-
Global information
- Generated on Wed Mar 1 10:00:57 2023
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2023-03-01_110000.log, ..., /home/postgres/pg_data/data/pg_log/postgresql-2023-03-01_115429.log
- Parsed 2,062,122 log entries in 1m55s
- Log start from 2023-03-01 11:00:00 to 2023-03-01 12:00:00
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Overview
Global Stats
- 471 Number of unique normalized queries
- 216,867 Number of queries
- 5d2h45s Total query duration
- 2023-03-01 11:00:00 First query
- 2023-03-01 12:00:00 Last query
- 1,418 queries/s at 2023-03-01 11:48:42 Query peak
- 5d2h45s Total query duration
- 1m5s Prepare/parse total duration
- 10m31s Bind total duration
- 5d1h49m8s Execute total duration
- 792 Number of events
- 9 Number of unique normalized events
- 350 Max number of times the same event was reported
- 0 Number of cancellation
- 885 Total number of automatic vacuums
- 50 Total number of automatic analyzes
- 260 Number temporary file
- 56.74 MiB Max size of temporary file
- 6.13 MiB Average size of temporary file
- 13,252 Total number of sessions
- 72 sessions at 2023-03-01 11:25:37 Session peak
- 7d22h41m36s Total duration of sessions
- 51s803ms Average duration of sessions
- 16 Average queries per session
- 33s145ms Average queries duration per session
- 18s657ms Average idle time per session
- 13,249 Total number of connections
- 71 connections/s at 2023-03-01 11:00:27 Connection peak
- 1 Total number of databases
SQL Traffic
Key values
- 1,418 queries/s Query Peak
- 2023-03-01 11:48:42 Date
SELECT Traffic
Key values
- 650 queries/s Query Peak
- 2023-03-01 11:37:22 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 1,404 queries/s Query Peak
- 2023-03-01 11:48:42 Date
Queries duration
Key values
- 5d2h45s Total query duration
Prepared queries ratio
Key values
- 0.00 Ratio of bind vs prepare
- 0.00 % Ratio between prepared and "usual" statements
General Activity
↑ Back to the top of the General Activity tableDay Hour Count Min duration Max duration Avg duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Mar 01 11 216,866 0ms 3h33m9s 2s22ms 27m6s 41m16s 4d10h33m29s 12 1 0ms 0ms 0ms 0ms 0ms 0ms Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Mar 01 11 138,427 26 342ms 13m17s 17m13s 35m54s 12 1 0 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Mar 01 11 45,923 5,436 4 24 7s285ms 57s170ms 2m7s 6m31s 12 0 0 0 0 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Mar 01 11 119,909 184,134 1.54 62.04% 12 0 1 1.00 0.00% Day Hour Count Average / Second Mar 01 11 13,249 3.68/s 12 0 0.00/s Day Hour Count Average Duration Average idle time Mar 01 11 13,252 51s803ms 18s710ms 12 0 0ms 0ms -
Connections
Established Connections
Key values
- 71 connections Connection Peak
- 2023-03-01 11:00:27 Date
Connections per database
Key values
- acaweb_fx Main Database
- 13,249 connections Total
Connections per user
Key values
- postgres Main User
- 13,249 connections Total
Connections per host
Key values
- 192.168.1.23 Main host with 3933 connections
- 13,249 Total connections
Host Count 105.27.154.74 1 127.0.0.1 122 172.10.1.90 22 192.168.0.216 166 192.168.0.239 271 192.168.0.42 2,150 192.168.1.135 103 192.168.1.145 15 192.168.1.20 22 192.168.1.201 3,164 192.168.1.23 3,933 192.168.1.239 55 192.168.1.25 118 192.168.1.250 482 192.168.1.44 713 192.168.1.45 78 192.168.2.126 129 192.168.2.182 12 192.168.2.205 24 192.168.2.82 48 192.168.3.199 90 192.168.4.137 1 192.168.4.142 1,186 192.168.4.150 20 192.168.4.238 16 192.168.4.38 1 192.168.4.98 184 [local] 123 -
Sessions
Simultaneous sessions
Key values
- 72 sessions Session Peak
- 2023-03-01 11:25:37 Date
Histogram of session times
Key values
- 9,295 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 13,252 sessions Total
Sessions per user
Key values
- postgres Main User
- 13,252 sessions Total
Sessions per host
Key values
- 192.168.1.23 Main Host
- 13,252 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 121 2h5m19s 1m2s 172.10.1.90 22 40s451ms 1s838ms 192.168.0.216 166 22m7s 7s999ms 192.168.0.23 1 14m58s 14m58s 192.168.0.239 271 2h21m53s 31s415ms 192.168.0.42 2,150 5h5m21s 8s521ms 192.168.1.135 103 2h42m58s 1m34s 192.168.1.145 14 4h3m5s 17m21s 192.168.1.20 21 5h53m56s 16m51s 192.168.1.201 3,164 2h35m42s 2s952ms 192.168.1.23 3,936 5h32m51s 5s74ms 192.168.1.239 55 504ms 9ms 192.168.1.25 118 4m11s 2s135ms 192.168.1.250 481 7h30m21s 56s177ms 192.168.1.44 713 35s153ms 49ms 192.168.1.45 78 2h21m27s 1m48s 192.168.2.126 129 24s948ms 193ms 192.168.2.182 12 2s624ms 218ms 192.168.2.205 23 2h14m40s 5m51s 192.168.2.82 48 2s864ms 59ms 192.168.3.199 90 4m8s 2s756ms 192.168.4.137 1 949ms 949ms 192.168.4.142 1,190 4d8h32m39s 5m16s 192.168.4.150 20 1d12h46m18s 1h50m18s 192.168.4.238 16 6s503ms 406ms 192.168.4.38 1 38s169ms 38s169ms 192.168.4.98 184 20m13s 6s597ms [local] 124 5h46m46s 2m47s -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 3,861 buffers Checkpoint Peak
- 2023-03-01 11:26:20 Date
- 210.464 seconds Highest write time
- 314.957 seconds Sync time
Checkpoints Wal files
Key values
- 30 files Wal files usage Peak
- 2023-03-01 11:21:50 Date
Checkpoints distance
Key values
- 950.17 Mo Distance Peak
- 2023-03-01 11:21:50 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Mar 01 11 17,565 1,848.89s 397.67s 2,263.823s 12 0 0s 0s 0s Day Hour Added Removed Recycled Synced files Longest sync Average sync Mar 01 11 0 0 62 2,215 78.222s 1.598s 12 0 0 0 0 0s 0s Day Hour Count Avg time (sec) Mar 01 11 0 0s 12 0 0s Day Hour Mean distance Mean estimate Mar 01 11 101,268.80 kB 320,394.20 kB 12 0.00 kB 0.00 kB -
Temporary Files
Size of temporary files
Key values
- 52.32 MiB Temp Files size Peak
- 2023-03-01 11:40:36 Date
Number of temporary files
Key values
- 5 per second Temp Files Peak
- 2023-03-01 11:00:39 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Mar 01 11 260 1.56 GiB 6.13 MiB 12 0 0 0 Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 69 303.98 MiB 2.66 MiB 7.93 MiB 4.41 MiB with rar_max as ( ;-
WITH rar_max as ( ;
Date: 2023-03-01 11:54:40 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver
2 52 202.35 MiB 3.68 MiB 4.22 MiB 3.89 MiB select distinct a.resultuid as ruid, c.symbolid as sid, c.symbol as sym, c.longname as longname, c.shortname, c.exchange as e, c.timegranularity as tg, p.patternid as pid, a.direction as d, cast(atbaridentified as timestamp) as pet, cast(patternstarttime as timestamp) as pst, patternprice as patp, breakoutprice as pe, breakoutbars as be, errormargin as erm, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, cast(x0 as timestamp) as x0, cast(x1 as timestamp) as x1, cast(x2 as timestamp) as x2, cast(( case when x3 = ? then ? else x3 end) as timestamp) as x3, cast(( case when x4 = ? then ? else x4 end) as timestamp) as x4, cast(( case when x5 = ? then ? else x5 end) as timestamp) as x5, cast(( case when x6 = ? then ? else x6 end) as timestamp) as x6, cast(( case when x7 = ? then ? else x7 end) as timestamp) as x7, cast(( case when x8 = ? then ? else x8 end) as timestamp) as x8, cast(( case when x9 = ? then ? else x9 end) as timestamp) as x9, cast(atbaridentified as timestamp) as patternendtime, cast(atbaridentified as timestamp) as atbar, cast(( case when approachingtimestamp = ? then ? else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzos, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as relevant, cast(?.? as double precision) as premium, cast(? as bigint) as instrumentid, ? as derivativeid, ? as underlyingid, ? as isunderlying from symbols c inner join brokersymbollist b on c.symbolid = b.symbolid inner join symbolgroup sg on c.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = c.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join keylevels_results a on a.symbolid = c.symbolid inner join hrspatterns p on a.patternid = p.patternid left outer join relevance_keylevels_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and patternclassid = ? and patternlengthbars >= ? and a.patternid & ? > ? and dftt.dayofweek = ? and a.qtytp >= ? and a.resultuid > ? and c.nonliquid = ? and c.deleted = ? and dss.enabled = ? order by relevant desc, age asc, patternendtime desc, qtp desc limit ?;-
/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 622 AND sg.groupid = 515852059853768308 AND patternclassid = '1' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '1653660799' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:17:01 Duration: 1m7s Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 621 AND sg.groupid = 515852059852088308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '-936617313' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:11:42 Duration: 1m1s Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 622 AND sg.groupid = 515852059853768308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '1329650799' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:12:08 Duration: 1m Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver
3 36 575.03 MiB 2.81 MiB 56.74 MiB 15.97 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: 2023-03-01 11:11:02 Duration: 59s729ms Database: acaweb_fx User: postgres Remote: 192.168.1.25 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: 2023-03-01 11:20:43 Duration: 40s157ms Database: acaweb_fx User: postgres Remote: 192.168.1.25 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: 2023-03-01 11:00:39 Duration: 36s733ms Database: acaweb_fx User: postgres Remote: 192.168.1.25 Application: [unknown]
4 15 64.38 MiB 4.23 MiB 4.31 MiB 4.29 MiB select distinct patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, longname, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as relevant from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join autochartist_results a on a.symbolid = s.symbolid inner join patterns p on a.pattern = p.patternname left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and (((s.symbol ilike ? and timegranularity <= ?);-
/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 667 AND (((s.symbol ilike '%gbpnzd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:55:33 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.239 Application: PostgreSQL JDBC Driver
5 10 159.75 MiB 15.91 MiB 16.00 MiB 15.97 MiB select distinct patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, longname, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as relevant from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join autochartist_results a on a.symbolid = s.symbolid inner join patterns p on a.pattern = p.patternname left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and (((s.symbol ilike ? and timegranularity = ?);-
/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 538 AND (((s.symbol ilike '%gbpusd%' AND timegranularity = 240);
Date: 2023-03-01 11:54:42 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver
6 4 48.29 MiB 11.56 MiB 12.41 MiB 12.07 MiB select s.symbolid, s.symbol, s.timegranularity, dss.classname, dss.downloadersymbol, min(t.pricedatetime) as min_pricedatetime, max(t.pricedatetime) as max_pricedatetime, max(t.high), min(t.low) from symbols s, downloadersymbolsettings dss, t1440 t where s.nonliquid = ? and s.symbolid = dss.symbolid and dss.enabled = ? and t.symbolid = dss.symbolid and t.pricedatetime >= current_date - interval ? group by s.symbolid, s.symbol, s.timegranularity, dss.classname, dss.downloadersymbol having max(t.high) > min(t.low);-
select s.symbolid, s.symbol, s.timegranularity, dss.classname, dss.downloadersymbol, min(t.pricedatetime) as min_pricedatetime, max(t.pricedatetime) as max_pricedatetime, max(t.high), min(t.low) from symbols s, downloadersymbolsettings dss, t1440 t where s.nonliquid = 0 and s.symbolid = dss.symbolid and dss.enabled = 1 and t.symbolid = dss.symbolid and t.pricedatetime >= CURRENT_DATE - INTERVAL '1 year' group by s.symbolid, s.symbol, s.timegranularity, dss.classname, dss.downloadersymbol having max(t.high) > min(t.low);
Date: 2023-03-01 11:48:40 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.4.38 Application: [unknown]
7 4 14.09 MiB 3.52 MiB 3.53 MiB 3.52 MiB 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 (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;-
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 = $1 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 (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ($2 = 0 OR s.timegranularity in ($3, $4, $5, $6, $7, $8, $9)) AND ($10 = 0 OR s.exchange in ($11)) AND ($12 = 0 OR coalesce(bim.code, s.symbol) in ($13, $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, $235, $236, $237, $238, $239, $240, $241, $242, $243)) AND ($244 = 0 OR ccr.patternlengthbars <= $245)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $246 OR relevant = 1) AND ($247 = 0 OR age <= $248) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2023-03-01 11:27:42 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver
8 2 50.08 MiB 20.21 MiB 29.87 MiB 25.04 MiB select * from t15 t join downloadersymbolsettings dss on t.symbolid = dss.symbolid where classname ilike ? order by pricedatetime desc;-
select * from t15 t join downloadersymbolsettings dss on t.symbolid = dss.symbolid where classname ilike 'LEGACYFXMT5' order by pricedatetime desc;
Date: 2023-03-01 11:18:20 Duration: 9s155ms Database: acaweb_fx User: postgres Remote: 105.27.154.74 Application: PostgreSQL JDBC Driver
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select * from t15 t join downloadersymbolsettings dss on t.symbolid = dss.symbolid where classname ilike 'forex4you' order by pricedatetime desc;
Date: 2023-03-01 11:20:53 Duration: 6s249ms Database: acaweb_fx User: postgres Remote: 105.27.154.74 Application: PostgreSQL JDBC Driver
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select * from t15 t join downloadersymbolsettings dss on t.symbolid = dss.symbolid where classname ilike 'LEGACYFXMT5' order by pricedatetime desc;
Date: 2023-03-01 11:20:44 Duration: 5s755ms Database: acaweb_fx User: postgres Remote: 105.27.154.74 Application: PostgreSQL JDBC Driver
9 1 9.60 MiB 9.60 MiB 9.60 MiB 9.60 MiB select * from t15 t join downloadersymbolsettings dss on t.symbolid = dss.symbolid;-
select * from t15 t join downloadersymbolsettings dss on t.symbolid = dss.symbolid;
Date: 2023-03-01 11:17:28 Duration: 0ms Database: acaweb_fx User: postgres Remote: 105.27.154.74 Application: PostgreSQL JDBC Driver
10 1 16.42 MiB 16.42 MiB 16.42 MiB 16.42 MiB from latest_t15_candle_view order by classname;-
from latest_t15_candle_view order by classname;
Date: 2023-03-01 11:42:01 Duration: 0ms Database: acaweb_fx User: postgres Remote: 105.27.154.74 Application: PostgreSQL JDBC Driver
11 1 3.52 MiB 3.52 MiB 3.52 MiB 3.52 MiB select distinct patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, longname, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as relevant from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join symbolgroup sg on s.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join autochartist_results a on a.symbolid = s.symbolid inner join patterns p on a.pattern = p.patternname left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and breakout = ? and patternlengthbars >= ? and patternquality >= ?.? and initialtrend >= ?.? and symmetry >= ?.? and noise <= ?.? and volumeincrease >= ?.? and temporarypattern = ? and patternid & ? > ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and a.resultuid > ? and s.nonliquid = ? and dftt.dayofweek = ? and ((rar.age is null and a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?)) or rar.age >= ?) order by relevant desc, age asc, patternendtime desc, patternquality desc limit ?;-
/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059758978308 AND breakout = - 1 AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 601556014865129301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 AND ((rar.age IS NULL AND a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1)) OR rar.age >= 1) ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:54:18 Duration: 1s421ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 700 AND sg.groupid = 515852059922449308 AND breakout = - 1 AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 AND ((rar.age IS NULL AND a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1)) OR rar.age >= 1) ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:36:23 Duration: 132ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 700 AND sg.groupid = 515852059922449308 AND breakout = - 1 AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 601555834583783301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 AND ((rar.age IS NULL AND a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1)) OR rar.age >= 1) ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:48:23 Duration: 70ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver
12 1 5.36 MiB 5.36 MiB 5.36 MiB 5.36 MiB 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 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 (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 <= ?)), 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_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 = $1 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 = $2 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 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 (kr.simulation = 0 OR kr.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)) AND ($15 = 0 OR p.patternname in ($16)) AND ($17 = 0 OR kr.patternclassid in ($18, $19)) AND ($20 = 0 OR kr.patternlengthbars <= $21)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $22 OR relevant = 1) AND ($23 = 0 OR age <= $24) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2023-03-01 11:42:23 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver
13 1 3.59 MiB 3.59 MiB 3.59 MiB 3.59 MiB select distinct patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, longname from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join symbolgroup sg on s.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join autochartist_results a on a.symbolid = s.symbolid inner join patterns p on a.pattern = p.patternname where b.brokerid = ? and sg.groupid = ? and breakout = ? and patternlengthbars >= ? and patternquality >= ?.? and initialtrend >= ?.? and symmetry >= ?.? and noise <= ?.? and volumeincrease >= ?.? and temporarypattern = ? and patternid & ? > ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and a.resultuid > ? and s.nonliquid = ? and dftt.dayofweek = ? order by patternendtime desc, patternquality desc limit ?;-
/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname WHERE b.brokerid = 529 AND sg.groupid = 515852059758978308 AND breakout = - 1 AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:54:38 Duration: 17s992ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname WHERE b.brokerid = 529 AND sg.groupid = 515852059709228308 AND breakout = - 1 AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:54:32 Duration: 11s658ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname WHERE b.brokerid = 529 AND sg.groupid = 515852059714438308 AND breakout = - 1 AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:54:35 Duration: 8s480ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver
14 1 5.36 MiB 5.36 MiB 5.36 MiB 5.36 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 (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 (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, $235, $236, $237, $238, $239, $240, $241, $242, $243, $244)) AND ($245 = 0 OR fr.pattern in ($246)) AND ($247 = 0 OR fr.patternlengthbars <= $248) AND ($249 = 0 OR ($250 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($251 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $252 OR relevant = 1) AND ($253 = 0 OR age <= $254) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2023-03-01 11:54:06 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 56.74 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: 2023-03-01 11:50:25 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.25 - Application: [unknown] ]
2 40.57 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: 2023-03-01 11:20:43 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.25 - Application: [unknown] ]
3 32.73 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: 2023-03-01 11:20:37 ]
4 29.94 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: 2023-03-01 11:50:31 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.25 - Application: [unknown] ]
5 29.93 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: 2023-03-01 11:40:36 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.25 - Application: [unknown] ]
6 29.93 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: 2023-03-01 11:30:39 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.25 - Application: [unknown] ]
7 29.93 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: 2023-03-01 11:11:02 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.25 - Application: [unknown] ]
8 29.93 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: 2023-03-01 11:00:39 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.25 - Application: [unknown] ]
9 29.87 MiB select * from t15 t join downloadersymbolsettings dss on t.symbolid = dss.symbolid where classname ilike 'forex4you' order by pricedatetime desc;[ Date: 2023-03-01 11:20:47 - Database: acaweb_fx - User: postgres - Remote: 105.27.154.74 - Application: PostgreSQL JDBC Driver ]
10 28.37 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: 2023-03-01 11:40:34 ]
11 28.30 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2023-03-01 11:00:35 ]
12 24.00 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: 2023-03-01 11:30:33 ]
13 22.93 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: 2023-03-01 11:10:52 ]
14 20.23 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2023-03-01 11:10:54 - Database: acaweb_fx - User: postgres - Remote: 192.168.1.25 - Application: [unknown] ]
15 20.21 MiB select * from t15 t join downloadersymbolsettings dss on t.symbolid = dss.symbolid where classname ilike 'LEGACYFXMT5' order by pricedatetime desc;[ Date: 2023-03-01 11:18:20 - Database: acaweb_fx - User: postgres - Remote: 105.27.154.74 - Application: PostgreSQL JDBC Driver ]
16 19.10 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: 2023-03-01 11:20:40 ]
17 18.18 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: 2023-03-01 11:40:32 ]
18 16.42 MiB from latest_t15_candle_view order by classname;[ Date: 2023-03-01 11:42:01 - Database: acaweb_fx - User: postgres - Remote: 105.27.154.74 - Application: PostgreSQL JDBC Driver ]
19 16.00 MiB /*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 538 AND (((s.symbol ilike '%gbpusd%' AND timegranularity = 240);[ Date: 2023-03-01 11:46:33 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.42 - Application: PostgreSQL JDBC Driver ]
20 16.00 MiB /*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 538 AND (((s.symbol ilike '%gbpusd%' AND timegranularity = 240);[ Date: 2023-03-01 11:50:37 - Database: acaweb_fx - User: postgres - Remote: 192.168.0.42 - Application: PostgreSQL JDBC Driver ]
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Vacuums
Vacuums / Analyzes Distribution
Key values
- 0 sec Highest CPU-cost vacuum
Table
Database - Date
- 0 sec Highest CPU-cost analyze
Table
Database - Date
Analyzes per table
Key values
- public.solr_relevance_old (11) Main table analyzed (database acaweb_fx)
- 50 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 11 acaweb_fx.pg_catalog.pg_attribute 6 acaweb_fx.public.datafeeds_latestrun 5 acaweb_fx.pg_catalog.pg_class 3 acaweb_fx.pg_catalog.pg_type 3 acaweb_fx.public.relevance_bigmovement_results 3 acaweb_fx.pg_catalog.pg_index 2 acaweb_fx.public.autochartist_symbolupdates 2 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.public.latest_candle_datetime_per_receng 2 acaweb_fx.public.relevance_fibonacci_results 2 acaweb_fx.public.relevance_consecutivecandles_results 2 acaweb_fx.public.symbollatestupdatetime 2 acaweb_fx.public.solr_imports 1 acaweb_fx.pg_catalog.pg_namespace 1 acaweb_fx.pg_catalog.pg_depend 1 acaweb_fx.public.relevance_keylevels_results 1 acaweb_fx.public.roundnumber_increment 1 Total 50 Vacuums per table
Key values
- pg_toast.pg_toast_2619 (58) Main table vacuumed on database acaweb_fx
- 885 vacuums Total
Index Buffer usage Skipped WAL usage Table Vacuums scans hits misses dirtied pins frozen records full page bytes acaweb_fx.pg_toast.pg_toast_2619 58 0 9,965 0 42 0 0 16 7 58,723 acaweb_fx.public.relevance_consecutivecandles_results 58 0 3,641 0 15 0 0 9 2 17,719 acaweb_fx.public.relevance_bigmovement_results 58 0 9,719 0 9 1 0 11 2 17,993 acaweb_fx.pg_catalog.pg_index 57 3 3,536 0 63 0 0 36 3 21,531 acaweb_fx.public.datafeeds_latestrun 57 0 6,296 0 17 0 0 4 2 16,330 acaweb_fx.public.autochartist_symbolupdates 57 0 104,657 0 279 3 59,757 65 17 149,113 acaweb_fx.public.solr_imports 57 0 2,479 0 42 0 0 5 3 24,687 acaweb_fx.pg_catalog.pg_attribute 57 3 25,597 0 55 0 3,363 99 18 144,274 acaweb_fx.pg_catalog.pg_class 57 3 10,891 0 49 0 0 74 9 51,521 acaweb_fx.pg_catalog.pg_type 57 3 4,831 0 55 0 0 49 7 49,209 acaweb_fx.pg_catalog.pg_statistic 57 3 48,985 0 72 0 0 57 18 136,387 acaweb_fx.public.symbollatestupdatetime 57 0 51,239 0 283 0 2,793 37 10 87,583 acaweb_fx.public.relevance_fibonacci_results 53 0 23,276 0 44 40 0 48 8 73,034 acaweb_fx.public.solr_relevance_old 51 0 44,484 0 206 4 0 101 4 42,740 acaweb_fx.public.relevance_keylevels_results 50 0 60,812 0 52 116 0 46 4 42,501 acaweb_fx.public.latest_t15_candle_view 35 2 2,356 0 14 0 0 17 3 26,317 acaweb_fx.pg_catalog.pg_depend 7 2 903 0 92 0 406 89 50 302,042 acaweb_fx.public.roundnumber_increment 1 0 468 0 53 0 0 52 3 27,976 acaweb_fx_integer.public.fibonacci_results 1 1 32,511 0 44,016 0 0 74,136 40,416 249,976,084 Total 885 20 446,646 235,466 45,458 164 66,319 74,951 40,586 251,265,764 Tuples removed per table
Key values
- public.fibonacci_results (3211) Main table with removed tuples on database acaweb_fx_integer
- 3748 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx_integer.public.fibonacci_results 1 1 3,211 399,824 0 0 30,738 acaweb_fx.pg_catalog.pg_depend 7 2 345 90,046 17,436 0 812 acaweb_fx.pg_catalog.pg_attribute 57 3 84 1,093,784 648,191 0 22,542 acaweb_fx.public.latest_t15_candle_view 35 2 57 15,068 14,158 0 137 acaweb_fx.pg_catalog.pg_class 57 3 18 178,183 89,377 0 4,461 acaweb_fx.pg_catalog.pg_type 57 3 15 126,138 53,064 0 2,906 acaweb_fx.pg_catalog.pg_statistic 57 3 15 304,757 200,333 0 29,298 acaweb_fx.pg_catalog.pg_index 57 3 3 64,779 18,894 0 1,581 acaweb_fx.pg_toast.pg_toast_2619 58 0 0 34,470 24,378 0 6,664 acaweb_fx.public.datafeeds_latestrun 57 0 0 47,013 45,531 0 1,254 acaweb_fx.public.autochartist_symbolupdates 57 0 0 6,405,231 2,469,043 0 131,727 acaweb_fx.public.solr_imports 57 0 0 5,060 5,003 0 114 acaweb_fx.public.relevance_keylevels_results 50 0 0 1,725,258 899,830 0 26,231 acaweb_fx.public.roundnumber_increment 1 0 0 23,282 0 0 172 acaweb_fx.public.relevance_fibonacci_results 53 0 0 219,846 119,231 0 7,140 acaweb_fx.public.relevance_consecutivecandles_results 58 0 0 50,995 21,884 0 669 acaweb_fx.public.symbollatestupdatetime 57 0 0 6,208,662 2,132,821 0 48,564 acaweb_fx.public.relevance_bigmovement_results 58 0 0 272,877 167,438 0 3,990 acaweb_fx.public.solr_relevance_old 51 0 0 1,236,656 613,073 0 21,802 Total 885 20 3,748 18,501,929 7,539,685 0 340,802 Pages removed per table
Key values
- unknown (0) Main table with removed pages on database unknown
- 0 pages Total removed
Pages removed per tables
NO DATASET
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_toast.pg_toast_2619 58 0 0 0 acaweb_fx.pg_catalog.pg_index 57 3 3 0 acaweb_fx.public.datafeeds_latestrun 57 0 0 0 acaweb_fx.public.autochartist_symbolupdates 57 0 0 0 acaweb_fx.public.solr_imports 57 0 0 0 acaweb_fx.pg_catalog.pg_attribute 57 3 84 0 acaweb_fx.public.latest_t15_candle_view 35 2 57 0 acaweb_fx.pg_catalog.pg_depend 7 2 345 0 acaweb_fx.public.relevance_keylevels_results 50 0 0 0 acaweb_fx.pg_catalog.pg_class 57 3 18 0 acaweb_fx.public.roundnumber_increment 1 0 0 0 acaweb_fx.public.relevance_fibonacci_results 53 0 0 0 acaweb_fx.pg_catalog.pg_type 57 3 15 0 acaweb_fx.pg_catalog.pg_statistic 57 3 15 0 acaweb_fx.public.relevance_consecutivecandles_results 58 0 0 0 acaweb_fx.public.symbollatestupdatetime 57 0 0 0 acaweb_fx.public.relevance_bigmovement_results 58 0 0 0 acaweb_fx_integer.public.fibonacci_results 1 1 3211 0 acaweb_fx.public.solr_relevance_old 51 0 0 0 Total 885 20 3,748 0 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Mar 01 11 885 50 12 0 0 - 0 sec Highest CPU-cost vacuum
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Locks
Locks by types
Key values
- AccessExclusiveLock Main Lock Type
- 164 locks Total
Most frequent waiting queries (N)
Rank Count Total time Min time Max time Avg duration Query 1 53 4d6h46m48s 1s34ms 3h17m47s 1h56m21s 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 = ?;-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-03 09:00:00', '6.335', '6.335', '6.335', '6.335', '2', '600197227125639300', '0', '2023-03-01 08:40:22.766', '2023-03-01 08:40:22.766') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '6.335', high = '6.335', low = '6.335', close = '6.335', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:40:22.766', sastdatetimereceived = '2023-03-01 08:40:22.766';
Date: 2023-03-01 11:58:11 Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-12-02 09:00:00', '0', '0', '0', '0', '2', '500991632125453200', '0', '2023-03-01 08:41:12.178', '2023-03-01 08:41:12.177') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0', high = '0', low = '0', close = '0', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:41:12.178', sastdatetimereceived = '2023-03-01 08:41:12.177';
Date: 2023-03-01 11:58:11 Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-03 09:00:00', '25.88', '25.88', '25.88', '25.88', '2', '600197227405596300', '0', '2023-03-01 08:43:37.359', '2023-03-01 08:43:37.358') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '25.88', high = '25.88', low = '25.88', close = '25.88', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:43:37.359', sastdatetimereceived = '2023-03-01 08:43:37.358';
Date: 2023-03-01 11:58:11 Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
2 3 2m35s 5s618ms 2m20s 51s827ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;-
UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2023-03-01 10:00:00', reason = 'Pattern is too old to be relevant. PEIndex at 601 vs 612' WHERE uniqueIndex = '515840246471599300-1|44981.7917|44986.0833|44984.7083|44985.8333|22.84|21.42|21.37|20.94' and relevant = 1;
Date: 2023-03-01 11:23:09 Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2023-03-01 10:30:00', reason = 'Price has entered the prediction area for a completed pattern.' WHERE uniqueIndex = '|515840217887008300|23627.55|1|2023-03-01 06:30:00|1|1' and relevant = 1;
Date: 2023-03-01 11:23:09 Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2023-03-01 10:00:00', reason = 'Price has entered the prediction area for a completed pattern.' WHERE uniqueIndex = '|515840217871844300|4.7027|2|2023-03-01 06:30:00|-1|1' and relevant = 1;
Date: 2023-03-01 11:23:09 Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
3 2 53s402ms 15s756ms 37s646ms 26s701ms refresh materialized view concurrently latest_t15_candle_view;-
refresh materialized view concurrently latest_t15_candle_view;
Date: 2023-03-01 11:14:07 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: 2023-03-01 11:17:26 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: 2023-03-01 11:35:16 Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
4 7 7s1ms 1s 1s 1s select updateresultsmaterializedview ();-
select updateresultsmaterializedview ();
Date: 2023-03-01 11:22:55 Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2023-03-01 11:24:20 Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateresultsmaterializedview ();
Date: 2023-03-01 11:40:27 Database: acaweb_fx User: postgres Remote: [local] Application: psql
Queries that waited the most
Rank Wait time Query 1 3h17m47s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
2 3h16m58s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
3 3h14m33s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
4 3h13m58s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
5 3h12m23s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
6 3h11m20s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
7 3h8m57s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
8 3h8m8s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
9 2h57m51s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
10 2h57m37s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
11 2h57m6s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
12 2h56m42s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
13 2h55m44s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
14 2h55m39s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
15 2h54m14s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
16 2h47m13s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
17 2h42m36s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
18 2h27m54s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
19 2h27m18s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
20 2h26m37s 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: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] ]
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Queries
Queries by type
Key values
- 138,428 Total read queries
- 54,849 Total write queries
Queries by database
Key values
- acaweb_fx Main database
- 216,867 Requests
- 5d1h49m8s (acaweb_fx)
- Main time consuming database
Queries by user
Key values
- postgres Main user
- 216,867 Requests
User Request type Count Duration postgres Total 216,867 5d1h49m8s copy from 24 7s728ms copy to 26 2m59s cte 3,062 4h19m20s ddl 4 2s530ms delete 4 14ms insert 45,923 4d7h27m54s others 23,590 20m8s select 138,428 13h6m31s tcl 370 7s18ms update 5,436 31m56s Duration by user
Key values
- 5d1h49m8s (postgres) Main time consuming user
User Request type Count Duration postgres Total 216,867 5d1h49m8s copy from 24 7s728ms copy to 26 2m59s cte 3,062 4h19m20s ddl 4 2s530ms delete 4 14ms insert 45,923 4d7h27m54s others 23,590 20m8s select 138,428 13h6m31s tcl 370 7s18ms update 5,436 31m56s Queries by host
Key values
- 192.168.1.23 Main host
- 52,294 Requests
- 4d6h57m2s (192.168.4.142)
- Main time consuming host
Host Request type Count Duration 105.27.154.74 Total 29 27s70ms others 2 0ms select 27 27s70ms 127.0.0.1 Total 27,245 49m50s copy to 26 2m59s cte 8 2s104ms insert 20,941 25m59s others 78 1ms select 1,629 14m22s update 4,563 6m27s 172.10.1.90 Total 88 283ms others 44 5ms select 40 214ms update 4 62ms 182.165.1.42 Total 32 1s95ms select 32 1s95ms 192.168.0.216 Total 654 3m43s insert 5 3m41s others 322 29ms select 319 1s341ms update 8 93ms 192.168.0.23 Total 8,205 41m55s select 8,205 41m55s 192.168.0.236 Total 54 2s191ms cte 8 4ms select 46 2s187ms 192.168.0.239 Total 7,349 32m52s others 542 4ms select 6,807 32m52s 192.168.0.42 Total 21,854 2h58m45s cte 16 6s756ms insert 18 1s638ms others 4,300 41ms select 17,516 2h58m37s update 4 0ms 192.168.1.121 Total 4 0ms select 4 0ms 192.168.1.135 Total 2,488 46m33s cte 570 41m19s others 206 1ms select 1,712 5m13s 192.168.1.145 Total 1,439 59m cte 240 58m33s others 30 0ms select 1,169 27s156ms 192.168.1.20 Total 2,961 1h8m41s cte 263 1h8m17s others 44 0ms select 2,654 24s475ms 192.168.1.201 Total 41,767 41m7s cte 7 980ms insert 4 190ms others 6,328 64ms select 35,315 41m6s update 113 382ms 192.168.1.210 Total 18 202ms select 18 202ms 192.168.1.23 Total 52,294 1h56m27s cte 18 4s609ms insert 1 28ms others 7,866 73ms select 43,968 1h56m22s update 441 871ms 192.168.1.239 Total 220 262ms others 110 9ms select 110 252ms 192.168.1.25 Total 126 4m8s cte 6 3m54s others 8 0ms select 112 14s336ms 192.168.1.250 Total 17,274 1h16m27s cte 1,877 1h1m43s others 964 8ms select 14,433 14m44s 192.168.1.44 Total 2,500 3s315ms insert 357 2s815ms others 2,139 18ms select 4 481ms 192.168.1.45 Total 1,730 30m23s others 156 1ms select 1,574 30m23s 192.168.1.93 Total 2 74ms select 2 74ms 192.168.1.97 Total 54 2s146ms cte 8 3ms select 46 2s143ms 192.168.2.126 Total 147 17s444ms others 18 0ms select 129 17s444ms 192.168.2.182 Total 48 231ms others 24 2ms select 12 15ms update 12 213ms 192.168.2.205 Total 92 49s571ms insert 2 48s976ms others 44 4ms select 42 523ms update 4 67ms 192.168.2.82 Total 539 42s138ms insert 255 38s977ms others 96 9ms select 124 830ms update 64 2s320ms 192.168.3.199 Total 360 601ms others 180 16ms select 168 468ms update 12 116ms 192.168.4.137 Total 3 796ms cte 1 796ms others 2 0ms 192.168.4.142 Total 23,570 4d6h57m2s insert 21,407 4d6h56m40s select 2,163 22s212ms 192.168.4.150 Total 44 12m3s others 42 0ms select 2 12m3s 192.168.4.238 Total 48 3s248ms cte 16 3s247ms others 32 0ms 192.168.4.38 Total 2,940 35s839ms insert 2,933 826ms select 2 34s967ms tcl 5 46ms 192.168.4.98 Total 549 20m11s others 9 20m3s tcl 365 6s972ms update 175 909ms [local] Total 140 5h46m46s copy from 24 7s728ms cte 24 25m14s ddl 4 2s530ms delete 4 14ms others 4 4s483ms select 44 4h55m54s update 36 25m24s Queries by application
Key values
- PostgreSQL JDBC Driver Main application
- 147,355 Requests
- 4d8h14m23s ([unknown])
- Main time consuming application
Application Request type Count Duration PostgreSQL JDBC Driver Total 147,355 11h44m51s cte 3,008 3h50m9s insert 23 1s856ms others 10,284 97ms select 133,482 7h54m38s update 558 1s254ms [unknown] Total 68,199 4d8h14m23s cte 22 3m54s insert 45,543 4d7h27m50s others 12,589 20m3s select 4,846 15m58s tcl 370 7s18ms update 4,829 6m30s dreamfactory Total 1,074 3s303ms insert 357 2s815ms others 713 6ms select 4 481ms psql Total 239 5h49m50s copy from 24 7s728ms copy to 26 2m59s cte 32 25m16s ddl 4 2s530ms delete 4 14ms others 4 4s483ms select 96 4h55m55s update 49 25m24s Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2023-03-01 11:11:52 Date
Number of cancelled queries (5 minutes period)
