;Times Reported Time consuming prepare #8
Day Hour Count Duration Avg duration 19 12 57ms 4ms [ User: postgres - Total duration: 14s778ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14s778ms - Times executed: 12 ]
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with sym_info as ( ;
Date: 2024-11-13 19:36:47 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
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with sym_info as ( ;
Date: 2024-11-13 19:51:46 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
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with sym_info as ( ;
Date: 2024-11-13 19:07:08 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
9 49ms 1,203 0ms 2ms 0ms select 1;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 19 1,203 49ms 0ms [ User: postgres - Total duration: 5ms - Times executed: 1203 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 5ms - Times executed: 1203 ]
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select 1;
Date: 2024-11-13 19:30:03 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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select 1;
Date: 2024-11-13 19:45:03 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
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select 1;
Date: 2024-11-13 19:00:04 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
10 39ms 45 0ms 3ms 0ms WITH last_candle AS ( ;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 19 45 39ms 0ms [ User: postgres - Total duration: 19s333ms - Times executed: 45 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 19s333ms - Times executed: 45 ]
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WITH last_candle AS ( ;
Date: 2024-11-13 19:00:14 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
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WITH last_candle AS ( ;
Date: 2024-11-13 19:00:14 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
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WITH last_candle AS ( ;
Date: 2024-11-13 19:16:00 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
11 37ms 18 1ms 2ms 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 #11
Day Hour Count Duration Avg duration 19 18 37ms 2ms [ User: postgres - Total duration: 25ms - Times executed: 18 ]
[ Application: [unknown] - Total duration: 25ms - Times executed: 18 ]
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select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2024-11-13 19:00:03 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
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select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2024-11-13 19:30:03 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
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select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2024-11-13 19:11:00 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
12 18ms 172 0ms 0ms 0ms INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 19 172 18ms 0ms [ User: postgres - Total duration: 71ms - Times executed: 172 ]
[ Application: [unknown] - Total duration: 71ms - Times executed: 172 ]
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INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2024-11-13 19:10:58 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2024-11-13 19:10:40 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2024-11-13 19:11:12 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
13 16ms 6 2ms 3ms 2ms 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 #13
Day Hour Count Duration Avg duration 19 6 16ms 2ms [ User: postgres - Total duration: 11ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 11ms - Times executed: 6 ]
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select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2024-11-13 19:50:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
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select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2024-11-13 19:00:04 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
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select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2024-11-13 19:30:05 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
14 15ms 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 #14
Day Hour Count Duration Avg duration 19 6 15ms 2ms [ User: postgres - Total duration: 33s631ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 33s631ms - 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: 2024-11-13 19:00:02 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: 2024-11-13 19:50:02 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: 2024-11-13 19:30:02 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
15 14ms 24 0ms 0ms 0ms select count(*) from datafeed_restarter_events where is_current_entry = 1;Times Reported Time consuming prepare #15
Day Hour Count Duration Avg duration 19 24 14ms 0ms [ User: postgres - Total duration: 55ms - Times executed: 24 ]