NO DATASET
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Top Queries
Histogram of query times
Key values
- 139,753 0-1ms duration
Slowest individual queries
Rank Duration Query 1 3h33m9s select cleanupt30 (30, 20, 20);[ Date: 2023-03-01 11:58:10 - Database: acaweb_fx - User: postgres - Remote: [local] - Application: psql ]
2 3h17m48s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-03 09:00:00', '6.335', '6.335', '6.335', '6.335', '2', '600197227125639300', '0', '2023-03-01 08:40:22.766', '2023-03-01 08:40:22.766') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '6.335', high = '6.335', low = '6.335', close = '6.335', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:40:22.766', sastdatetimereceived = '2023-03-01 08:40:22.766';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
3 3h16m59s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-12-02 09:00:00', '0', '0', '0', '0', '2', '500991632125453200', '0', '2023-03-01 08:41:12.178', '2023-03-01 08:41:12.177') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0', high = '0', low = '0', close = '0', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:41:12.178', sastdatetimereceived = '2023-03-01 08:41:12.177';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
4 3h14m33s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-03 09:00:00', '25.88', '25.88', '25.88', '25.88', '2', '600197227405596300', '0', '2023-03-01 08:43:37.359', '2023-03-01 08:43:37.358') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '25.88', high = '25.88', low = '25.88', close = '25.88', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:43:37.359', sastdatetimereceived = '2023-03-01 08:43:37.358';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
5 3h13m59s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-03 09:00:00', '68.235', '68.235', '68.235', '68.235', '2', '600197227498029300', '0', '2023-03-01 08:44:11.768', '2023-03-01 08:44:11.767') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '68.235', high = '68.235', low = '68.235', close = '68.235', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:44:11.768', sastdatetimereceived = '2023-03-01 08:44:11.767';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
6 3h12m24s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-12-02 09:00:00', '0', '0', '0', '0', '2', '600530195219616300', '0', '2023-03-01 08:45:47.103', '2023-03-01 08:45:47.102') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0', high = '0', low = '0', close = '0', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:45:47.103', sastdatetimereceived = '2023-03-01 08:45:47.102';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
7 3h11m21s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-12-02 09:00:00', '0', '0', '0', '0', '2', '500991632154608200', '0', '2023-03-01 08:46:50.439', '2023-03-01 08:46:50.438') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0', high = '0', low = '0', close = '0', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:46:50.439', sastdatetimereceived = '2023-03-01 08:46:50.438';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
8 3h8m58s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-03 09:00:00', '29.49', '29.49', '29.49', '29.49', '2', '600197228057054300', '0', '2023-03-01 08:49:12.738', '2023-03-01 08:49:12.738') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '29.49', high = '29.49', low = '29.49', close = '29.49', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:49:12.738', sastdatetimereceived = '2023-03-01 08:49:12.738';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
9 3h8m9s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-12-02 09:00:00', '0', '0', '0', '0', '2', '500991632165553200', '0', '2023-03-01 08:50:02.086', '2023-03-01 08:50:02.085') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0', high = '0', low = '0', close = '0', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:50:02.086', sastdatetimereceived = '2023-03-01 08:50:02.085';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
10 2h57m52s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-12-02 09:00:00', '0', '0', '0', '0', '2', '600530195967866300', '0', '2023-03-01 09:00:19.05', '2023-03-01 09:00:19.032') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0', high = '0', low = '0', close = '0', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 09:00:19.05', sastdatetimereceived = '2023-03-01 09:00:19.032';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
11 2h57m38s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-14 09:00:00', '0', '0', '0', '0', '2', '600476165690462300', '0', '2023-03-01 09:00:32.653', '2023-03-01 09:00:32.651') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0', high = '0', low = '0', close = '0', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 09:00:32.653', sastdatetimereceived = '2023-03-01 09:00:32.651';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
12 2h57m7s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-27 09:00:00', '18.5905', '18.5905', '18.5905', '18.5905', '2', '600598083433347300', '0', '2023-03-01 09:01:03.82', '2023-03-01 09:01:03.82') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '18.5905', high = '18.5905', low = '18.5905', close = '18.5905', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 09:01:03.82', sastdatetimereceived = '2023-03-01 09:01:03.82';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
13 2h56m42s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-11-25 09:00:00', '0', '0', '0', '0', '2', '600670986156447300', '0', '2023-03-01 09:01:28.403', '2023-03-01 09:01:28.402') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0', high = '0', low = '0', close = '0', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 09:01:28.403', sastdatetimereceived = '2023-03-01 09:01:28.402';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
14 2h55m45s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-11-01 09:00:00', '0', '0.1866', '0', '0.1866', '4', '600875485895110300', '0', '2023-03-01 09:02:26.213', '2023-03-01 09:02:18.551') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0', high = '0.1866', low = '0', close = '0.1866', volume = '4', bsf = '0', sastdatetimewritten = '2023-03-01 09:02:26.213', sastdatetimereceived = '2023-03-01 09:02:18.551';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
15 2h55m40s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-11-01 10:00:00', '0', '556.75', '0', '0', '8', '600875485983930300', '0', '2023-03-01 09:02:30.877', '2023-03-01 09:02:24.241') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0', high = '556.75', low = '0', close = '0', volume = '8', bsf = '0', sastdatetimewritten = '2023-03-01 09:02:30.877', sastdatetimereceived = '2023-03-01 09:02:24.241';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
16 2h54m15s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-12-01 09:00:00', '0', '10.05', '0', '10.05', '4', '601045351762235300', '0', '2023-03-01 09:03:55.684', '2023-03-01 09:03:50.296') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0', high = '10.05', low = '0', close = '10.05', volume = '4', bsf = '0', sastdatetimewritten = '2023-03-01 09:03:55.684', sastdatetimereceived = '2023-03-01 09:03:50.296';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
17 2h47m14s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-03 09:00:00', '115.795', '115.795', '115.795', '115.795', '2', '600197225230525300', '0', '2023-03-01 09:10:57.019', '2023-03-01 09:10:57.018') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '115.795', high = '115.795', low = '115.795', close = '115.795', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 09:10:57.019', sastdatetimereceived = '2023-03-01 09:10:57.018';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
18 2h42m37s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-03 09:00:00', '28.955', '28.955', '28.955', '28.955', '2', '600197225797504300', '0', '2023-03-01 09:15:33.985', '2023-03-01 09:15:33.971') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '28.955', high = '28.955', low = '28.955', close = '28.955', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 09:15:33.985', sastdatetimereceived = '2023-03-01 09:15:33.971';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
19 2h27m55s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-11-04 09:00:00', '0', '0', '0', '0', '2', '500991632144278200', '0', '2023-03-01 09:30:16.44', '2023-03-01 09:30:16.438') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0', high = '0', low = '0', close = '0', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 09:30:16.44', sastdatetimereceived = '2023-03-01 09:30:16.438';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
20 2h27m19s INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-03 09:00:00', '25.39', '25.39', '25.39', '25.39', '2', '600197227590905300', '0', '2023-03-01 09:30:52.019', '2023-03-01 09:30:52.006') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '25.39', high = '25.39', low = '25.39', close = '25.39', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 09:30:52.019', sastdatetimereceived = '2023-03-01 09:30:52.006';[ Date: 2023-03-01 11:58:11 - Database: acaweb_fx - User: postgres - Remote: 192.168.4.142 - Application: [unknown] - Bind query: yes ]
Time consuming queries
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 4d6h50m16s 6,458 0ms 3h17m48s 57s326ms 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 #1
Day Hour Count Duration Avg duration Mar 01 11 6,458 4d6h50m16s 57s326ms [ User: postgres - Total duration: 4d6h50m16s - Times executed: 6458 ]
[ Application: [unknown] - Total duration: 4d6h50m16s - Times executed: 6458 ]
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-03 09:00:00', '6.335', '6.335', '6.335', '6.335', '2', '600197227125639300', '0', '2023-03-01 08:40:22.766', '2023-03-01 08:40:22.766') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '6.335', high = '6.335', low = '6.335', close = '6.335', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:40:22.766', sastdatetimereceived = '2023-03-01 08:40:22.766';
Date: 2023-03-01 11:58:11 Duration: 3h17m48s Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-12-02 09:00:00', '0', '0', '0', '0', '2', '500991632125453200', '0', '2023-03-01 08:41:12.178', '2023-03-01 08:41:12.177') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0', high = '0', low = '0', close = '0', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:41:12.178', sastdatetimereceived = '2023-03-01 08:41:12.177';
Date: 2023-03-01 11:58:11 Duration: 3h16m59s Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-03 09:00:00', '25.88', '25.88', '25.88', '25.88', '2', '600197227405596300', '0', '2023-03-01 08:43:37.359', '2023-03-01 08:43:37.358') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '25.88', high = '25.88', low = '25.88', close = '25.88', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:43:37.359', sastdatetimereceived = '2023-03-01 08:43:37.358';
Date: 2023-03-01 11:58:11 Duration: 3h14m33s Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
2 3h33m9s 1 3h33m9s 3h33m9s 3h33m9s select cleanupt30 (?, ?, ?);Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Mar 01 11 1 3h33m9s 3h33m9s [ User: postgres - Total duration: 3h33m9s - Times executed: 1 ]
[ Application: psql - Total duration: 3h33m9s - Times executed: 1 ]
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select cleanupt30 (30, 20, 20);
Date: 2023-03-01 11:58:10 Duration: 3h33m9s Database: acaweb_fx User: postgres Remote: [local] Application: psql
3 3h30m11s 4,685 0ms 1m7s 2s691ms select distinct a.resultuid as ruid, c.symbolid as sid, c.symbol as sym, c.longname as longname, c.shortname, c.exchange as e, c.timegranularity as tg, p.patternid as pid, a.direction as d, cast(atbaridentified as timestamp) as pet, cast(patternstarttime as timestamp) as pst, patternprice as patp, breakoutprice as pe, breakoutbars as be, errormargin as erm, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, cast(x0 as timestamp) as x0, cast(x1 as timestamp) as x1, cast(x2 as timestamp) as x2, cast(( case when x3 = ? then ? else x3 end) as timestamp) as x3, cast(( case when x4 = ? then ? else x4 end) as timestamp) as x4, cast(( case when x5 = ? then ? else x5 end) as timestamp) as x5, cast(( case when x6 = ? then ? else x6 end) as timestamp) as x6, cast(( case when x7 = ? then ? else x7 end) as timestamp) as x7, cast(( case when x8 = ? then ? else x8 end) as timestamp) as x8, cast(( case when x9 = ? then ? else x9 end) as timestamp) as x9, cast(atbaridentified as timestamp) as patternendtime, cast(atbaridentified as timestamp) as atbar, cast(( case when approachingtimestamp = ? then ? else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzos, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as relevant, cast(?.? as double precision) as premium, cast(? as bigint) as instrumentid, ? as derivativeid, ? as underlyingid, ? as isunderlying from symbols c inner join brokersymbollist b on c.symbolid = b.symbolid inner join symbolgroup sg on c.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = c.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join keylevels_results a on a.symbolid = c.symbolid inner join hrspatterns p on a.patternid = p.patternid left outer join relevance_keylevels_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and patternclassid = ? and patternlengthbars >= ? and a.patternid & ? > ? and dftt.dayofweek = ? and a.qtytp >= ? and a.resultuid > ? and c.nonliquid = ? and c.deleted = ? and dss.enabled = ? order by relevant desc, age asc, patternendtime desc, qtp desc limit ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Mar 01 11 4,685 3h30m11s 2s691ms [ User: postgres - Total duration: 3h30m11s - Times executed: 4685 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3h30m11s - Times executed: 4685 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 622 AND sg.groupid = 515852059853768308 AND patternclassid = '1' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '1653660799' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:17:01 Duration: 1m7s Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 621 AND sg.groupid = 515852059852088308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '-936617313' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:11:42 Duration: 1m1s Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 622 AND sg.groupid = 515852059853768308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '1329650799' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:12:08 Duration: 1m Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
4 2h2m33s 128 1s134ms 4m27s 57s449ms 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 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 (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 ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Mar 01 11 128 2h2m33s 57s449ms [ User: postgres - Total duration: 2h2m33s - Times executed: 128 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2h2m33s - Times executed: 128 ]
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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 = '529' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN 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 (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('31' = 0 OR coalesce(bim.code, s.symbol) in ('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURNZD', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'JPN225', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', 'XAGUSD', 'XAUUSD')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false ), 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: 2023-03-01 11:12:41 Duration: 4m27s 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 = '479' 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 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 (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 ('263' = 0 OR coalesce(bim.code, s.symbol) in ('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHFNOK', 'EURAUD', 'EURCAD', 'EURCHF', 'EURCZK', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPSEK', 'GBPUSD', 'HKDJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'PnL', 'SGDJPY', 'TRYJPY', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDZAR', 'ZARJPY', 'ACCOR', 'ADIDAS', 'AIR-LIQUIDE', 'AIRBUS-GRP', 'ALLIANZ', 'ALSTOM', 'ARCELORMITL', 'AXA', 'BASF', 'BAYER', 'BEIERSDORF', 'BMW', 'BNP-PARIBAS', 'BOUYGUES', 'CAP-GEMINI', 'CARREFOUR', 'CONTINENTAL', 'CREDIT-AGRI', 'DANONE', 'DEUT-BOERSE', 'DEUT-TELEKM', 'DEUTSCHE-BK', 'DEUTSCHPOST', 'E.ON', 'EDF', 'ENGIE', 'FRESENI-MED', 'FRESENIUS', 'HEIDBGCEMNT', 'HENKEL', 'INFINEONTEC', 'KERING', 'LANXESS', 'LEGRAND', 'LINDE', 'LOREAL', 'LUFTHANSA', 'LVMH', 'MERCK-KGAA', 'MICHELIN', 'MUNICH-RE', 'ORANGE', 'PERNOD-RICD', 'PUBLICIS-GR', 'RENAULT', 'RWE', 'SAFRAN', 'SAINTGOBAIN', 'SANOFI', 'SAP', 'SCHNEIDELEC', 'SIEMENS', 'SOCIETE-GEN', 'SOLVAY', 'THYSSENKRUP', 'TOTAL', 'VALEO', 'VEOLIA-ENV', 'VINCI', 'VIVENDI', 'VOLKSWAGEN', 'XAGUSD', 'XAUUSD', 'ESTOX', 'FRENCH40', 'GERMAN30', 'UK100', 'US30', 'US500', 'USNDX', '3M', '3i-GROUP', 'ADMIRAL', 'AIG', 'ALIBABA', 'AMAZON', 'AMEX', 'ANGLO-AMERI', 'ANTOFAGASTA', 'APPLE', 'ASHTEAD', 'ASTRAZENECA', 'AT&T', 'AVIVA', 'BABCOCK', 'BAE-SYSTEMS', 'BAIDU', 'BALFOUR-B', 'BARCLAYS', 'BARRAT', 'BATS', 'BHP-BILITON', 'BNK-AMER', 'BOEING', 'BP', 'BRIT-FOODS', 'BRIT-LND', 'BT', 'BUNZL', 'BURBERRY', 'CAPITA', 'CARNIVAL', 'CAT', 'CENTRICA', 'CHEVRON', 'CISCO', 'CITI', 'COMPASS', 'CRH', 'DIAGEO', 'DIRECT-LINE', 'DISNEY', 'DRAX', 'EASYJET', 'EBAY', 'EXPERIAN', 'EXXON', 'FACEBOOK', 'FEDEX', 'FERRARI', 'FORD', 'GE', 'GLAXO', 'GLENCORE', 'GM', 'GOLDMANS', 'HALLIBURTON', 'HAMMERSON', 'HOME-DEP', 'HP', 'HSBC', 'IAG', 'IBM', 'IG-GROUP', 'IHG', 'IMI', 'IMP-TOBACCO', 'INCHCAPE', 'INTEL', 'INTERTEK', 'ITV', 'JOHNSON', 'JOHNSON-MAT', 'JPMORGAN', 'KINGFISHER', 'LAND-SEC', 'LEGAL-GEN', 'LLOYDS', 'LSE', 'M&S', 'MAN-GROUP', 'MATCH', 'MERCK', 'META', 'MICROSOFT', 'MONDI', 'MORGAN-S', 'MSTRCARD', 'McD', 'NAT-GRID', 'NETFLIX', 'NEXT', 'NIKE', 'OCADO', 'ORACLE', 'P&G', 'PAYPAL', 'PEARSON', 'PENNON', 'PEPSI', 'PERSIMMON', 'PETROFAC', 'PFIZER', 'PHIL-MOR', 'PRUDENTIAL', 'REED-ELSVR', 'RENTOKIL', 'RIGHTMOVE', 'RIO-TINTO', 'ROLLS-ROYCE', 'SAGE', 'SAINSBURY', 'SCHLUMBERGR', 'SEVERN-TRNT', 'SMITH-NEPH', 'SMITHS', 'SQUARE-INC', 'SSE', 'ST-JAMES', 'STAN-CHARTD', 'STARBUX', 'TAYLOR-WIMP', 'TESCO', 'TESLA', 'THOMAS-COOK', 'TRAVELRS', 'TRAVIS-PERK', 'TUI', 'TULLOW', 'UNILEVER', 'UNITED-UTIL', 'UTD-HLTH', 'VERIZON', 'VISA', 'VODAFONE', 'WALMART', 'WEIR-GROUP', 'WELLS-FG', 'WHITBREAD', 'WPP')) 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 ), 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: 2023-03-01 11:26:22 Duration: 4m2s 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 ), 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 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 (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 ('231' = 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', 'EURHUF', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'GER_30', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHUF', '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', 'EURHUF', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHUF', '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', 'GER_30', '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 ), 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: 2023-03-01 11:24:19 Duration: 3m49s Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