[ Application: [unknown] - Total duration: 55ms - Times executed: 24 ]
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2024-11-13 19:30:01 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: 2024-11-13 19:55:00 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: 2024-11-13 19:30:01 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
16 7ms 89 0ms 0ms 0ms INSERT INTO mt4datafeederrors (datafeedname, eventtimestamp, errordescription, status, serveraddress, username) values ($1, current_timestamp, $2, $3, $4, $5);Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 19 89 7ms 0ms [ User: postgres - Total duration: 7ms - Times executed: 89 ]
[ Application: [unknown] - Total duration: 7ms - Times executed: 89 ]
-
INSERT INTO mt4datafeederrors (datafeedname, eventtimestamp, errordescription, status, serveraddress, username) values ($1, current_timestamp, $2, $3, $4, $5);
Date: 2024-11-13 19:02:29 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.205
-
INSERT INTO mt4datafeederrors (datafeedname, eventtimestamp, errordescription, status, serveraddress, username) values ($1, current_timestamp, $2, $3, $4, $5);
Date: 2024-11-13 19:47:53 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.205
-
INSERT INTO mt4datafeederrors (datafeedname, eventtimestamp, errordescription, status, serveraddress, username) values ($1, current_timestamp, $2, $3, $4, $5);
Date: 2024-11-13 19:32:32 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.205
17 4ms 475 0ms 0ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 19 475 4ms 0ms [ User: postgres - Total duration: 4ms - Times executed: 475 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 4ms - Times executed: 475 ]
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2024-11-13 19:58:32 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2024-11-13 19:40:15 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2024-11-13 19:45:03 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
18 4ms 9 0ms 0ms 0ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 19 9 4ms 0ms [ User: postgres - Total duration: 0ms - Times executed: 9 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 0ms - Times executed: 9 ]
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2024-11-13 19:23:25 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2024-11-13 19:28:25 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2024-11-13 19:54:08 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
19 3ms 4 0ms 0ms 0ms select distinct replace(recognitionengine, ' ', '_') || '%' || replace(datetimeupdate::text, ' ', '_') as t from latest_candle_datetime_per_receng order by t;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 19 4 3ms 0ms [ User: postgres - Total duration: 0ms - Times executed: 4 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 4 ]
-
select distinct replace(recognitionengine, ' ', '_') || '%' || replace(datetimeupdate::text, ' ', '_') as t from latest_candle_datetime_per_receng order by t;
Date: 2024-11-13 19:10:05 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
-
select distinct replace(recognitionengine, ' ', '_') || '%' || replace(datetimeupdate::text, ' ', '_') as t from latest_candle_datetime_per_receng order by t;
Date: 2024-11-13 19:10:07 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select distinct replace(recognitionengine, ' ', '_') || '%' || replace(datetimeupdate::text, ' ', '_') as t from latest_candle_datetime_per_receng order by t;
Date: 2024-11-13 19:40:06 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
20 3ms 4 0ms 0ms 0ms select *, ;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 19 4 3ms 0ms [ User: postgres - Total duration: 0ms - Times executed: 4 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 0ms - Times executed: 4 ]
-
select *, ;
Date: 2024-11-13 19:12:32 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.16
-
select *, ;
Date: 2024-11-13 19:12:32 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.16
-
select *, ;
Date: 2024-11-13 19:12:32 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.16
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 18s756ms 42,188 0ms 25ms 0ms SELECT ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Nov 13 19 42,188 18s756ms 0ms [ User: postgres - Total duration: 1m31s - Times executed: 42188 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m31s - Times executed: 41536 ]
[ Application: [unknown] - Total duration: 80ms - Times executed: 652 ]
-
SELECT ;
Date: 2024-11-13 19:30:05 Duration: 25ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529', $3 = '515840249452611300'
-
SELECT ;
Date: 2024-11-13 19:30:04 Duration: 24ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '515840243241002300'
-
SELECT ;
Date: 2024-11-13 19:30:05 Duration: 22ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '0', $3 = '0', $4 = 'GBPAUD', $5 = 'GBPAUD'
2 11s705ms 2,833 0ms 35ms 4ms WITH rar_max as ( ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 19 2,833 11s705ms 4ms [ User: postgres - Total duration: 42m37s - Times executed: 2833 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 36m38s - Times executed: 2773 ]
[ Application: [unknown] - Total duration: 5m58s - Times executed: 60 ]
-
WITH rar_max as ( ;
Date: 2024-11-13 19:59:20 Duration: 35ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = 't', $2 = '538', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '127', $14 = 'ANGLO', $15 = 'BARC', $16 = 'BAY', $17 = 'BPLON', $18 = 'HSBCL', $19 = 'LLOY', $20 = 'RIO', $21 = 'RollsRoyce', $22 = 'TESCO', $23 = 'VOD', $24 = 'AUDCAD', $25 = 'AUDCHF', $26 = 'AUDJPY', $27 = 'AUDNZD', $28 = 'AUDUSD', $29 = 'CADCHF', $30 = 'CADJPY', $31 = 'CHFJPY', $32 = 'EURAUD', $33 = 'EURCAD', $34 = 'EURCHF', $35 = 'EURDKK', $36 = 'EURGBP', $37 = 'EURHUF', $38 = 'EURJPY', $39 = 'EURNOK', $40 = 'EURNZD', $41 = 'EURPLN', $42 = 'EURUSD', $43 = 'GBPAUD', $44 = 'GBPCAD', $45 = 'GBPCHF', $46 = 'GBPJPY', $47 = 'GBPNZD', $48 = 'GBPUSD', $49 = 'GBPZAR', $50 = 'NZDCAD', $51 = 'NZDCHF', $52 = 'NZDJPY', $53 = 'NZDUSD', $54 = 'USDCAD', $55 = 'USDCHF', $56 = 'USDCNH', $57 = 'USDCZK', $58 = 'USDDKK', $59 = 'USDHKD', $60 = 'USDHUF', $61 = 'USDJPY', $62 = 'USDMXN', $63 = 'USDNOK', $64 = 'USDPLN', $65 = 'USDRUB', $66 = 'USDSEK', $67 = 'USDSGD', $68 = 'USDTRY', $69 = 'USDZAR', $70 = 'XAGEUR', $71 = 'XAGUSD', $72 = 'XAUEUR', $73 = 'XAUUSD', $74 = 'ZARJPY', $75 = 'Cocoa', $76 = 'Coffee', $77 = 'Copper', $78 = 'Palladium', $79 = 'Platinum', $80 = 'Sugar', $81 = 'UKOIL', $82 = 'USOIL', $83 = 'AUS200', $84 = 'FRA40', $85 = 'JPN225', $86 = 'NETH25', $87 = 'SPA35', $88 = 'SUI20', $89 = 'UK100', $90 = 'USA100', $91 = 'USA30', $92 = 'USDIndex', $93 = 'ALCOA', $94 = 'ALIBABA', $95 = 'AMAZON', $96 = 'AMEX', $97 = 'APPLE', $98 = 'BBVA', $99 = 'BOA', $100 = 'BOEING', $101 = 'CHEVRON', $102 = 'CISCO', $103 = 'COKE', $104 = 'EBAY', $105 = 'GE', $106 = 'GOOGLE', $107 = 'GS', $108 = 'HLT', $109 = 'IBM', $110 = 'ILMN', $111 = 'INTEL', $112 = 'Iberdrola', $113 = 'MCARD', $114 = 'MCDON', $115 = 'META', $116 = 'MSFT', $117 = 'Mapfre', $118 = 'Netflix', $119 = 'PFIZER', $120 = 'QCOM', $121 = 'Santander', $122 = 'TEVA', $123 = 'Telefonica', $124 = 'Tesla', $125 = 'AUDUSD', $126 = 'EURGBP', $127 = 'EURUSD', $128 = 'GBPUSD', $129 = 'NZDUSD', $130 = 'USDCAD', $131 = 'USDCHF', $132 = 'USDJPY', $133 = 'AIRFKLM', $134 = 'Adidas', $135 = 'Bayer', $136 = 'Daimler', $137 = 'Danone', $138 = 'LVMH', $139 = 'Lufthansa', $140 = 'Volksw', $141 = '0', $142 = '', $143 = '0', $144 = '0', $145 = '0', $146 = '400', $147 = '400', $148 = 't', $149 = '10', $150 = '10'
-
WITH rar_max as ( ;
Date: 2024-11-13 19:04:32 Duration: 30ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = 't', $2 = '538', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '127', $14 = 'ANGLO', $15 = 'BARC', $16 = 'BAY', $17 = 'BPLON', $18 = 'HSBCL', $19 = 'LLOY', $20 = 'RIO', $21 = 'RollsRoyce', $22 = 'TESCO', $23 = 'VOD', $24 = 'AUDCAD', $25 = 'AUDCHF', $26 = 'AUDJPY', $27 = 'AUDNZD', $28 = 'AUDUSD', $29 = 'CADCHF', $30 = 'CADJPY', $31 = 'CHFJPY', $32 = 'EURAUD', $33 = 'EURCAD', $34 = 'EURCHF', $35 = 'EURDKK', $36 = 'EURGBP', $37 = 'EURHUF', $38 = 'EURJPY', $39 = 'EURNOK', $40 = 'EURNZD', $41 = 'EURPLN', $42 = 'EURUSD', $43 = 'GBPAUD', $44 = 'GBPCAD', $45 = 'GBPCHF', $46 = 'GBPJPY', $47 = 'GBPNZD', $48 = 'GBPUSD', $49 = 'GBPZAR', $50 = 'NZDCAD', $51 = 'NZDCHF', $52 = 'NZDJPY', $53 = 'NZDUSD', $54 = 'USDCAD', $55 = 'USDCHF', $56 = 'USDCNH', $57 = 'USDCZK', $58 = 'USDDKK', $59 = 'USDHKD', $60 = 'USDHUF', $61 = 'USDJPY', $62 = 'USDMXN', $63 = 'USDNOK', $64 = 'USDPLN', $65 = 'USDRUB', $66 = 'USDSEK', $67 = 'USDSGD', $68 = 'USDTRY', $69 = 'USDZAR', $70 = 'XAGEUR', $71 = 'XAGUSD', $72 = 'XAUEUR', $73 = 'XAUUSD', $74 = 'ZARJPY', $75 = 'Cocoa', $76 = 'Coffee', $77 = 'Copper', $78 = 'Palladium', $79 = 'Platinum', $80 = 'Sugar', $81 = 'UKOIL', $82 = 'USOIL', $83 = 'AUS200', $84 = 'FRA40', $85 = 'JPN225', $86 = 'NETH25', $87 = 'SPA35', $88 = 'SUI20', $89 = 'UK100', $90 = 'USA100', $91 = 'USA30', $92 = 'USDIndex', $93 = 'ALCOA', $94 = 'ALIBABA', $95 = 'AMAZON', $96 = 'AMEX', $97 = 'APPLE', $98 = 'BBVA', $99 = 'BOA', $100 = 'BOEING', $101 = 'CHEVRON', $102 = 'CISCO', $103 = 'COKE', $104 = 'EBAY', $105 = 'GE', $106 = 'GOOGLE', $107 = 'GS', $108 = 'HLT', $109 = 'IBM', $110 = 'ILMN', $111 = 'INTEL', $112 = 'Iberdrola', $113 = 'MCARD', $114 = 'MCDON', $115 = 'META', $116 = 'MSFT', $117 = 'Mapfre', $118 = 'Netflix', $119 = 'PFIZER', $120 = 'QCOM', $121 = 'Santander', $122 = 'TEVA', $123 = 'Telefonica', $124 = 'Tesla', $125 = 'AUDUSD', $126 = 'EURGBP', $127 = 'EURUSD', $128 = 'GBPUSD', $129 = 'NZDUSD', $130 = 'USDCAD', $131 = 'USDCHF', $132 = 'USDJPY', $133 = 'AIRFKLM', $134 = 'Adidas', $135 = 'Bayer', $136 = 'Daimler', $137 = 'Danone', $138 = 'LVMH', $139 = 'Lufthansa', $140 = 'Volksw', $141 = '0', $142 = '', $143 = '0', $144 = '0', $145 = '0', $146 = '400', $147 = '400', $148 = 't', $149 = '10', $150 = '10'
-