5 1h15m16s 145 166ms 3m2s 31s149ms (( select distinct ? 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 = ? union select distinct ? as patterntype, ar.resultuid as resultuid, ?, ? from autochartist_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = ? inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?))) union all (( select distinct ? 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 = ? union select distinct ? as patterntype, ar.resultuid as resultuid, ?, ? from fibonacci_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = ? inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ?))) union all (( select distinct ? 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 = ? union select distinct ? as patterntype, ar.resultuid as resultuid, ?, ? from keylevels_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = ? inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?)));Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Mar 01 11 145 1h15m16s 31s149ms [ User: postgres - Total duration: 1h15m16s - Times executed: 145 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h15m16s - Times executed: 145 ]
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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 = '692' 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 = '692' 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 = '692' 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 = '692' 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 = '692' 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 = '692' inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1)));
Date: 2023-03-01 11:12:50 Duration: 3m2s Database: acaweb_fx User: postgres Remote: 192.168.1.45 Application: PostgreSQL JDBC Driver Bind query: yes
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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 = '692' 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 = '692' 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 = '692' 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 = '692' 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 = '692' 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 = '692' inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1)));
Date: 2023-03-01 11:36:05 Duration: 2m6s Database: acaweb_fx User: postgres Remote: 192.168.1.45 Application: PostgreSQL JDBC Driver Bind query: yes
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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 = '667' 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 = '667' 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 = '667' 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 = '667' 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 = '667' 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 = '667' inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1)));
Date: 2023-03-01 11:11:13 Duration: 1m58s Database: acaweb_fx User: postgres Remote: 192.168.0.239 Application: PostgreSQL JDBC Driver Bind query: yes
6 59m16s 2 27m34s 31m41s 29m38s select updateageforrelevantresults ();Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Mar 01 11 2 59m16s 29m38s [ User: postgres - Total duration: 59m16s - Times executed: 2 ]
[ Application: psql - Total duration: 59m16s - Times executed: 2 ]
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select updateageforrelevantresults ();
Date: 2023-03-01 11:18:44 Duration: 31m41s Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2023-03-01 11:59:36 Duration: 27m34s Database: acaweb_fx User: postgres Remote: [local] Application: psql
7 47m29s 128 536ms 2m34s 22s261ms 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 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 (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 <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Mar 01 11 128 47m29s 22s261ms [ User: postgres - Total duration: 47m29s - Times executed: 128 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 47m29s - Times executed: 128 ]
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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 = '479' 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 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 (kr.simulation = 0 OR kr.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 ('263' = 0 OR coalesce(bim.code, s.symbol) in ('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHFNOK', 'EURAUD', 'EURCAD', 'EURCHF', 'EURCZK', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPSEK', 'GBPUSD', 'HKDJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'PnL', 'SGDJPY', 'TRYJPY', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDZAR', 'ZARJPY', 'ACCOR', 'ADIDAS', 'AIR-LIQUIDE', 'AIRBUS-GRP', 'ALLIANZ', 'ALSTOM', 'ARCELORMITL', 'AXA', 'BASF', 'BAYER', 'BEIERSDORF', 'BMW', 'BNP-PARIBAS', 'BOUYGUES', 'CAP-GEMINI', 'CARREFOUR', 'CONTINENTAL', 'CREDIT-AGRI', 'DANONE', 'DEUT-BOERSE', 'DEUT-TELEKM', 'DEUTSCHE-BK', 'DEUTSCHPOST', 'E.ON', 'EDF', 'ENGIE', 'FRESENI-MED', 'FRESENIUS', 'HEIDBGCEMNT', 'HENKEL', 'INFINEONTEC', 'KERING', 'LANXESS', 'LEGRAND', 'LINDE', 'LOREAL', 'LUFTHANSA', 'LVMH', 'MERCK-KGAA', 'MICHELIN', 'MUNICH-RE', 'ORANGE', 'PERNOD-RICD', 'PUBLICIS-GR', 'RENAULT', 'RWE', 'SAFRAN', 'SAINTGOBAIN', 'SANOFI', 'SAP', 'SCHNEIDELEC', 'SIEMENS', 'SOCIETE-GEN', 'SOLVAY', 'THYSSENKRUP', 'TOTAL', 'VALEO', 'VEOLIA-ENV', 'VINCI', 'VIVENDI', 'VOLKSWAGEN', 'XAGUSD', 'XAUUSD', 'ESTOX', 'FRENCH40', 'GERMAN30', 'UK100', 'US30', 'US500', 'USNDX', '3M', '3i-GROUP', 'ADMIRAL', 'AIG', 'ALIBABA', 'AMAZON', 'AMEX', 'ANGLO-AMERI', 'ANTOFAGASTA', 'APPLE', 'ASHTEAD', 'ASTRAZENECA', 'AT&T', 'AVIVA', 'BABCOCK', 'BAE-SYSTEMS', 'BAIDU', 'BALFOUR-B', 'BARCLAYS', 'BARRAT', 'BATS', 'BHP-BILITON', 'BNK-AMER', 'BOEING', 'BP', 'BRIT-FOODS', 'BRIT-LND', 'BT', 'BUNZL', 'BURBERRY', 'CAPITA', 'CARNIVAL', 'CAT', 'CENTRICA', 'CHEVRON', 'CISCO', 'CITI', 'COMPASS', 'CRH', 'DIAGEO', 'DIRECT-LINE', 'DISNEY', 'DRAX', 'EASYJET', 'EBAY', 'EXPERIAN', 'EXXON', 'FACEBOOK', 'FEDEX', 'FERRARI', 'FORD', 'GE', 'GLAXO', 'GLENCORE', 'GM', 'GOLDMANS', 'HALLIBURTON', 'HAMMERSON', 'HOME-DEP', 'HP', 'HSBC', 'IAG', 'IBM', 'IG-GROUP', 'IHG', 'IMI', 'IMP-TOBACCO', 'INCHCAPE', 'INTEL', 'INTERTEK', 'ITV', 'JOHNSON', 'JOHNSON-MAT', 'JPMORGAN', 'KINGFISHER', 'LAND-SEC', 'LEGAL-GEN', 'LLOYDS', 'LSE', 'M&S', 'MAN-GROUP', 'MATCH', 'MERCK', 'META', 'MICROSOFT', 'MONDI', 'MORGAN-S', 'MSTRCARD', 'McD', 'NAT-GRID', 'NETFLIX', 'NEXT', 'NIKE', 'OCADO', 'ORACLE', 'P&G', 'PAYPAL', 'PEARSON', 'PENNON', 'PEPSI', 'PERSIMMON', 'PETROFAC', 'PFIZER', 'PHIL-MOR', 'PRUDENTIAL', 'REED-ELSVR', 'RENTOKIL', 'RIGHTMOVE', 'RIO-TINTO', 'ROLLS-ROYCE', 'SAGE', 'SAINSBURY', 'SCHLUMBERGR', 'SEVERN-TRNT', 'SMITH-NEPH', 'SMITHS', 'SQUARE-INC', 'SSE', 'ST-JAMES', 'STAN-CHARTD', 'STARBUX', 'TAYLOR-WIMP', 'TESCO', 'TESLA', 'THOMAS-COOK', 'TRAVELRS', 'TRAVIS-PERK', 'TUI', 'TULLOW', 'UNILEVER', 'UNITED-UTIL', 'UTD-HLTH', 'VERIZON', 'VISA', 'VODAFONE', 'WALMART', 'WEIR-GROUP', 'WELLS-FG', 'WHITBREAD', 'WPP')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.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: 2023-03-01 11:37:45 Duration: 2m34s Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = '479' 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 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 (kr.simulation = 0 OR kr.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 ('263' = 0 OR coalesce(bim.code, s.symbol) in ('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHFNOK', 'EURAUD', 'EURCAD', 'EURCHF', 'EURCZK', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPSEK', 'GBPUSD', 'HKDJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'PnL', 'SGDJPY', 'TRYJPY', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDZAR', 'ZARJPY', 'ACCOR', 'ADIDAS', 'AIR-LIQUIDE', 'AIRBUS-GRP', 'ALLIANZ', 'ALSTOM', 'ARCELORMITL', 'AXA', 'BASF', 'BAYER', 'BEIERSDORF', 'BMW', 'BNP-PARIBAS', 'BOUYGUES', 'CAP-GEMINI', 'CARREFOUR', 'CONTINENTAL', 'CREDIT-AGRI', 'DANONE', 'DEUT-BOERSE', 'DEUT-TELEKM', 'DEUTSCHE-BK', 'DEUTSCHPOST', 'E.ON', 'EDF', 'ENGIE', 'FRESENI-MED', 'FRESENIUS', 'HEIDBGCEMNT', 'HENKEL', 'INFINEONTEC', 'KERING', 'LANXESS', 'LEGRAND', 'LINDE', 'LOREAL', 'LUFTHANSA', 'LVMH', 'MERCK-KGAA', 'MICHELIN', 'MUNICH-RE', 'ORANGE', 'PERNOD-RICD', 'PUBLICIS-GR', 'RENAULT', 'RWE', 'SAFRAN', 'SAINTGOBAIN', 'SANOFI', 'SAP', 'SCHNEIDELEC', 'SIEMENS', 'SOCIETE-GEN', 'SOLVAY', 'THYSSENKRUP', 'TOTAL', 'VALEO', 'VEOLIA-ENV', 'VINCI', 'VIVENDI', 'VOLKSWAGEN', 'XAGUSD', 'XAUUSD', 'ESTOX', 'FRENCH40', 'GERMAN30', 'UK100', 'US30', 'US500', 'USNDX', '3M', '3i-GROUP', 'ADMIRAL', 'AIG', 'ALIBABA', 'AMAZON', 'AMEX', 'ANGLO-AMERI', 'ANTOFAGASTA', 'APPLE', 'ASHTEAD', 'ASTRAZENECA', 'AT&T', 'AVIVA', 'BABCOCK', 'BAE-SYSTEMS', 'BAIDU', 'BALFOUR-B', 'BARCLAYS', 'BARRAT', 'BATS', 'BHP-BILITON', 'BNK-AMER', 'BOEING', 'BP', 'BRIT-FOODS', 'BRIT-LND', 'BT', 'BUNZL', 'BURBERRY', 'CAPITA', 'CARNIVAL', 'CAT', 'CENTRICA', 'CHEVRON', 'CISCO', 'CITI', 'COMPASS', 'CRH', 'DIAGEO', 'DIRECT-LINE', 'DISNEY', 'DRAX', 'EASYJET', 'EBAY', 'EXPERIAN', 'EXXON', 'FACEBOOK', 'FEDEX', 'FERRARI', 'FORD', 'GE', 'GLAXO', 'GLENCORE', 'GM', 'GOLDMANS', 'HALLIBURTON', 'HAMMERSON', 'HOME-DEP', 'HP', 'HSBC', 'IAG', 'IBM', 'IG-GROUP', 'IHG', 'IMI', 'IMP-TOBACCO', 'INCHCAPE', 'INTEL', 'INTERTEK', 'ITV', 'JOHNSON', 'JOHNSON-MAT', 'JPMORGAN', 'KINGFISHER', 'LAND-SEC', 'LEGAL-GEN', 'LLOYDS', 'LSE', 'M&S', 'MAN-GROUP', 'MATCH', 'MERCK', 'META', 'MICROSOFT', 'MONDI', 'MORGAN-S', 'MSTRCARD', 'McD', 'NAT-GRID', 'NETFLIX', 'NEXT', 'NIKE', 'OCADO', 'ORACLE', 'P&G', 'PAYPAL', 'PEARSON', 'PENNON', 'PEPSI', 'PERSIMMON', 'PETROFAC', 'PFIZER', 'PHIL-MOR', 'PRUDENTIAL', 'REED-ELSVR', 'RENTOKIL', 'RIGHTMOVE', 'RIO-TINTO', 'ROLLS-ROYCE', 'SAGE', 'SAINSBURY', 'SCHLUMBERGR', 'SEVERN-TRNT', 'SMITH-NEPH', 'SMITHS', 'SQUARE-INC', 'SSE', 'ST-JAMES', 'STAN-CHARTD', 'STARBUX', 'TAYLOR-WIMP', 'TESCO', 'TESLA', 'THOMAS-COOK', 'TRAVELRS', 'TRAVIS-PERK', 'TUI', 'TULLOW', 'UNILEVER', 'UNITED-UTIL', 'UTD-HLTH', 'VERIZON', 'VISA', 'VODAFONE', 'WALMART', 'WEIR-GROUP', 'WELLS-FG', 'WHITBREAD', 'WPP')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.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: 2023-03-01 11:37:45 Duration: 2m34s Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
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WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = '479' 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 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 (kr.simulation = 0 OR kr.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 ('263' = 0 OR coalesce(bim.code, s.symbol) in ('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHFNOK', 'EURAUD', 'EURCAD', 'EURCHF', 'EURCZK', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPSEK', 'GBPUSD', 'HKDJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'PnL', 'SGDJPY', 'TRYJPY', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDZAR', 'ZARJPY', 'ACCOR', 'ADIDAS', 'AIR-LIQUIDE', 'AIRBUS-GRP', 'ALLIANZ', 'ALSTOM', 'ARCELORMITL', 'AXA', 'BASF', 'BAYER', 'BEIERSDORF', 'BMW', 'BNP-PARIBAS', 'BOUYGUES', 'CAP-GEMINI', 'CARREFOUR', 'CONTINENTAL', 'CREDIT-AGRI', 'DANONE', 'DEUT-BOERSE', 'DEUT-TELEKM', 'DEUTSCHE-BK', 'DEUTSCHPOST', 'E.ON', 'EDF', 'ENGIE', 'FRESENI-MED', 'FRESENIUS', 'HEIDBGCEMNT', 'HENKEL', 'INFINEONTEC', 'KERING', 'LANXESS', 'LEGRAND', 'LINDE', 'LOREAL', 'LUFTHANSA', 'LVMH', 'MERCK-KGAA', 'MICHELIN', 'MUNICH-RE', 'ORANGE', 'PERNOD-RICD', 'PUBLICIS-GR', 'RENAULT', 'RWE', 'SAFRAN', 'SAINTGOBAIN', 'SANOFI', 'SAP', 'SCHNEIDELEC', 'SIEMENS', 'SOCIETE-GEN', 'SOLVAY', 'THYSSENKRUP', 'TOTAL', 'VALEO', 'VEOLIA-ENV', 'VINCI', 'VIVENDI', 'VOLKSWAGEN', 'XAGUSD', 'XAUUSD', 'ESTOX', 'FRENCH40', 'GERMAN30', 'UK100', 'US30', 'US500', 'USNDX', '3M', '3i-GROUP', 'ADMIRAL', 'AIG', 'ALIBABA', 'AMAZON', 'AMEX', 'ANGLO-AMERI', 'ANTOFAGASTA', 'APPLE', 'ASHTEAD', 'ASTRAZENECA', 'AT&T', 'AVIVA', 'BABCOCK', 'BAE-SYSTEMS', 'BAIDU', 'BALFOUR-B', 'BARCLAYS', 'BARRAT', 'BATS', 'BHP-BILITON', 'BNK-AMER', 'BOEING', 'BP', 'BRIT-FOODS', 'BRIT-LND', 'BT', 'BUNZL', 'BURBERRY', 'CAPITA', 'CARNIVAL', 'CAT', 'CENTRICA', 'CHEVRON', 'CISCO', 'CITI', 'COMPASS', 'CRH', 'DIAGEO', 'DIRECT-LINE', 'DISNEY', 'DRAX', 'EASYJET', 'EBAY', 'EXPERIAN', 'EXXON', 'FACEBOOK', 'FEDEX', 'FERRARI', 'FORD', 'GE', 'GLAXO', 'GLENCORE', 'GM', 'GOLDMANS', 'HALLIBURTON', 'HAMMERSON', 'HOME-DEP', 'HP', 'HSBC', 'IAG', 'IBM', 'IG-GROUP', 'IHG', 'IMI', 'IMP-TOBACCO', 'INCHCAPE', 'INTEL', 'INTERTEK', 'ITV', 'JOHNSON', 'JOHNSON-MAT', 'JPMORGAN', 'KINGFISHER', 'LAND-SEC', 'LEGAL-GEN', 'LLOYDS', 'LSE', 'M&S', 'MAN-GROUP', 'MATCH', 'MERCK', 'META', 'MICROSOFT', 'MONDI', 'MORGAN-S', 'MSTRCARD', 'McD', 'NAT-GRID', 'NETFLIX', 'NEXT', 'NIKE', 'OCADO', 'ORACLE', 'P&G', 'PAYPAL', 'PEARSON', 'PENNON', 'PEPSI', 'PERSIMMON', 'PETROFAC', 'PFIZER', 'PHIL-MOR', 'PRUDENTIAL', 'REED-ELSVR', 'RENTOKIL', 'RIGHTMOVE', 'RIO-TINTO', 'ROLLS-ROYCE', 'SAGE', 'SAINSBURY', 'SCHLUMBERGR', 'SEVERN-TRNT', 'SMITH-NEPH', 'SMITHS', 'SQUARE-INC', 'SSE', 'ST-JAMES', 'STAN-CHARTD', 'STARBUX', 'TAYLOR-WIMP', 'TESCO', 'TESLA', 'THOMAS-COOK', 'TRAVELRS', 'TRAVIS-PERK', 'TUI', 'TULLOW', 'UNILEVER', 'UNITED-UTIL', 'UTD-HLTH', 'VERIZON', 'VISA', 'VODAFONE', 'WALMART', 'WEIR-GROUP', 'WELLS-FG', 'WHITBREAD', 'WPP')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.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: 2023-03-01 11:53:23 Duration: 2m5s Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
8 33m46s 2,225 0ms 44s281ms 910ms select distinct a.resultuid as ruid, c.symbolid as sid, c.symbol as sym, c.longname as longname, c.shortname, c.exchange as e, c.timegranularity as tg, p.patternid as pid, a.direction as d, cast(atbaridentified as timestamp) as pet, cast(patternstarttime as timestamp) as pst, patternprice as patp, breakoutprice as pe, breakoutbars as be, errormargin as erm, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, cast(x0 as timestamp) as x0, cast(x1 as timestamp) as x1, cast(x2 as timestamp) as x2, cast(( case when x3 = ? then ? else x3 end) as timestamp) as x3, cast(( case when x4 = ? then ? else x4 end) as timestamp) as x4, cast(( case when x5 = ? then ? else x5 end) as timestamp) as x5, cast(( case when x6 = ? then ? else x6 end) as timestamp) as x6, cast(( case when x7 = ? then ? else x7 end) as timestamp) as x7, cast(( case when x8 = ? then ? else x8 end) as timestamp) as x8, cast(( case when x9 = ? then ? else x9 end) as timestamp) as x9, cast(atbaridentified as timestamp) as patternendtime, cast(atbaridentified as timestamp) as atbar, cast(( case when approachingtimestamp = ? then ? else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzos, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as relevant, cast(?.? as double precision) as premium, cast(? as bigint) as instrumentid, ? as derivativeid, ? as underlyingid, ? as isunderlying from symbols c inner join brokersymbollist b on c.symbolid = b.symbolid inner join symbolgroup sg on c.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = c.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join keylevels_results a on a.symbolid = c.symbolid inner join hrspatterns p on a.patternid = p.patternid left outer join relevance_keylevels_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and patternclassid = ? and patternlengthbars >= ? and a.patternid & ? > ? and dftt.dayofweek = ? and a.resultuid > ? and c.nonliquid = ? and c.deleted = ? and dss.enabled = ? order by relevant desc, age asc, patternendtime desc, qtp desc limit ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Mar 01 11 2,225 33m46s 910ms [ User: postgres - Total duration: 33m46s - Times executed: 2225 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 33m46s - Times executed: 2225 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 538 AND sg.groupid = 515852059729069308 AND patternclassid = '1' AND patternlengthbars >= '20' AND a.PatternID & '3' > 0 AND dftt.dayofweek = '3' AND a.resultuid > '-1227948089' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:35:45 Duration: 44s281ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 538 AND sg.groupid = 515852059729069308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '3' > 0 AND dftt.dayofweek = '3' AND a.resultuid > '776704799' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:35:45 Duration: 43s938ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 667 AND sg.groupid = 500996399199151208 AND patternclassid = '1' AND patternlengthbars >= '20' AND a.PatternID & '3' > 0 AND dftt.dayofweek = '3' AND a.resultuid > '-1792441497' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:35:00 Duration: 41s335ms Database: acaweb_fx User: postgres Remote: 192.168.0.239 Application: PostgreSQL JDBC Driver Bind query: yes
9 33m26s 13 148ms 31m17s 2m34s 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 ), results as ( select distinct on (s.symbolid) kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, 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 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 relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true where kr.gmttimefound > now() - interval ? and dss.enabled = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or s.symbol in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) order by symbolid, identified desc, patternlengthbars desc ) select * from results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by identified desc, length desc;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Mar 01 11 13 33m26s 2m34s [ User: postgres - Total duration: 33m26s - Times executed: 13 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 33m26s - Times executed: 13 ]
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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 ), results AS ( SELECT DISTINCT ON (s.symbolid) kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, 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 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 relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 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 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') ORDER BY symbolid, identified DESC, patternlengthbars DESC ) SELECT * from results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY identified DESC, length DESC;
Date: 2023-03-01 11:28:46 Duration: 31m17s Database: acaweb_fx User: postgres Remote: 192.168.1.135 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 ), results AS ( SELECT DISTINCT ON (s.symbolid) kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, 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 FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '700' 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 relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 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 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') ORDER BY symbolid, identified DESC, patternlengthbars DESC ) SELECT * from results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY identified DESC, length DESC;
Date: 2023-03-01 11:31:27 Duration: 49s242ms Database: acaweb_fx User: postgres Remote: 192.168.1.135 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 ), results AS ( SELECT DISTINCT ON (s.symbolid) kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, 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 FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '642' 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 relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND (kr.simulation = 0 OR kr.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 s.symbol in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('0' = 0 OR kr.patternlengthbars <= '0') ORDER BY symbolid, identified DESC, patternlengthbars DESC ) SELECT * from results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY identified DESC, length DESC;
Date: 2023-03-01 11:34:02 Duration: 22s392ms Database: acaweb_fx User: postgres Remote: 192.168.1.135 Application: PostgreSQL JDBC Driver Bind query: yes
10 25m6s 4 5m38s 6m48s 6m16s update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 01 11 4 25m6s 6m16s [ User: postgres - Total duration: 25m6s - Times executed: 4 ]
[ Application: psql - Total duration: 25m6s - Times executed: 4 ]
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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: 2023-03-01 11:33:07 Duration: 6m48s 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: 2023-03-01 11:17:46 Duration: 6m30s 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: 2023-03-01 11:47:20 Duration: 6m8s Database: acaweb_fx User: postgres Remote: [local] Application: psql
11 24m58s 4 4m57s 7m10s 6m14s 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 #11
Day Hour Count Duration Avg duration Mar 01 11 4 24m58s 6m14s [ User: postgres - Total duration: 24m58s - Times executed: 4 ]
[ Application: psql - Total duration: 24m58s - Times executed: 4 ]
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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: 2023-03-01 11:40:21 Duration: 7m10s 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: 2023-03-01 11:08:31 Duration: 6m26s 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: 2023-03-01 11:24:12 Duration: 6m24s Database: acaweb_fx User: postgres Remote: [local] Application: psql
12 20m53s 192 5ms 24s191ms 6s527ms select * from ( select pricedatetime, open, high, low, close, volume, bsf from t30 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Mar 01 11 192 20m53s 6s527ms [ User: postgres - Total duration: 20m53s - Times executed: 192 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 20m53s - Times executed: 192 ]
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T30 WHERE symbolid = '515840217506801300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:33:08 Duration: 24s191ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T30 WHERE symbolid = '515840243187254300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:23:47 Duration: 23s260ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T30 WHERE symbolid = '515840243268503300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:15:53 Duration: 19s771ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
13 20m3s 9 7s386ms 4m18s 2m13s refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Mar 01 11 9 20m3s 2m13s [ User: postgres - Total duration: 20m3s - Times executed: 9 ]
[ Application: [unknown] - Total duration: 20m3s - Times executed: 9 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2023-03-01 11:14:07 Duration: 4m18s 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: 2023-03-01 11:17:26 Duration: 3m34s 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: 2023-03-01 11:35:16 Duration: 3m27s Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
14 14m59s 106 566ms 25s223ms 8s489ms select * from ( select pricedatetime, open, high, low, close, volume, bsf from t240 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Mar 01 11 106 14m59s 8s489ms [ User: postgres - Total duration: 14m59s - Times executed: 106 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14m59s - Times executed: 106 ]
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T240 WHERE symbolid = '515840243246556300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:11:57 Duration: 25s223ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T240 WHERE symbolid = '515840243238979300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:11:55 Duration: 21s656ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T240 WHERE symbolid = '515840248269940300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:09:41 Duration: 18s186ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
15 13m58s 4 2m37s 4m6s 3m29s select updaterelevantforrelevantresults ();Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Mar 01 11 4 13m58s 3m29s [ User: postgres - Total duration: 13m58s - Times executed: 4 ]
[ Application: psql - Total duration: 13m58s - Times executed: 4 ]
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select updaterelevantforrelevantresults ();
Date: 2023-03-01 11:39:37 Duration: 4m6s Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updaterelevantforrelevantresults ();
Date: 2023-03-01 11:54:31 Duration: 3m59s Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updaterelevantforrelevantresults ();
Date: 2023-03-01 11:08:45 Duration: 3m14s Database: acaweb_fx User: postgres Remote: [local] Application: psql
16 13m52s 234 2ms 1m21s 3s559ms select distinct patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, longname, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as relevant from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join autochartist_results a on a.symbolid = s.symbolid inner join patterns p on a.pattern = p.patternname left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and (((s.symbol ilike ? and timegranularity = ?))) and breakout >= ?.? and patternendtime = latestbaratbreakouttime and patternlengthbars >= ? and patternquality >= ?.? and initialtrend >= ?.? and symmetry >= ?.? and noise <= ?.? and volumeincrease >= ?.? and temporarypattern = ? and patternid & ? > ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and a.resultuid > ? and s.nonliquid = ? and dftt.dayofweek = ? order by relevant desc, age asc, patternendtime desc, patternquality desc limit ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 01 11 234 13m52s 3s559ms [ User: postgres - Total duration: 13m52s - Times executed: 234 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 13m52s - Times executed: 234 ]
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 538 AND (((s.symbol ilike '%usdzar%' AND timegranularity = 1440))) AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 601334092758412301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:54:46 Duration: 1m21s Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 538 AND (((s.symbol ilike '%usdzar%' AND timegranularity = 1440))) AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 601334092758412301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:20:56 Duration: 1m14s Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
-
/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 538 AND (((s.symbol ilike '%gbpusd%' AND timegranularity = 240))) AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 601477691791436301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:28:53 Duration: 57s485ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
17 13m9s 12,136 0ms 1s986ms 65ms 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 #17
Day Hour Count Duration Avg duration Mar 01 11 12,136 13m9s 65ms [ User: postgres - Total duration: 13m9s - Times executed: 12136 ]
[ Application: [unknown] - Total duration: 13m9s - Times executed: 12136 ]
-
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 ('515840218878190300-1|44986.1146|44986.4479|44986|44986.3542|1.795|1.788|1.7843|1.7809', 515840218878190300, 2.000000000000000000000000000000, 'Falling Wedge', 4, '2023-03-01 09:12:33'::timestamp without time zone, - 1, 0.172702563943889525500000000000, - 1.000000000000000000000000000000, 0.940460833592811629200000000000, 0.905167773242821272000000000000, 0.493133776676476842600000000000, 1.781270210508815621000000000000, 1.783174671045339776000000000000, '2023-03-01 11:00:00'::timestamp without time zone, '2023-03-01 16:30:00'::timestamp without time zone, '2023-02-28 22:00:00'::timestamp without time zone, '2023-03-01 11:00:00'::timestamp without time zone, 1.790694999999999926000000000000, 1.782845000000000013000000000000, '2023-03-01 02:45:00'::timestamp without time zone, '2023-03-01 10:45:00'::timestamp without time zone, '2023-03-01 00:00:00'::timestamp without time zone, '2023-03-01 08:30:00'::timestamp without time zone, 1.795045000000000002000000000000, 1.788005000000000066000000000000, 1.784315000000000095000000000000, 1.780934999999999935000000000000, - 0.000099411764705887074060000000, - 0.000219999999999997975000000000, 1.339685566993866095000000000000, 0.253556189125848374600000000000, 'Continuation', 0.000000000000000000000000000000, '2023-03-01 11:00:00'::timestamp without time zone, 1.784534999999999982000000000000, 44, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:15:22 Duration: 1s986ms 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 ('515840218878190300-1|44986.1146|44986.4479|44986|44986.3542|1.795|1.788|1.7843|1.7809', 515840218878190300, 3.000000000000000000000000000000, 'Falling Wedge', 4, '2023-03-01 09:12:33'::timestamp without time zone, - 1, 0.495278355645712931000000000000, - 1.000000000000000000000000000000, 0.803502837814596082600000000000, 0.905167773242821272000000000000, 0.493133776676476842600000000000, 1.779885715210831387000000000000, 1.782597798004513123000000000000, '2023-03-01 11:00:00'::timestamp without time zone, '2023-03-01 16:30:00'::timestamp without time zone, '2023-02-28 17:15:00'::timestamp without time zone, '2023-03-01 11:00:00'::timestamp without time zone, 1.803015000000000034000000000000, 1.782845000000000013000000000000, '2023-03-01 02:45:00'::timestamp without time zone, '2023-03-01 10:45:00'::timestamp without time zone, '2023-03-01 00:00:00'::timestamp without time zone, '2023-03-01 08:30:00'::timestamp without time zone, 1.795045000000000002000000000000, 1.788005000000000066000000000000, 1.784315000000000095000000000000, 1.780934999999999935000000000000, - 0.000099411764705887074060000000, - 0.000219999999999997975000000000, 1.565144735172960600000000000000, 0.361081453026456167200000000000, 'Continuation', 0.000000000000000000000000000000, '2023-03-01 11:00:00'::timestamp without time zone, 1.784534999999999982000000000000, 44, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:15:22 Duration: 1s837ms 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 ('515840247979934300-1|44984.5833|44985.5833|44985.4167|44986.4271|220.5685|223.4185|218.4185|221.75', 515840247979934300, 4.000000000000000000000000000000, 'Channel Up', 4, '2023-03-01 08:57:50'::timestamp without time zone, 1, 0.261255650133706551800000000000, - 1.000000000000000000000000000000, 1.000000000000000000000000000000, 0.494435865001761232200000000000, 0.872651564459706152800000000000, 223.637477233603675600000000000000, 224.459945360648845300000000000000, '2023-03-01 10:45:00'::timestamp without time zone, '2023-03-02 09:07:30'::timestamp without time zone, '2023-02-24 17:30:00'::timestamp without time zone, '2023-03-01 10:45:00'::timestamp without time zone, 216.750000000000000000000000000000, 223.050000000000011400000000000000, '2023-02-27 14:00:00'::timestamp without time zone, '2023-02-28 14:00:00'::timestamp without time zone, '2023-02-28 10:00:00'::timestamp without time zone, '2023-03-01 10:15:00'::timestamp without time zone, 220.568500000000000200000000000000, 223.418499999999994500000000000000, 218.418499999999994500000000000000, 221.750000000000000000000000000000, 0.095185714285714442820000000000, 0.083823529411764532980000000000, 2.205025229788127650000000000000, 0.546490449863883842600000000000, 'Continuation', 0.000000000000000000000000000000, '2023-03-01 10:45:00'::timestamp without time zone, 223.050000000000011400000000000000, 55, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:00:38 Duration: 1s783ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
18 12m3s 2 3m47s 8m16s 6m1s select gen_whatshot ();Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Mar 01 11 2 12m3s 6m1s [ User: postgres - Total duration: 12m3s - Times executed: 2 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12m3s - Times executed: 2 ]
-
select gen_whatshot ();
Date: 2023-03-01 11:16:32 Duration: 8m16s Database: acaweb_fx User: postgres Remote: 192.168.4.150 Application: PostgreSQL JDBC Driver Bind query: yes
-
select gen_whatshot ();
Date: 2023-03-01 11:28:28 Duration: 3m47s Database: acaweb_fx User: postgres Remote: 192.168.4.150 Application: PostgreSQL JDBC Driver Bind query: yes
19 10m30s 248 3ms 21s240ms 2s543ms select * from ( select pricedatetime, open, high, low, close, volume, bsf from t60 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Mar 01 11 248 10m30s 2s543ms [ User: postgres - Total duration: 10m30s - Times executed: 248 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 10m30s - Times executed: 248 ]
-
SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T60 WHERE symbolid = '515840243902252300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:16:48 Duration: 21s240ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T60 WHERE symbolid = '515840243214354300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:16:27 Duration: 16s567ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T60 WHERE symbolid = '515840248632535300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:10:41 Duration: 14s971ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
20 10m10s 4,809 0ms 1s916ms 126ms 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 #20
Day Hour Count Duration Avg duration Mar 01 11 4,809 10m10s 126ms [ User: postgres - Total duration: 10m10s - Times executed: 4809 ]
[ Application: [unknown] - Total duration: 10m10s - Times executed: 4809 ]
-
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, 2, '2023-03-01 09:27:40'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 81, 19.960000000000000850000000000000, '2023-02-28 10:00:00', '2023-02-22 08:00:00', '2023-02-22 07:30:00', '', '', '', '', '', '', '', 162, 19.919000000000000480000000000000, '2023-03-01 04:00:00'::timestamp without time zone, '2023-03-01 04:00:00', 0.000000000000000000000000000000, 0.041000000000000015600000000000, 1, 515840221503096300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840221503096300|19.96|2|2023-03-01 04:00:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2023-02-22 07:30:00', 19.629999999999999000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:30:29 Duration: 1s916ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (5.000000000000000000000000000000, - 1, 2, '2023-03-01 09:27:40'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 81, 19.960000000000000850000000000000, '2023-02-28 10:00:00', '2023-02-22 08:00:00', '2023-02-22 07:30:00', '', '', '', '', '', '', '', 162, 19.919000000000000480000000000000, '2023-03-01 04:00:00'::timestamp without time zone, '2023-03-01 04:00:00', 0.000000000000000000000000000000, 0.041000000000000015600000000000, 1, 515840221503096300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840221503096300|19.96|2|2023-03-01 04:00:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2023-02-22 07:30:00', 19.629999999999999000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:30:29 Duration: 1s912ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (4.000000000000000000000000000000, - 1, 2, '2023-03-01 09:12:34'::timestamp without time zone, '', 0.500000000000000000000000000000, 4, 68, 7239.300000000000182000000000000000, '2023-03-01 09:30:00', '2023-02-28 00:30:00', '2023-02-27 18:00:00', '2023-02-27 17:30:00', '', '', '', '', '', '', 170, 7236.239999999999782000000000000000, '2023-03-01 10:30:00'::timestamp without time zone, '2023-03-01 10:30:00', 0.000000000000000000000000000000, 3.059999999999991172000000000000, 1, 515840248015340300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840248015340300|7239.3|2|2023-03-01 10:30:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2023-02-27 17:30:00', 7206.300000000000182000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:15:22 Duration: 1s607ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 68,422 390ms 0ms 1ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 01 11 68,421 390ms 0ms 12 1 0ms 0ms [ User: postgres - Total duration: 390ms - Times executed: 68422 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 357ms - Times executed: 68015 ]
[ Application: [unknown] - Total duration: 33ms - Times executed: 407 ]
-
select 1;
Date: 2023-03-01 11:05:30 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2023-03-01 11:27:50 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
-
select 1;
Date: 2023-03-01 11:35:07 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
2 12,136 13m9s 0ms 1s986ms 65ms 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 #2
Day Hour Count Duration Avg duration Mar 01 11 12,136 13m9s 65ms [ User: postgres - Total duration: 13m9s - Times executed: 12136 ]
[ Application: [unknown] - Total duration: 13m9s - Times executed: 12136 ]
-