WITH rar_max as ( ;
Date: 2024-11-13 19:43:58 Duration: 30ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '538', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '127', $13 = 'ANGLO', $14 = 'BARC', $15 = 'BAY', $16 = 'BPLON', $17 = 'HSBCL', $18 = 'LLOY', $19 = 'RIO', $20 = 'RollsRoyce', $21 = 'TESCO', $22 = 'VOD', $23 = 'AUDCAD', $24 = 'AUDCHF', $25 = 'AUDJPY', $26 = 'AUDNZD', $27 = 'AUDUSD', $28 = 'CADCHF', $29 = 'CADJPY', $30 = 'CHFJPY', $31 = 'EURAUD', $32 = 'EURCAD', $33 = 'EURCHF', $34 = 'EURDKK', $35 = 'EURGBP', $36 = 'EURHUF', $37 = 'EURJPY', $38 = 'EURNOK', $39 = 'EURNZD', $40 = 'EURPLN', $41 = 'EURUSD', $42 = 'GBPAUD', $43 = 'GBPCAD', $44 = 'GBPCHF', $45 = 'GBPJPY', $46 = 'GBPNZD', $47 = 'GBPUSD', $48 = 'GBPZAR', $49 = 'NZDCAD', $50 = 'NZDCHF', $51 = 'NZDJPY', $52 = 'NZDUSD', $53 = 'USDCAD', $54 = 'USDCHF', $55 = 'USDCNH', $56 = 'USDCZK', $57 = 'USDDKK', $58 = 'USDHKD', $59 = 'USDHUF', $60 = 'USDJPY', $61 = 'USDMXN', $62 = 'USDNOK', $63 = 'USDPLN', $64 = 'USDRUB', $65 = 'USDSEK', $66 = 'USDSGD', $67 = 'USDTRY', $68 = 'USDZAR', $69 = 'XAGEUR', $70 = 'XAGUSD', $71 = 'XAUEUR', $72 = 'XAUUSD', $73 = 'ZARJPY', $74 = 'Cocoa', $75 = 'Coffee', $76 = 'Copper', $77 = 'Palladium', $78 = 'Platinum', $79 = 'Sugar', $80 = 'UKOIL', $81 = 'USOIL', $82 = 'AUS200', $83 = 'FRA40', $84 = 'JPN225', $85 = 'NETH25', $86 = 'SPA35', $87 = 'SUI20', $88 = 'UK100', $89 = 'USA100', $90 = 'USA30', $91 = 'USDIndex', $92 = 'ALCOA', $93 = 'ALIBABA', $94 = 'AMAZON', $95 = 'AMEX', $96 = 'APPLE', $97 = 'BBVA', $98 = 'BOA', $99 = 'BOEING', $100 = 'CHEVRON', $101 = 'CISCO', $102 = 'COKE', $103 = 'EBAY', $104 = 'GE', $105 = 'GOOGLE', $106 = 'GS', $107 = 'HLT', $108 = 'IBM', $109 = 'ILMN', $110 = 'INTEL', $111 = 'Iberdrola', $112 = 'MCARD', $113 = 'MCDON', $114 = 'META', $115 = 'MSFT', $116 = 'Mapfre', $117 = 'Netflix', $118 = 'PFIZER', $119 = 'QCOM', $120 = 'Santander', $121 = 'TEVA', $122 = 'Telefonica', $123 = 'Tesla', $124 = 'AUDUSD', $125 = 'EURGBP', $126 = 'EURUSD', $127 = 'GBPUSD', $128 = 'NZDUSD', $129 = 'USDCAD', $130 = 'USDCHF', $131 = 'USDJPY', $132 = 'AIRFKLM', $133 = 'Adidas', $134 = 'Bayer', $135 = 'Daimler', $136 = 'Danone', $137 = 'LVMH', $138 = 'Lufthansa', $139 = 'Volksw', $140 = '400', $141 = '400', $142 = 't', $143 = '10', $144 = '10'
3 965ms 628 1ms 4ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 19 628 965ms 1ms [ User: postgres - Total duration: 669ms - Times executed: 628 ]
[ Application: [unknown] - Total duration: 669ms - Times executed: 628 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2024-11-13 19:15:04 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'AXIORY'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2024-11-13 19:00:22 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'GO_MARKETS'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2024-11-13 19:25:31 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = 'FPMARKETS'
4 530ms 5,976 0ms 0ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 19 5,976 530ms 0ms [ User: postgres - Total duration: 7s303ms - Times executed: 5976 ]
[ Application: [unknown] - Total duration: 7s303ms - Times executed: 5976 ]
-
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: 2024-11-13 19:55:52 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2024-11-13 19:30:00', $2 = '1.95962', $3 = '1.95997', $4 = '1.95939', $5 = '1.95951', $6 = '2044', $7 = '515840230476629300', $8 = '0', $9 = '2024-11-13 19:55:52.334', $10 = '2024-11-13 19:55:52.289', $11 = '1.95962', $12 = '1.95997', $13 = '1.95939', $14 = '1.95951', $15 = '2044', $16 = '0', $17 = '2024-11-13 19:55:52.334', $18 = '2024-11-13 19:55:52.289'
-
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: 2024-11-13 19:57:34 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2024-11-13 20:30:00', $2 = '38895', $3 = '38969', $4 = '38891', $5 = '38949', $6 = '1131', $7 = '515840249388737300', $8 = '0', $9 = '2024-11-13 19:57:34.529', $10 = '2024-11-13 19:57:34.494', $11 = '38895', $12 = '38969', $13 = '38891', $14 = '38949', $15 = '1131', $16 = '0', $17 = '2024-11-13 19:57:34.529', $18 = '2024-11-13 19:57:34.494'
-
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: 2024-11-13 19:55:34 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2024-11-13 19:30:00', $2 = '111.063', $3 = '111.147', $4 = '111.063', $5 = '111.134', $6 = '1000', $7 = '515840245865875300', $8 = '0', $9 = '2024-11-13 19:55:34.321', $10 = '2024-11-13 19:55:34.138', $11 = '111.063', $12 = '111.147', $13 = '111.063', $14 = '111.134', $15 = '1000', $16 = '0', $17 = '2024-11-13 19:55:34.321', $18 = '2024-11-13 19:55:34.138'
5 515ms 89 4ms 12ms 5ms WITH last_candle AS ( ;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 19 89 515ms 5ms [ User: postgres - Total duration: 34s471ms - Times executed: 89 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 34s471ms - Times executed: 89 ]
-
WITH last_candle AS ( ;
Date: 2024-11-13 19:00:14 Duration: 12ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2024-11-13 19:00:14 Duration: 11ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2024-11-13 19:00:06 Duration: 8ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '538', $2 = '538'
6 488ms 29,208 0ms 11ms 0ms select 1;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 19 29,208 488ms 0ms [ User: postgres - Total duration: 148ms - Times executed: 29208 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 147ms - Times executed: 29136 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 72 ]
-
select 1;
Date: 2024-11-13 19:30:04 Duration: 11ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145
-
select 1;
Date: 2024-11-13 19:30:05 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
select 1;
Date: 2024-11-13 19:30:06 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
7 338ms 12 27ms 28ms 28ms with sym_info as ( ;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 19 12 338ms 28ms [ User: postgres - Total duration: 14s778ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14s778ms - Times executed: 12 ]
-
with sym_info as ( ;
Date: 2024-11-13 19:36:47 Duration: 28ms 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: 2024-11-13 19:07:12 Duration: 28ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'
-
with sym_info as ( ;
Date: 2024-11-13 19:07:08 Duration: 28ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '627', $2 = 'Forex', $3 = 'Forex', $4 = '627', $5 = 'Forex', $6 = '627', $7 = '627', $8 = 'Forex', $9 = '627'
8 216ms 3,008 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 #8
Day Hour Count Duration Avg duration 19 3,008 216ms 0ms [ User: postgres - Total duration: 1s461ms - Times executed: 3008 ]
[ Application: [unknown] - Total duration: 1s461ms - Times executed: 3008 ]
-
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: 2024-11-13 19:40:03 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2024-11-13 19:00:00', $2 = '162.1', $3 = '162.45', $4 = '161.98', $5 = '162.15', $6 = '426', $7 = '515840247929431300', $8 = '0', $9 = '2024-11-13 19:40:03.226', $10 = '2024-11-13 19:40:03.144', $11 = '162.1', $12 = '162.45', $13 = '161.98', $14 = '162.15', $15 = '426', $16 = '0', $17 = '2024-11-13 19:40:03.226', $18 = '2024-11-13 19:40:03.144'
-
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: 2024-11-13 19:10:32 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2024-11-13 18:30:00', $2 = '4.10393', $3 = '4.11023', $4 = '4.10333', $5 = '4.10793', $6 = '2213', $7 = '515840247873808300', $8 = '0', $9 = '2024-11-13 19:10:32.412', $10 = '2024-11-13 19:10:32.347', $11 = '4.10393', $12 = '4.11023', $13 = '4.10333', $14 = '4.10793', $15 = '2213', $16 = '0', $17 = '2024-11-13 19:10:32.412', $18 = '2024-11-13 19:10:32.347'
-
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: 2024-11-13 19:41:29 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2024-11-13 19:00:00', $2 = '44138.4', $3 = '44206.4', $4 = '44125.4', $5 = '44146.4', $6 = '2971', $7 = '515840248000726300', $8 = '0', $9 = '2024-11-13 19:41:29.922', $10 = '2024-11-13 19:41:29.864', $11 = '44138.4', $12 = '44206.4', $13 = '44125.4', $14 = '44146.4', $15 = '2971', $16 = '0', $17 = '2024-11-13 19:41:29.922', $18 = '2024-11-13 19:41:29.864'
9 142ms 183 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 #9
Day Hour Count Duration Avg duration 19 183 142ms 0ms [ User: postgres - Total duration: 550ms - Times executed: 183 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 537ms - Times executed: 180 ]
[ Application: [unknown] - Total duration: 13ms - Times executed: 3 ]
-
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: 2024-11-13 19:29:28 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '558', $2 = 'XAUEUR', $3 = '558'
-
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2024-11-13 19:00:19 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42 parameters: $1 = '538', $2 = 'GBPCAD', $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: 2024-11-13 19:59:28 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '558', $2 = 'XAUEUR', $3 = '558'
10 131ms 1,607 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 #10
Day Hour Count Duration Avg duration 19 1,607 131ms 0ms [ User: postgres - Total duration: 616ms - Times executed: 1607 ]
[ Application: [unknown] - Total duration: 616ms - Times executed: 1607 ]
-
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: 2024-11-13 19:10:58 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2024-11-13 17:00:00', $2 = '223.22', $3 = '224.48', $4 = '223.2', $5 = '224.4', $6 = '14748', $7 = '515840247917405300', $8 = '0', $9 = '2024-11-13 19:10:58.65', $10 = '2024-11-13 19:10:58.608', $11 = '223.22', $12 = '224.48', $13 = '223.2', $14 = '224.4', $15 = '14748', $16 = '0', $17 = '2024-11-13 19:10:58.65', $18 = '2024-11-13 19:10:58.608'
-