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 ('515840218878190300-1|44986.1146|44986.4479|44986|44986.3542|1.795|1.788|1.7843|1.7809', 515840218878190300, 2.000000000000000000000000000000, 'Falling Wedge', 4, '2023-03-01 09:12:33'::timestamp without time zone, - 1, 0.172702563943889525500000000000, - 1.000000000000000000000000000000, 0.940460833592811629200000000000, 0.905167773242821272000000000000, 0.493133776676476842600000000000, 1.781270210508815621000000000000, 1.783174671045339776000000000000, '2023-03-01 11:00:00'::timestamp without time zone, '2023-03-01 16:30:00'::timestamp without time zone, '2023-02-28 22:00:00'::timestamp without time zone, '2023-03-01 11:00:00'::timestamp without time zone, 1.790694999999999926000000000000, 1.782845000000000013000000000000, '2023-03-01 02:45:00'::timestamp without time zone, '2023-03-01 10:45:00'::timestamp without time zone, '2023-03-01 00:00:00'::timestamp without time zone, '2023-03-01 08:30:00'::timestamp without time zone, 1.795045000000000002000000000000, 1.788005000000000066000000000000, 1.784315000000000095000000000000, 1.780934999999999935000000000000, - 0.000099411764705887074060000000, - 0.000219999999999997975000000000, 1.339685566993866095000000000000, 0.253556189125848374600000000000, 'Continuation', 0.000000000000000000000000000000, '2023-03-01 11:00:00'::timestamp without time zone, 1.784534999999999982000000000000, 44, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:15:22 Duration: 1s986ms 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 ('515840218878190300-1|44986.1146|44986.4479|44986|44986.3542|1.795|1.788|1.7843|1.7809', 515840218878190300, 3.000000000000000000000000000000, 'Falling Wedge', 4, '2023-03-01 09:12:33'::timestamp without time zone, - 1, 0.495278355645712931000000000000, - 1.000000000000000000000000000000, 0.803502837814596082600000000000, 0.905167773242821272000000000000, 0.493133776676476842600000000000, 1.779885715210831387000000000000, 1.782597798004513123000000000000, '2023-03-01 11:00:00'::timestamp without time zone, '2023-03-01 16:30:00'::timestamp without time zone, '2023-02-28 17:15:00'::timestamp without time zone, '2023-03-01 11:00:00'::timestamp without time zone, 1.803015000000000034000000000000, 1.782845000000000013000000000000, '2023-03-01 02:45:00'::timestamp without time zone, '2023-03-01 10:45:00'::timestamp without time zone, '2023-03-01 00:00:00'::timestamp without time zone, '2023-03-01 08:30:00'::timestamp without time zone, 1.795045000000000002000000000000, 1.788005000000000066000000000000, 1.784315000000000095000000000000, 1.780934999999999935000000000000, - 0.000099411764705887074060000000, - 0.000219999999999997975000000000, 1.565144735172960600000000000000, 0.361081453026456167200000000000, 'Continuation', 0.000000000000000000000000000000, '2023-03-01 11:00:00'::timestamp without time zone, 1.784534999999999982000000000000, 44, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:15:22 Duration: 1s837ms 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 ('515840247979934300-1|44984.5833|44985.5833|44985.4167|44986.4271|220.5685|223.4185|218.4185|221.75', 515840247979934300, 4.000000000000000000000000000000, 'Channel Up', 4, '2023-03-01 08:57:50'::timestamp without time zone, 1, 0.261255650133706551800000000000, - 1.000000000000000000000000000000, 1.000000000000000000000000000000, 0.494435865001761232200000000000, 0.872651564459706152800000000000, 223.637477233603675600000000000000, 224.459945360648845300000000000000, '2023-03-01 10:45:00'::timestamp without time zone, '2023-03-02 09:07:30'::timestamp without time zone, '2023-02-24 17:30:00'::timestamp without time zone, '2023-03-01 10:45:00'::timestamp without time zone, 216.750000000000000000000000000000, 223.050000000000011400000000000000, '2023-02-27 14:00:00'::timestamp without time zone, '2023-02-28 14:00:00'::timestamp without time zone, '2023-02-28 10:00:00'::timestamp without time zone, '2023-03-01 10:15:00'::timestamp without time zone, 220.568500000000000200000000000000, 223.418499999999994500000000000000, 218.418499999999994500000000000000, 221.750000000000000000000000000000, 0.095185714285714442820000000000, 0.083823529411764532980000000000, 2.205025229788127650000000000000, 0.546490449863883842600000000000, 'Continuation', 0.000000000000000000000000000000, '2023-03-01 10:45:00'::timestamp without time zone, 223.050000000000011400000000000000, 55, 0, 0.000000000000000000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:00:38 Duration: 1s783ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
3 11,597 5m10s 0ms 819ms 26ms 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 #3
Day Hour Count Duration Avg duration Mar 01 11 11,597 5m10s 26ms [ User: postgres - Total duration: 5m10s - Times executed: 11597 ]
[ Application: [unknown] - Total duration: 5m10s - Times executed: 11597 ]
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2023-03-01 08:45:00', '7911.4', '7919.16', '7903.14', '7918.67', '1483', '515840230952387300', '0', '2023-03-01 11:04:23.149', '2023-03-01 11:04:22.932') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '7911.4', high = '7919.16', low = '7903.14', close = '7918.67', volume = '1483', bsf = '0', sastdatetimewritten = '2023-03-01 11:04:23.15', sastdatetimereceived = '2023-03-01 11:04:22.932';
Date: 2023-03-01 11:04:23 Duration: 819ms 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 ('2023-03-01 11:30:00', '7253.4', '7255.9', '7251.4', '7253.9', '131', '515840238058964300', '0', '2023-03-01 11:56:01.735', '2023-03-01 11:56:01.682') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '7253.4', high = '7255.9', low = '7251.4', close = '7253.9', volume = '131', bsf = '0', sastdatetimewritten = '2023-03-01 11:56:01.735', sastdatetimereceived = '2023-03-01 11:56:01.682';
Date: 2023-03-01 11:56:02 Duration: 729ms 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 ('2023-03-01 10:45:00', '7248.3', '7258.3', '7247.3', '7255.3', '89', '515840248015086300', '0', '2023-03-01 11:14:35.071', '2023-03-01 11:14:35.007') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '7248.3', high = '7258.3', low = '7247.3', close = '7255.3', volume = '89', bsf = '0', sastdatetimewritten = '2023-03-01 11:14:35.071', sastdatetimereceived = '2023-03-01 11:14:35.007';
Date: 2023-03-01 11:14:36 Duration: 668ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
4 10,308 100ms 0ms 4ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Mar 01 11 10,308 100ms 0ms [ User: postgres - Total duration: 100ms - Times executed: 10308 ]
[ Application: [unknown] - Total duration: 100ms - Times executed: 10308 ]
-
SET extra_float_digits = 3;
Date: 2023-03-01 11:33:30 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2023-03-01 11:19:17 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: [unknown] Bind query: yes
-
SET extra_float_digits = 3;
Date: 2023-03-01 11:27:50 Duration: 1ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: [unknown] Bind query: yes
5 10,282 97ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Mar 01 11 10,282 97ms 0ms [ User: postgres - Total duration: 97ms - Times executed: 10282 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 97ms - Times executed: 10282 ]
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2023-03-01 11:11:33 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2023-03-01 11:37:30 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2023-03-01 11:00:28 Duration: 0ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
6 6,458 4d6h50m16s 0ms 3h17m48s 57s326ms 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 Mar 01 11 6,458 4d6h50m16s 57s326ms [ User: postgres - Total duration: 4d6h50m16s - Times executed: 6458 ]
[ Application: [unknown] - Total duration: 4d6h50m16s - Times executed: 6458 ]
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-03 09:00:00', '6.335', '6.335', '6.335', '6.335', '2', '600197227125639300', '0', '2023-03-01 08:40:22.766', '2023-03-01 08:40:22.766') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '6.335', high = '6.335', low = '6.335', close = '6.335', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:40:22.766', sastdatetimereceived = '2023-03-01 08:40:22.766';
Date: 2023-03-01 11:58:11 Duration: 3h17m48s Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-12-02 09:00:00', '0', '0', '0', '0', '2', '500991632125453200', '0', '2023-03-01 08:41:12.178', '2023-03-01 08:41:12.177') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0', high = '0', low = '0', close = '0', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:41:12.178', sastdatetimereceived = '2023-03-01 08:41:12.177';
Date: 2023-03-01 11:58:11 Duration: 3h16m59s 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 ('2022-10-03 09:00:00', '25.88', '25.88', '25.88', '25.88', '2', '600197227405596300', '0', '2023-03-01 08:43:37.359', '2023-03-01 08:43:37.358') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '25.88', high = '25.88', low = '25.88', close = '25.88', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:43:37.359', sastdatetimereceived = '2023-03-01 08:43:37.358';
Date: 2023-03-01 11:58:11 Duration: 3h14m33s Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
7 4,809 10m10s 0ms 1s916ms 126ms 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 #7
Day Hour Count Duration Avg duration Mar 01 11 4,809 10m10s 126ms [ User: postgres - Total duration: 10m10s - Times executed: 4809 ]
[ Application: [unknown] - Total duration: 10m10s - Times executed: 4809 ]
-
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, 2, '2023-03-01 09:27:40'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 81, 19.960000000000000850000000000000, '2023-02-28 10:00:00', '2023-02-22 08:00:00', '2023-02-22 07:30:00', '', '', '', '', '', '', '', 162, 19.919000000000000480000000000000, '2023-03-01 04:00:00'::timestamp without time zone, '2023-03-01 04:00:00', 0.000000000000000000000000000000, 0.041000000000000015600000000000, 1, 515840221503096300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840221503096300|19.96|2|2023-03-01 04:00:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2023-02-22 07:30:00', 19.629999999999999000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:30:29 Duration: 1s916ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (5.000000000000000000000000000000, - 1, 2, '2023-03-01 09:27:40'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 81, 19.960000000000000850000000000000, '2023-02-28 10:00:00', '2023-02-22 08:00:00', '2023-02-22 07:30:00', '', '', '', '', '', '', '', 162, 19.919000000000000480000000000000, '2023-03-01 04:00:00'::timestamp without time zone, '2023-03-01 04:00:00', 0.000000000000000000000000000000, 0.041000000000000015600000000000, 1, 515840221503096300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840221503096300|19.96|2|2023-03-01 04:00:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2023-02-22 07:30:00', 19.629999999999999000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:30:29 Duration: 1s912ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
-
INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (4.000000000000000000000000000000, - 1, 2, '2023-03-01 09:12:34'::timestamp without time zone, '', 0.500000000000000000000000000000, 4, 68, 7239.300000000000182000000000000000, '2023-03-01 09:30:00', '2023-02-28 00:30:00', '2023-02-27 18:00:00', '2023-02-27 17:30:00', '', '', '', '', '', '', 170, 7236.239999999999782000000000000000, '2023-03-01 10:30:00'::timestamp without time zone, '2023-03-01 10:30:00', 0.000000000000000000000000000000, 3.059999999999991172000000000000, 1, 515840248015340300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840248015340300|7239.3|2|2023-03-01 10:30:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2023-02-27 17:30:00', 7206.300000000000182000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:15:22 Duration: 1s607ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
8 4,685 3h30m11s 0ms 1m7s 2s691ms select distinct a.resultuid as ruid, c.symbolid as sid, c.symbol as sym, c.longname as longname, c.shortname, c.exchange as e, c.timegranularity as tg, p.patternid as pid, a.direction as d, cast(atbaridentified as timestamp) as pet, cast(patternstarttime as timestamp) as pst, patternprice as patp, breakoutprice as pe, breakoutbars as be, errormargin as erm, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, cast(x0 as timestamp) as x0, cast(x1 as timestamp) as x1, cast(x2 as timestamp) as x2, cast(( case when x3 = ? then ? else x3 end) as timestamp) as x3, cast(( case when x4 = ? then ? else x4 end) as timestamp) as x4, cast(( case when x5 = ? then ? else x5 end) as timestamp) as x5, cast(( case when x6 = ? then ? else x6 end) as timestamp) as x6, cast(( case when x7 = ? then ? else x7 end) as timestamp) as x7, cast(( case when x8 = ? then ? else x8 end) as timestamp) as x8, cast(( case when x9 = ? then ? else x9 end) as timestamp) as x9, cast(atbaridentified as timestamp) as patternendtime, cast(atbaridentified as timestamp) as atbar, cast(( case when approachingtimestamp = ? then ? else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzos, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as relevant, cast(?.? as double precision) as premium, cast(? as bigint) as instrumentid, ? as derivativeid, ? as underlyingid, ? as isunderlying from symbols c inner join brokersymbollist b on c.symbolid = b.symbolid inner join symbolgroup sg on c.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = c.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join keylevels_results a on a.symbolid = c.symbolid inner join hrspatterns p on a.patternid = p.patternid left outer join relevance_keylevels_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and patternclassid = ? and patternlengthbars >= ? and a.patternid & ? > ? and dftt.dayofweek = ? and a.qtytp >= ? and a.resultuid > ? and c.nonliquid = ? and c.deleted = ? and dss.enabled = ? order by relevant desc, age asc, patternendtime desc, qtp desc limit ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Mar 01 11 4,685 3h30m11s 2s691ms [ User: postgres - Total duration: 3h30m11s - Times executed: 4685 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3h30m11s - Times executed: 4685 ]
-
/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 622 AND sg.groupid = 515852059853768308 AND patternclassid = '1' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '1653660799' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:17:01 Duration: 1m7s Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 621 AND sg.groupid = 515852059852088308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '-936617313' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:11:42 Duration: 1m1s Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 622 AND sg.groupid = 515852059853768308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '1329650799' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:12:08 Duration: 1m Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
9 4,550 6m26s 0ms 2m20s 84ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Mar 01 11 4,550 6m26s 84ms [ User: postgres - Total duration: 6m26s - Times executed: 4550 ]
[ Application: [unknown] - Total duration: 6m26s - Times executed: 4550 ]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2023-03-01 10:00:00', reason = 'Pattern is too old to be relevant. PEIndex at 601 vs 612' WHERE uniqueIndex = '515840246471599300-1|44981.7917|44986.0833|44984.7083|44985.8333|22.84|21.42|21.37|20.94' and relevant = 1;
Date: 2023-03-01 11:23:09 Duration: 2m20s Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2023-03-01 10:30:00', reason = 'Price has entered the prediction area for a completed pattern.' WHERE uniqueIndex = '|515840217887008300|23627.55|1|2023-03-01 06:30:00|1|1' and relevant = 1;
Date: 2023-03-01 11:23:09 Duration: 9s39ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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UPDATE patternresultsrelevance SET relevant = 0, saxo_relevant = 0, notrelevantpricedatetime = '2023-03-01 10:00:00', reason = 'Price has entered the prediction area for a completed pattern.' WHERE uniqueIndex = '|515840217871844300|4.7027|2|2023-03-01 06:30:00|-1|1' and relevant = 1;
Date: 2023-03-01 11:23:09 Duration: 5s659ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
10 3,848 4m10s 2ms 5s260ms 65ms select distinct a.resultuid as ruid, c.symbolid as sid, c.symbol as sym, c.longname as longname, c.shortname, c.exchange as e, c.timegranularity as tg, p.patternid as pid, a.direction as d, cast(atbaridentified as timestamp) as pet, cast(patternstarttime as timestamp) as pst, patternprice as patp, breakoutprice as pe, breakoutbars as be, errormargin as erm, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, cast(x0 as timestamp) as x0, cast(x1 as timestamp) as x1, cast(x2 as timestamp) as x2, cast(( case when x3 = ? then ? else x3 end) as timestamp) as x3, cast(( case when x4 = ? then ? else x4 end) as timestamp) as x4, cast(( case when x5 = ? then ? else x5 end) as timestamp) as x5, cast(( case when x6 = ? then ? else x6 end) as timestamp) as x6, cast(( case when x7 = ? then ? else x7 end) as timestamp) as x7, cast(( case when x8 = ? then ? else x8 end) as timestamp) as x8, cast(( case when x9 = ? then ? else x9 end) as timestamp) as x9, cast(atbaridentified as timestamp) as patternendtime, cast(atbaridentified as timestamp) as atbar, cast(( case when approachingtimestamp = ? then ? else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzos, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as relevant, cast(?.? as double precision) as premium, cast(? as bigint) as instrumentid, ? as derivativeid, ? as underlyingid, ? as isunderlying from symbols c inner join brokersymbollist b on c.symbolid = b.symbolid inner join downloadersymbolsettings dss on dss.symbolid = c.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join keylevels_results a on a.symbolid = c.symbolid inner join hrspatterns p on a.patternid = p.patternid left outer join relevance_keylevels_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and (((c.symbol ilike ? and timegranularity <= ?))) and patternclassid = ? and patternlengthbars >= ? and a.patternid & ? > ? and dftt.dayofweek = ? and a.resultuid > ? and c.nonliquid = ? and c.deleted = ? and dss.enabled = ? order by relevant desc, age asc, patternendtime desc, qtp desc limit ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 01 11 3,848 4m10s 65ms [ User: postgres - Total duration: 4m10s - Times executed: 3848 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 4m10s - Times executed: 3848 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 489 AND (((c.symbol ilike '%xauusd%' AND timegranularity <= 1440))) AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '3' > 0 AND dftt.dayofweek = '3' AND a.resultuid > '1408752327' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:51:58 Duration: 5s260ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 489 AND (((c.symbol ilike '%xauusd%' AND timegranularity <= 1440))) AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '3' > 0 AND dftt.dayofweek = '3' AND a.resultuid > '1408752327' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:56:02 Duration: 3s805ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 667 AND (((c.symbol ilike '%nzdusd%' AND timegranularity <= 1440))) AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '3' > 0 AND dftt.dayofweek = '3' AND a.resultuid > '-323411529' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:56:32 Duration: 3s496ms Database: acaweb_fx User: postgres Remote: 192.168.0.239 Application: PostgreSQL JDBC Driver Bind query: yes
11 3,484 1m30s 0ms 1s850ms 26ms insert into fibonacci_results (bandwidth, pattern, gmttimefound, direction, patternstarttime, patternendtime, patternstartprice, patternendprice, qtytp, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, patternlengthbars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) values (?.?, ?, ?::timestamp without time zone, ?, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?, ?, ?, ?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Mar 01 11 3,484 1m30s 26ms [ User: postgres - Total duration: 1m30s - Times executed: 3484 ]