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: 2024-11-13 19:11:02 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2024-11-13 17:00:00', $2 = '387.15', $3 = '388.69', $4 = '386.79', $5 = '388.67', $6 = '1394', $7 = '515840247889020300', $8 = '0', $9 = '2024-11-13 19:11:02.733', $10 = '2024-11-13 19:11:02.666', $11 = '387.15', $12 = '388.69', $13 = '386.79', $14 = '388.67', $15 = '1394', $16 = '0', $17 = '2024-11-13 19:11:02.733', $18 = '2024-11-13 19:11:02.666'
-
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: 2024-11-13 19:10:34 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142 parameters: $1 = '2024-11-13 18:00:00', $2 = '2605.33', $3 = '2605.89', $4 = '2584.62', $5 = '2585.73', $6 = '15979', $7 = '515840247906886300', $8 = '0', $9 = '2024-11-13 19:10:34.507', $10 = '2024-11-13 19:10:34.447', $11 = '2605.33', $12 = '2605.89', $13 = '2584.62', $14 = '2585.73', $15 = '15979', $16 = '0', $17 = '2024-11-13 19:10:34.507', $18 = '2024-11-13 19:10:34.447'
11 100ms 9 10ms 13ms 11ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #11
Day Hour Count Duration Avg duration 19 9 100ms 11ms [ User: postgres - Total duration: 0ms - Times executed: 9 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 0ms - Times executed: 9 ]
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2024-11-13 19:23:25 Duration: 13ms 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: 2024-11-13 19:28:25 Duration: 13ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '489', $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: 2024-11-13 19:57:36 Duration: 12ms 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'
12 88ms 8 0ms 27ms 11ms with wh_patitioned as ( ;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 19 8 88ms 11ms [ User: postgres - Total duration: 277ms - Times executed: 8 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 277ms - Times executed: 8 ]
-
with wh_patitioned as ( ;
Date: 2024-11-13 19:32:14 Duration: 27ms 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: 2024-11-13 19:30:00 Duration: 24ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
-
with wh_patitioned as ( ;
Date: 2024-11-13 19:12:53 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.135 parameters: $1 = '529', $2 = '529', $3 = '529', $4 = '529', $5 = '529', $6 = '529', $7 = '529', $8 = '529', $9 = '529'
13 33ms 9 3ms 5ms 3ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 19 9 33ms 3ms [ User: postgres - Total duration: 1s201ms - Times executed: 9 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s201ms - Times executed: 9 ]
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2024-11-13 19:19:39 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2024-11-13 19:11:26 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '627', $2 = '627'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2024-11-13 19:35:47 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '538', $2 = '538'
14 31ms 452 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 #14
Day Hour Count Duration Avg duration 19 452 31ms 0ms [ User: postgres - Total duration: 36ms - Times executed: 452 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 36ms - Times executed: 452 ]
-
/*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: 2024-11-13 19:16:35 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '605085526550429301'
-
/*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: 2024-11-13 19:04:34 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42 parameters: $1 = '605085088803019301'
-
/*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: 2024-11-13 19:28:01 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '605085528147696301'
15 30ms 1 30ms 30ms 30ms with maxwhid as ( ;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 19 1 30ms 30ms [ User: postgres - Total duration: 40ms - Times executed: 1 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 40ms - Times executed: 1 ]
-
with maxwhid as ( ;
Date: 2024-11-13 19:12:43 Duration: 30ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.223 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'
16 26ms 12 0ms 4ms 2ms (( SELECT /*CPRelevantList*/ distinct 0 as patterntype, ar.resultuid as resultuid, rar.age, rar.relevant FROM autochartist_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid inner join symbols s on s.symbolid = bsl.symbolid inner join relevance_autochartist_results rar on rar.resultuid = ar.resultuid where bsl.brokerid = $1 union select distinct 0 as patterntype, ar.resultuid as resultuid, 0, 1 from autochartist_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = $2 inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_autochartist_results order by resultuid desc limit 1))) union all (( SELECT distinct 1 as patterntype, ar.resultuid as resultuid, rar.age, rar.relevant FROM fibonacci_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid inner join symbols s on s.symbolid = bsl.symbolid inner join relevance_fibonacci_results rar on rar.resultuid = ar.resultuid where bsl.brokerid = $3 union select distinct 1 as patterntype, ar.resultuid as resultuid, 0, 1 from fibonacci_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = $4 inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_fibonacci_results order by resultuid desc limit 1))) union all (( SELECT distinct 2 as patterntype, ar.resultuid as resultuid, rar.age, rar.relevant FROM keylevels_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid inner join symbols s on s.symbolid = bsl.symbolid inner join relevance_keylevels_results rar on rar.resultuid = ar.resultuid where bsl.brokerid = $5 union select distinct 2 as patterntype, ar.resultuid as resultuid, 0, 1 from keylevels_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = $6 inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1)));Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 19 12 26ms 2ms [ User: postgres - Total duration: 996ms - Times executed: 12 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 996ms - Times executed: 12 ]
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(( SELECT /*CPRelevantList*/ distinct 0 as patterntype, ar.resultuid as resultuid, rar.age, rar.relevant FROM autochartist_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid inner join symbols s on s.symbolid = bsl.symbolid inner join relevance_autochartist_results rar on rar.resultuid = ar.resultuid where bsl.brokerid = $1 union select distinct 0 as patterntype, ar.resultuid as resultuid, 0, 1 from autochartist_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = $2 inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_autochartist_results order by resultuid desc limit 1))) union all (( SELECT distinct 1 as patterntype, ar.resultuid as resultuid, rar.age, rar.relevant FROM fibonacci_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid inner join symbols s on s.symbolid = bsl.symbolid inner join relevance_fibonacci_results rar on rar.resultuid = ar.resultuid where bsl.brokerid = $3 union select distinct 1 as patterntype, ar.resultuid as resultuid, 0, 1 from fibonacci_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = $4 inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_fibonacci_results order by resultuid desc limit 1))) union all (( SELECT distinct 2 as patterntype, ar.resultuid as resultuid, rar.age, rar.relevant FROM keylevels_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid inner join symbols s on s.symbolid = bsl.symbolid inner join relevance_keylevels_results rar on rar.resultuid = ar.resultuid where bsl.brokerid = $5 union select distinct 2 as patterntype, ar.resultuid as resultuid, 0, 1 from keylevels_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = $6 inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1)));
Date: 2024-11-13 19:36:26 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '529', $2 = '529', $3 = '529', $4 = '529', $5 = '529', $6 = '529'
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(( SELECT /*CPRelevantList*/ distinct 0 as patterntype, ar.resultuid as resultuid, rar.age, rar.relevant FROM autochartist_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid inner join symbols s on s.symbolid = bsl.symbolid inner join relevance_autochartist_results rar on rar.resultuid = ar.resultuid where bsl.brokerid = $1 union select distinct 0 as patterntype, ar.resultuid as resultuid, 0, 1 from autochartist_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = $2 inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_autochartist_results order by resultuid desc limit 1))) union all (( SELECT distinct 1 as patterntype, ar.resultuid as resultuid, rar.age, rar.relevant FROM fibonacci_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid inner join symbols s on s.symbolid = bsl.symbolid inner join relevance_fibonacci_results rar on rar.resultuid = ar.resultuid where bsl.brokerid = $3 union select distinct 1 as patterntype, ar.resultuid as resultuid, 0, 1 from fibonacci_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = $4 inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_fibonacci_results order by resultuid desc limit 1))) union all (( SELECT distinct 2 as patterntype, ar.resultuid as resultuid, rar.age, rar.relevant FROM keylevels_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid inner join symbols s on s.symbolid = bsl.symbolid inner join relevance_keylevels_results rar on rar.resultuid = ar.resultuid where bsl.brokerid = $5 union select distinct 2 as patterntype, ar.resultuid as resultuid, 0, 1 from keylevels_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = $6 inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1)));
Date: 2024-11-13 19:06:25 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '529', $2 = '529', $3 = '529', $4 = '529', $5 = '529', $6 = '529'