[ Application: [unknown] - Total duration: 1m30s - Times executed: 3484 ]
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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', '2023-03-01 09:12:40'::timestamp without time zone, - 1, '2023-02-21 08:00:00'::timestamp without time zone, '2023-03-01 00:00:00'::timestamp without time zone, 1.215200000000000058000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 1.192499999999999893000000000000, '2023-02-27 00:00:00'::timestamp without time zone, 1.214800000000000102000000000000, '2023-02-28 08:00:00'::timestamp without time zone, 1.201699999999999990000000000000, '2023-02-28 16:00:00'::timestamp without time zone, 1.224000000000000199000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.862083333333332535400000000000, - 1.000000000000000000000000000000, 11.790447534833214500000000000000, 18, 1.201699999999999990000000000000, 1.210217842051990012000000000000, 1.187917842051989803000000000000, 1.206468824275060081000000000000, 1.195633961816150004000000000000, 1.212849999999999984000000000000, 1.215482157948010178000000000000, 515840221185868300, 0.275833333333334929100000000000, 'BC=0.618*AB (0.587) ', 0, 'ABCD|-1|2023-02-21 08:00:00|1.2152|-1|4|18|BC=0.618*AB (0.587)|0|515840221185868300|1899-12-29 00:00:00|2023-02-27 00:00:00|2023-02-28 08:00:00|2023-02-28 16:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:15:29 Duration: 1s850ms 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', '2023-03-01 08:58:16'::timestamp without time zone, - 1, '2023-02-27 15:00:00'::timestamp without time zone, '2023-03-01 10:00:00'::timestamp without time zone, 9.766000000000000014000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 9.682999999999999829000000000000, '2023-02-28 10:00:00'::timestamp without time zone, 9.801999999999999602000000000000, '2023-02-28 15:00:00'::timestamp without time zone, 9.730999999999999872000000000000, '2023-02-28 17:00:00'::timestamp without time zone, 9.849999999999999645000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.825363558597092650200000000000, - 1.000000000000000000000000000000, 26.396637271513544220000000000000, 12, 9.730999999999999872000000000000, 9.776453955344699409000000000000, 9.657453955344699636000000000000, 9.756447986041798970000000000000, 9.698629661709500027000000000000, 9.790499999999999758000000000000, 9.804546044655300108000000000000, 515840247101146300, 0.349272882805814755000000000000, 'BC=0.618*AB (0.597) ', 0, 'ABCD|-1|2023-02-27 15:00:00|9.766|-1|4|12|BC=0.618*AB (0.597)|0|515840247101146300|1899-12-29 00:00:00|2023-02-28 10:00:00|2023-02-28 15:00:00|2023-02-28 17:00:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:01:04 Duration: 852ms 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', '2023-03-01 08:58:08'::timestamp without time zone, - 1, '2023-02-28 19:15:00'::timestamp without time zone, '2023-03-01 10:45:00'::timestamp without time zone, 1.008950000000000014000000000000, - 1.000000000000000000000000000000, 4, - 1.000000000000000000000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 1.004189999999999916000000000000, '2023-03-01 00:00:00'::timestamp without time zone, 1.010780000000000012000000000000, '2023-03-01 07:30:00'::timestamp without time zone, 1.006879999999999997200000000000, '2023-03-01 10:30:00'::timestamp without time zone, 1.013470000000000093000000000000, '1899-12-29 00:00:00'::timestamp without time zone, 0.905776631773401508200000000000, - 1.000000000000000000000000000000, 24.801865490430969880000000000000, 72, 1.006879999999999997200000000000, 1.009397156014467001000000000000, 1.002807156014466905000000000000, 1.008289262420297927000000000000, 1.005087390509795009000000000000, 1.010175000000000045000000000000, 1.010952843985533089000000000000, 515840247946273300, 0.188446736453196928000000000000, 'BC=0.618*AB (0.592) ', 0, 'ABCD|-1|2023-02-28 19:15:00|1.00895|-1|4|72|BC=0.618*AB (0.592)|0|515840247946273300|1899-12-29 00:00:00|2023-03-01 00:00:00|2023-03-01 07:30:00|2023-03-01 10:30:00|1899-12-29 00:00:00', - 1, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:00:56 Duration: 841ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
12 3,231 4m48s 0ms 16s89ms 89ms select distinct a.resultuid as ruid, s.symbolid as sid, symbol as sym, longname, shortname, exchange as e, timegranularity as tg, p.patternid as pid, direction as d, patternstarttime as pst, patternendtime as pet, patternstartprice as psp, patternendprice as pep, pricex as px, timex as tx, pricea as pa, timea as ta, priceb as pb, timeb as tb, pricec as pc, timec as tc, priced as pd, timed as td, averagequality as aq, timequality as tq, errormargin as rq, (? - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, patternlengthbars as l, temporarypattern as tp, bandwidth as bw, qtytp as qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ?) then ? else ? end as relevant from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join symbolgroup sg on s.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join fibonacci_results a on a.symbolid = s.symbolid inner join fibonaccipatterns p on a.pattern = p.patternname left outer join relevance_fibonacci_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and patternlengthbars >= ? and averagequality >= ?.? and (timequality >= ?.? or timequality = ?) and errormargin >= ?.? and ? - noise >= ?.? and s.nonliquid = ? and patternid & ? > ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and patternendprice > ? and a.resultuid > ? and dftt.dayofweek = ? order by relevant desc, age asc, patternendtime desc, averagequality desc limit ?;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Mar 01 11 3,231 4m48s 89ms [ User: postgres - Total duration: 4m48s - Times executed: 3231 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 4m48s - Times executed: 3231 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 622 AND sg.groupid = 515852059853768308 AND patternlengthbars >= 20 AND averagequality >= 0.3 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice > - 1 AND a.resultuid > 601555599750214302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2023-03-01 11:16:38 Duration: 16s89ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 692 AND sg.groupid = 515852059916698308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice > - 1 AND a.resultuid > 601555656822457302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2023-03-01 11:56:54 Duration: 9s419ms Database: acaweb_fx User: postgres Remote: 192.168.1.45 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 622 AND sg.groupid = 515852059853768308 AND patternlengthbars >= 20 AND averagequality >= 0.3 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice > - 1 AND a.resultuid > 601555599750214302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2023-03-01 11:12:21 Duration: 9s182ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
13 3,230 2m21s 0ms 9s10ms 43ms select distinct a.resultuid as ruid, s.symbolid as sid, symbol as sym, longname, shortname, exchange as e, timegranularity as tg, p.patternid as pid, direction as d, patternstarttime as pst, patternendtime as pet, patternstartprice as psp, patternendprice as pep, pricex as px, timex as tx, pricea as pa, timea as ta, priceb as pb, timeb as tb, pricec as pc, timec as tc, priced as pd, timed as td, averagequality as aq, timequality as tq, errormargin as rq, (? - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, patternlengthbars as l, temporarypattern as tp, bandwidth as bw, qtytp as qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ?) then ? else ? end as relevant from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join symbolgroup sg on s.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join fibonacci_results a on a.symbolid = s.symbolid inner join fibonaccipatterns p on a.pattern = p.patternname left outer join relevance_fibonacci_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and patternlengthbars >= ? and averagequality >= ?.? and (timequality >= ?.? or timequality = ?) and errormargin >= ?.? and ? - noise >= ?.? and s.nonliquid = ? and patternid & ? > ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and patternendprice = ? and a.resultuid > ? and dftt.dayofweek = ? order by relevant desc, age asc, patternendtime desc, averagequality desc limit ?;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Mar 01 11 3,230 2m21s 43ms [ User: postgres - Total duration: 2m21s - Times executed: 3230 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2m21s - Times executed: 3230 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 489 AND sg.groupid = 515852059798808308 AND patternlengthbars >= 20 AND averagequality >= 0.3 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 601555190896580302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2023-03-01 11:10:20 Duration: 9s10ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 489 AND sg.groupid = 515852059798808308 AND patternlengthbars >= 20 AND averagequality >= 0.3 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 601555190896580302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2023-03-01 11:01:54 Duration: 6s664ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 632 AND sg.groupid = 515852059882874308 AND patternlengthbars >= 20 AND averagequality >= 0.3 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 601555599949148302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2023-03-01 11:10:10 Duration: 4s234ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
14 3,229 1m8s 0ms 815ms 21ms 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 #14
Day Hour Count Duration Avg duration Mar 01 11 3,229 1m8s 21ms [ User: postgres - Total duration: 1m8s - Times executed: 3229 ]
[ Application: [unknown] - Total duration: 1m8s - Times executed: 3229 ]
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2023-03-01 08:00:00', '374.346', '380.349', '374.346', '379.349', '7928', '515840231094634300', '0', '2023-03-01 11:04:43.374', '2023-03-01 11:04:43.373') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '374.346', high = '380.349', low = '374.346', close = '379.349', volume = '7928', bsf = '0', sastdatetimewritten = '2023-03-01 11:04:43.374', sastdatetimereceived = '2023-03-01 11:04:43.373';
Date: 2023-03-01 11:04:44 Duration: 815ms 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 ('2023-02-28 21:00:00', '250.41', '250.42', '249.28', '249.3', '5148', '515840247896450300', '0', '2023-03-01 11:14:32.88', '2023-03-01 11:14:32.843') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '250.41', high = '250.42', low = '249.28', close = '249.3', volume = '5148', bsf = '0', sastdatetimewritten = '2023-03-01 11:14:32.88', sastdatetimereceived = '2023-03-01 11:14:32.843';
Date: 2023-03-01 11:14:33 Duration: 289ms 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 ('2023-03-01 10:00:00', '164.475', '165.475', '163.95', '164.4', '1149', '515840246756337300', '0', '2023-03-01 11:00:31.461', '2023-03-01 11:00:31.46') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '164.475', high = '165.475', low = '163.95', close = '164.4', volume = '1149', bsf = '0', sastdatetimewritten = '2023-03-01 11:00:31.461', sastdatetimereceived = '2023-03-01 11:00:31.46';
Date: 2023-03-01 11:00:31 Duration: 232ms Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
15 3,035 3m38s 0ms 17s947ms 72ms select distinct patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, longname, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as relevant from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join symbolgroup sg on s.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join autochartist_results a on a.symbolid = s.symbolid inner join patterns p on a.pattern = p.patternname left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and breakout = ? and patternlengthbars >= ? and patternquality >= ?.? and initialtrend >= ?.? and symmetry >= ?.? and noise <= ?.? and volumeincrease >= ?.? and temporarypattern = ? and patternid & ? > ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and a.resultuid > ? and s.nonliquid = ? and dftt.dayofweek = ? order by relevant desc, age asc, patternendtime desc, patternquality desc limit ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Mar 01 11 3,035 3m38s 72ms [ User: postgres - Total duration: 3m38s - Times executed: 3035 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3m38s - Times executed: 3035 ]
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND sg.groupid = 515852059752350308 AND breakout = - 1 AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:23:21 Duration: 17s947ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 643 AND sg.groupid = 515852059885848308 AND breakout = - 1 AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:45:29 Duration: 15s255ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND sg.groupid = 515852059752285308 AND breakout = - 1 AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:23:14 Duration: 14s529ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
16 3,033 3m19s 0ms 16s57ms 65ms select distinct patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, longname, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as relevant from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join symbolgroup sg on s.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join autochartist_results a on a.symbolid = s.symbolid inner join patterns p on a.pattern = p.patternname left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and breakout >= ?.? and patternendtime = latestbaratbreakouttime and patternlengthbars >= ? and patternquality >= ?.? and initialtrend >= ?.? and symmetry >= ?.? and noise <= ?.? and volumeincrease >= ?.? and temporarypattern = ? and patternid & ? > ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and a.resultuid > ? and s.nonliquid = ? and dftt.dayofweek = ? order by relevant desc, age asc, patternendtime desc, patternquality desc limit ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 01 11 3,033 3m19s 65ms [ User: postgres - Total duration: 3m19s - Times executed: 3033 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3m19s - Times executed: 3033 ]
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND sg.groupid = 515852059752350308 AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:23:21 Duration: 16s57ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 643 AND sg.groupid = 515852059885848308 AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:45:29 Duration: 15s62ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND sg.groupid = 515852059752285308 AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:23:14 Duration: 14s470ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
17 2,933 826ms 0ms 543ms 0ms insert into roundnumber_increment (symbolid, increment_a, date) values (?, ?.?, ?::timestamp);Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Mar 01 11 2,933 826ms 0ms [ User: postgres - Total duration: 826ms - Times executed: 2933 ]
[ Application: [unknown] - Total duration: 826ms - Times executed: 2933 ]
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INSERT INTO roundnumber_increment (symbolid, increment_a, date) VALUES (500991627550803200, 0.0100000000, '2023-03-01T09:48:40.812361'::timestamp);
Date: 2023-03-01 11:48:41 Duration: 543ms Database: acaweb_fx User: postgres Remote: 192.168.4.38 Application: [unknown]
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INSERT INTO roundnumber_increment (symbolid, increment_a, date) VALUES (500991632123012200, 10.0000000000, '2023-03-01T09:48:40.818023'::timestamp);
Date: 2023-03-01 11:48:41 Duration: 23ms Database: acaweb_fx User: postgres Remote: 192.168.4.38 Application: [unknown]
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INSERT INTO roundnumber_increment (symbolid, increment_a, date) VALUES (500991628220122200, 0.1000000000, '2023-03-01T09:48:40.814156'::timestamp);
Date: 2023-03-01 11:48:41 Duration: 15ms Database: acaweb_fx User: postgres Remote: 192.168.4.38 Application: [unknown]
18 2,923 4s59ms 0ms 6ms 1ms select coalesce(bim.code, s.symbol) as name, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ? group by ?, ?, ?, ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Mar 01 11 2,923 4s59ms 1ms [ User: postgres - Total duration: 4s59ms - Times executed: 2923 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 4s59ms - Times executed: 2923 ]
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SELECT coalesce(bim.code, s.symbol) as name, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840248266548300' GROUP BY 1, 2, 3, 4;
Date: 2023-03-01 11:53:52 Duration: 6ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT coalesce(bim.code, s.symbol) as name, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840248267605300' GROUP BY 1, 2, 3, 4;
Date: 2023-03-01 11:12:09 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT coalesce(bim.code, s.symbol) as name, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone FROM symbols s LEFT JOIN brokersymbollist bsl ON bsl.brokerid = '529' AND bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable df ON df.classname ILIKE dss.classname LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = '529' AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = '515840248627636300' GROUP BY 1, 2, 3, 4;
Date: 2023-03-01 11:06:03 Duration: 4ms Database: acaweb_fx User: postgres Remote: 192.168.1.250 Application: PostgreSQL JDBC Driver Bind query: yes
19 2,590 24s64ms 0ms 406ms 9ms select distinct a.resultuid as ruid, s.symbolid as sid, symbol as sym, longname, shortname, exchange as e, timegranularity as tg, p.patternid as pid, direction as d, patternstarttime as pst, patternendtime as pet, patternstartprice as psp, patternendprice as pep, pricex as px, timex as tx, pricea as pa, timea as ta, priceb as pb, timeb as tb, pricec as pc, timec as tc, priced as pd, timed as td, averagequality as aq, timequality as tq, errormargin as rq, (? - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, patternlengthbars as l, temporarypattern as tp, bandwidth as bw, qtytp as qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ?) then ? else ? end as relevant from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join fibonacci_results a on a.symbolid = s.symbolid inner join fibonaccipatterns p on a.pattern = p.patternname left outer join relevance_fibonacci_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and (((symbol ilike ? and timegranularity <= ?))) and patternlengthbars >= ? and averagequality >= ?.? and (timequality >= ?.? or timequality = ?) and errormargin >= ?.? and ? - noise >= ?.? and s.nonliquid = ? and patternid & ? > ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and patternendprice > ? and a.resultuid > ? and dftt.dayofweek = ? order by relevant desc, age asc, patternendtime desc, averagequality desc limit ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Mar 01 11 2,590 24s64ms 9ms [ User: postgres - Total duration: 24s64ms - Times executed: 2590 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 24s64ms - Times executed: 2590 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 489 AND (((symbol ilike '%dow30%' AND timegranularity <= 1440))) AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 63 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice > - 1 AND a.resultuid > 601551245439650302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2023-03-01 11:45:55 Duration: 406ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%equities (all ภายในวัน)%' AND timegranularity <= 1440))) AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice > - 1 AND a.resultuid > 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2023-03-01 11:12:09 Duration: 377ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 489 AND (((symbol ilike '%sp500%' AND timegranularity <= 1440))) AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 63 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice > - 1 AND a.resultuid > 601551416598291302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2023-03-01 11:58:00 Duration: 360ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