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(( SELECT /*CPRelevantList*/ distinct 0 as patterntype, ar.resultuid as resultuid, rar.age, rar.relevant FROM autochartist_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid inner join symbols s on s.symbolid = bsl.symbolid inner join relevance_autochartist_results rar on rar.resultuid = ar.resultuid where bsl.brokerid = $1 union select distinct 0 as patterntype, ar.resultuid as resultuid, 0, 1 from autochartist_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = $2 inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_autochartist_results order by resultuid desc limit 1))) union all (( SELECT distinct 1 as patterntype, ar.resultuid as resultuid, rar.age, rar.relevant FROM fibonacci_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid inner join symbols s on s.symbolid = bsl.symbolid inner join relevance_fibonacci_results rar on rar.resultuid = ar.resultuid where bsl.brokerid = $3 union select distinct 1 as patterntype, ar.resultuid as resultuid, 0, 1 from fibonacci_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = $4 inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_fibonacci_results order by resultuid desc limit 1))) union all (( SELECT distinct 2 as patterntype, ar.resultuid as resultuid, rar.age, rar.relevant FROM keylevels_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid inner join symbols s on s.symbolid = bsl.symbolid inner join relevance_keylevels_results rar on rar.resultuid = ar.resultuid where bsl.brokerid = $5 union select distinct 2 as patterntype, ar.resultuid as resultuid, 0, 1 from keylevels_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = $6 inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1)));
Date: 2024-11-13 19:51:26 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '529', $2 = '529', $3 = '529', $4 = '529', $5 = '529', $6 = '529'
17 24ms 335 0ms 0ms 0ms /*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 19 335 24ms 0ms [ User: postgres - Total duration: 19ms - Times executed: 335 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 19ms - Times executed: 335 ]
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/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;
Date: 2024-11-13 19:28:24 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '605082696938916303'
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/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;
Date: 2024-11-13 19:59:31 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.239 parameters: $1 = '605085303084696303'
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/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;
Date: 2024-11-13 19:23:43 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.239 parameters: $1 = '605085184792077303'
18 24ms 184 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 19 184 24ms 0ms [ User: postgres - Total duration: 505ms - Times executed: 184 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 505ms - Times executed: 184 ]
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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: 2024-11-13 19:33:13 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '515840233956590300'
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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: 2024-11-13 19:23:43 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.239 parameters: $1 = '500991628237571200'
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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: 2024-11-13 19:28:35 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '515840243194971300'
19 21ms 6 3ms 4ms 3ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 19 6 21ms 3ms [ User: postgres - Total duration: 33s631ms - Times executed: 6 ]
[ Application: [unknown] - Total duration: 33s631ms - 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: 2024-11-13 19:00:02 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2024-11-13 19:50:02 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2024-11-13 19:30:02 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.90
20 20ms 604 0ms 0ms 0ms SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 19 604 20ms 0ms [ User: postgres - Total duration: 18ms - Times executed: 604 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 18ms - Times executed: 604 ]
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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: 2024-11-13 19:18:19 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42 parameters: $1 = '515840243917260300'
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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: 2024-11-13 19:33:13 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.239 parameters: $1 = '500991628237571200'
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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: 2024-11-13 19:30:23 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '515840243152332300'
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Events
Log levels
Key values
- 342,586 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 0 ERROR entries
- 0 WARNING entries
Errors per 5 minutes
NO DATASET
Most Frequent Errors/Events
Key values
- 0 Max number of times the same event was reported
- 0 Total events found
Rank Times reported Error NO DATASET