20 2,589 17s582ms 0ms 827ms 6ms select distinct a.resultuid as ruid, s.symbolid as sid, symbol as sym, longname, shortname, exchange as e, timegranularity as tg, p.patternid as pid, direction as d, patternstarttime as pst, patternendtime as pet, patternstartprice as psp, patternendprice as pep, pricex as px, timex as tx, pricea as pa, timea as ta, priceb as pb, timeb as tb, pricec as pc, timec as tc, priced as pd, timed as td, averagequality as aq, timequality as tq, errormargin as rq, (? - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, patternlengthbars as l, temporarypattern as tp, bandwidth as bw, qtytp as qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ?) then ? else ? end as relevant from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join fibonacci_results a on a.symbolid = s.symbolid inner join fibonaccipatterns p on a.pattern = p.patternname left outer join relevance_fibonacci_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and (((symbol ilike ? and timegranularity <= ?))) and patternlengthbars >= ? and averagequality >= ?.? and (timequality >= ?.? or timequality = ?) and errormargin >= ?.? and ? - noise >= ?.? and s.nonliquid = ? and patternid & ? > ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and patternendprice = ? and a.resultuid > ? and dftt.dayofweek = ? order by relevant desc, age asc, patternendtime desc, averagequality desc limit ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Mar 01 11 2,589 17s582ms 6ms [ User: postgres - Total duration: 17s582ms - Times executed: 2589 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 17s582ms - Times executed: 2589 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 489 AND (((symbol ilike '%eurjpy%' AND timegranularity <= 1440))) AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 63 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 601554060918336302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2023-03-01 11:58:02 Duration: 827ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%equities (all ภายในวัน)%' AND timegranularity <= 1440))) AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2023-03-01 11:12:09 Duration: 483ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%ethusd%' AND timegranularity <= 1440))) AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 63 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice = - 1 AND a.resultuid > 601555089967699302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2023-03-01 11:57:08 Duration: 351ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 3h33m9s 3h33m9s 3h33m9s 1 3h33m9s select cleanupt30 (?, ?, ?);Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 01 11 1 3h33m9s 3h33m9s [ User: postgres - Total duration: 3h33m9s - Times executed: 1 ]
[ Application: psql - Total duration: 3h33m9s - Times executed: 1 ]
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select cleanupt30 (30, 20, 20);
Date: 2023-03-01 11:58:10 Duration: 3h33m9s Database: acaweb_fx User: postgres Remote: [local] Application: psql
2 27m34s 31m41s 29m38s 2 59m16s select updateageforrelevantresults ();Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Mar 01 11 2 59m16s 29m38s [ User: postgres - Total duration: 59m16s - Times executed: 2 ]
[ Application: psql - Total duration: 59m16s - Times executed: 2 ]
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select updateageforrelevantresults ();
Date: 2023-03-01 11:18:44 Duration: 31m41s Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updateageforrelevantresults ();
Date: 2023-03-01 11:59:36 Duration: 27m34s Database: acaweb_fx User: postgres Remote: [local] Application: psql
3 5m38s 6m48s 6m16s 4 25m6s 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 #3
Day Hour Count Duration Avg duration Mar 01 11 4 25m6s 6m16s [ User: postgres - Total duration: 25m6s - Times executed: 4 ]
[ Application: psql - Total duration: 25m6s - Times executed: 4 ]
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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: 2023-03-01 11:33:07 Duration: 6m48s 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: 2023-03-01 11:17:46 Duration: 6m30s 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: 2023-03-01 11:47:20 Duration: 6m8s Database: acaweb_fx User: postgres Remote: [local] Application: psql
4 4m57s 7m10s 6m14s 4 24m58s 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 #4
Day Hour Count Duration Avg duration Mar 01 11 4 24m58s 6m14s [ User: postgres - Total duration: 24m58s - Times executed: 4 ]
[ Application: psql - Total duration: 24m58s - Times executed: 4 ]
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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: 2023-03-01 11:40:21 Duration: 7m10s 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: 2023-03-01 11:08:31 Duration: 6m26s 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: 2023-03-01 11:24:12 Duration: 6m24s Database: acaweb_fx User: postgres Remote: [local] Application: psql
5 3m47s 8m16s 6m1s 2 12m3s select gen_whatshot ();Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Mar 01 11 2 12m3s 6m1s [ User: postgres - Total duration: 12m3s - Times executed: 2 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12m3s - Times executed: 2 ]
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select gen_whatshot ();
Date: 2023-03-01 11:16:32 Duration: 8m16s Database: acaweb_fx User: postgres Remote: 192.168.4.150 Application: PostgreSQL JDBC Driver Bind query: yes
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select gen_whatshot ();
Date: 2023-03-01 11:28:28 Duration: 3m47s Database: acaweb_fx User: postgres Remote: 192.168.4.150 Application: PostgreSQL JDBC Driver Bind query: yes
6 2m37s 4m6s 3m29s 4 13m58s select updaterelevantforrelevantresults ();Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Mar 01 11 4 13m58s 3m29s [ User: postgres - Total duration: 13m58s - Times executed: 4 ]
[ Application: psql - Total duration: 13m58s - Times executed: 4 ]
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select updaterelevantforrelevantresults ();
Date: 2023-03-01 11:39:37 Duration: 4m6s Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updaterelevantforrelevantresults ();
Date: 2023-03-01 11:54:31 Duration: 3m59s Database: acaweb_fx User: postgres Remote: [local] Application: psql
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select updaterelevantforrelevantresults ();
Date: 2023-03-01 11:08:45 Duration: 3m14s Database: acaweb_fx User: postgres Remote: [local] Application: psql
7 148ms 31m17s 2m34s 13 33m26s 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 ), results as ( select distinct on (s.symbolid) kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, 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 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 relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true where kr.gmttimefound > now() - interval ? and dss.enabled = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or s.symbol in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) order by symbolid, identified desc, patternlengthbars desc ) select * from results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by identified desc, length desc;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Mar 01 11 13 33m26s 2m34s [ User: postgres - Total duration: 33m26s - Times executed: 13 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 33m26s - Times executed: 13 ]
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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 ), results AS ( SELECT DISTINCT ON (s.symbolid) kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, 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 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 relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 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 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') ORDER BY symbolid, identified DESC, patternlengthbars DESC ) SELECT * from results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY identified DESC, length DESC;
Date: 2023-03-01 11:28:46 Duration: 31m17s Database: acaweb_fx User: postgres Remote: 192.168.1.135 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 ), results AS ( SELECT DISTINCT ON (s.symbolid) kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, 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 FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '700' 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 relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 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 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') ORDER BY symbolid, identified DESC, patternlengthbars DESC ) SELECT * from results WHERE (FALSE = 't' OR relevant = 1) AND ('0' = 0 OR age <= '0') ORDER BY identified DESC, length DESC;
Date: 2023-03-01 11:31:27 Duration: 49s242ms Database: acaweb_fx User: postgres Remote: 192.168.1.135 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 ), results AS ( SELECT DISTINCT ON (s.symbolid) kr.resultuid AS resultuid, kr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, 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 FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = '642' 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 relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND (kr.simulation = 0 OR kr.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 s.symbol in ('')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('0' = 0 OR kr.patternlengthbars <= '0') ORDER BY symbolid, identified DESC, patternlengthbars DESC ) SELECT * from results WHERE (FALSE = 't' OR relevant = 1) AND ('10' = 0 OR age <= '10') ORDER BY identified DESC, length DESC;
Date: 2023-03-01 11:34:02 Duration: 22s392ms Database: acaweb_fx User: postgres Remote: 192.168.1.135 Application: PostgreSQL JDBC Driver Bind query: yes
8 7s386ms 4m18s 2m13s 9 20m3s refresh materialized view concurrently latest_t15_candle_view;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Mar 01 11 9 20m3s 2m13s [ User: postgres - Total duration: 20m3s - Times executed: 9 ]
[ Application: [unknown] - Total duration: 20m3s - Times executed: 9 ]
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refresh materialized view concurrently latest_t15_candle_view;
Date: 2023-03-01 11:14:07 Duration: 4m18s 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: 2023-03-01 11:17:26 Duration: 3m34s 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: 2023-03-01 11:35:16 Duration: 3m27s Database: acaweb_fx User: postgres Remote: 192.168.4.98 Application: [unknown]
9 1s134ms 4m27s 57s449ms 128 2h2m33s 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 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 (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 ), 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 #9
Day Hour Count Duration Avg duration Mar 01 11 128 2h2m33s 57s449ms [ User: postgres - Total duration: 2h2m33s - Times executed: 128 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2h2m33s - Times executed: 128 ]
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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 = '529' AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN 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 (ar.simulation = 0 OR ar.simulation IS NULL) AND ('7' = 0 OR s.timegranularity in ('15', '30', '60', '120', '240', '480', '1440')) AND ('0' = 0 OR s.exchange in ('')) AND ('31' = 0 OR coalesce(bim.code, s.symbol) in ('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADJPY', 'CHFJPY', 'EURAUD', 'EURCAD', 'EURCHF', 'EURGBP', 'EURJPY', 'EURNZD', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'JPN225', 'NAS100', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDJPY', 'XAGUSD', 'XAUUSD')) AND ('0' = 0 OR ar.pattern in ('')) AND ('0' = 0 OR ('0' = 1 AND ar.breakout >= 0) OR ('0' = 2 AND ar.breakout < 0)) AND ('0' = 0 OR ar.patternlengthbars <= '0') and newLevels.filtered = false ), 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: 2023-03-01 11:12:41 Duration: 4m27s 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 = '479' 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 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 (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 ('263' = 0 OR coalesce(bim.code, s.symbol) in ('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHFNOK', 'EURAUD', 'EURCAD', 'EURCHF', 'EURCZK', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPSEK', 'GBPUSD', 'HKDJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'PnL', 'SGDJPY', 'TRYJPY', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDZAR', 'ZARJPY', 'ACCOR', 'ADIDAS', 'AIR-LIQUIDE', 'AIRBUS-GRP', 'ALLIANZ', 'ALSTOM', 'ARCELORMITL', 'AXA', 'BASF', 'BAYER', 'BEIERSDORF', 'BMW', 'BNP-PARIBAS', 'BOUYGUES', 'CAP-GEMINI', 'CARREFOUR', 'CONTINENTAL', 'CREDIT-AGRI', 'DANONE', 'DEUT-BOERSE', 'DEUT-TELEKM', 'DEUTSCHE-BK', 'DEUTSCHPOST', 'E.ON', 'EDF', 'ENGIE', 'FRESENI-MED', 'FRESENIUS', 'HEIDBGCEMNT', 'HENKEL', 'INFINEONTEC', 'KERING', 'LANXESS', 'LEGRAND', 'LINDE', 'LOREAL', 'LUFTHANSA', 'LVMH', 'MERCK-KGAA', 'MICHELIN', 'MUNICH-RE', 'ORANGE', 'PERNOD-RICD', 'PUBLICIS-GR', 'RENAULT', 'RWE', 'SAFRAN', 'SAINTGOBAIN', 'SANOFI', 'SAP', 'SCHNEIDELEC', 'SIEMENS', 'SOCIETE-GEN', 'SOLVAY', 'THYSSENKRUP', 'TOTAL', 'VALEO', 'VEOLIA-ENV', 'VINCI', 'VIVENDI', 'VOLKSWAGEN', 'XAGUSD', 'XAUUSD', 'ESTOX', 'FRENCH40', 'GERMAN30', 'UK100', 'US30', 'US500', 'USNDX', '3M', '3i-GROUP', 'ADMIRAL', 'AIG', 'ALIBABA', 'AMAZON', 'AMEX', 'ANGLO-AMERI', 'ANTOFAGASTA', 'APPLE', 'ASHTEAD', 'ASTRAZENECA', 'AT&T', 'AVIVA', 'BABCOCK', 'BAE-SYSTEMS', 'BAIDU', 'BALFOUR-B', 'BARCLAYS', 'BARRAT', 'BATS', 'BHP-BILITON', 'BNK-AMER', 'BOEING', 'BP', 'BRIT-FOODS', 'BRIT-LND', 'BT', 'BUNZL', 'BURBERRY', 'CAPITA', 'CARNIVAL', 'CAT', 'CENTRICA', 'CHEVRON', 'CISCO', 'CITI', 'COMPASS', 'CRH', 'DIAGEO', 'DIRECT-LINE', 'DISNEY', 'DRAX', 'EASYJET', 'EBAY', 'EXPERIAN', 'EXXON', 'FACEBOOK', 'FEDEX', 'FERRARI', 'FORD', 'GE', 'GLAXO', 'GLENCORE', 'GM', 'GOLDMANS', 'HALLIBURTON', 'HAMMERSON', 'HOME-DEP', 'HP', 'HSBC', 'IAG', 'IBM', 'IG-GROUP', 'IHG', 'IMI', 'IMP-TOBACCO', 'INCHCAPE', 'INTEL', 'INTERTEK', 'ITV', 'JOHNSON', 'JOHNSON-MAT', 'JPMORGAN', 'KINGFISHER', 'LAND-SEC', 'LEGAL-GEN', 'LLOYDS', 'LSE', 'M&S', 'MAN-GROUP', 'MATCH', 'MERCK', 'META', 'MICROSOFT', 'MONDI', 'MORGAN-S', 'MSTRCARD', 'McD', 'NAT-GRID', 'NETFLIX', 'NEXT', 'NIKE', 'OCADO', 'ORACLE', 'P&G', 'PAYPAL', 'PEARSON', 'PENNON', 'PEPSI', 'PERSIMMON', 'PETROFAC', 'PFIZER', 'PHIL-MOR', 'PRUDENTIAL', 'REED-ELSVR', 'RENTOKIL', 'RIGHTMOVE', 'RIO-TINTO', 'ROLLS-ROYCE', 'SAGE', 'SAINSBURY', 'SCHLUMBERGR', 'SEVERN-TRNT', 'SMITH-NEPH', 'SMITHS', 'SQUARE-INC', 'SSE', 'ST-JAMES', 'STAN-CHARTD', 'STARBUX', 'TAYLOR-WIMP', 'TESCO', 'TESLA', 'THOMAS-COOK', 'TRAVELRS', 'TRAVIS-PERK', 'TUI', 'TULLOW', 'UNILEVER', 'UNITED-UTIL', 'UTD-HLTH', 'VERIZON', 'VISA', 'VODAFONE', 'WALMART', 'WEIR-GROUP', 'WELLS-FG', 'WHITBREAD', 'WPP')) 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 ), 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: 2023-03-01 11:26:22 Duration: 4m2s 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 ), 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 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 (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 ('231' = 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', 'EURHUF', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'EUR_50', 'FRA_40', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'GBR_100', 'GER_30', 'HKDJPY', 'HKG_50', 'IOTAUSD', 'LTCEUR', 'LTCUSD', 'NAS100', 'NEOUSD', 'NOKJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'OMGUSD', 'SPX500', 'TRXUSD', 'US30', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHUF', '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', 'EURHUF', 'EURJPY', 'EURMXN', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPUSD', 'GBPZAR', 'HKDJPY', 'NOKJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDDKK', 'USDHUF', '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', 'GER_30', '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 ), 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: 2023-03-01 11:24:19 Duration: 3m49s Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
10 0ms 3h17m48s 57s326ms 6,458 4d6h50m16s insert into t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 01 11 6,458 4d6h50m16s 57s326ms [ User: postgres - Total duration: 4d6h50m16s - Times executed: 6458 ]
[ Application: [unknown] - Total duration: 4d6h50m16s - Times executed: 6458 ]
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-03 09:00:00', '6.335', '6.335', '6.335', '6.335', '2', '600197227125639300', '0', '2023-03-01 08:40:22.766', '2023-03-01 08:40:22.766') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '6.335', high = '6.335', low = '6.335', close = '6.335', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:40:22.766', sastdatetimereceived = '2023-03-01 08:40:22.766';
Date: 2023-03-01 11:58:11 Duration: 3h17m48s Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-12-02 09:00:00', '0', '0', '0', '0', '2', '500991632125453200', '0', '2023-03-01 08:41:12.178', '2023-03-01 08:41:12.177') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '0', high = '0', low = '0', close = '0', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:41:12.178', sastdatetimereceived = '2023-03-01 08:41:12.177';
Date: 2023-03-01 11:58:11 Duration: 3h16m59s Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ('2022-10-03 09:00:00', '25.88', '25.88', '25.88', '25.88', '2', '600197227405596300', '0', '2023-03-01 08:43:37.359', '2023-03-01 08:43:37.358') ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = '25.88', high = '25.88', low = '25.88', close = '25.88', volume = '2', bsf = '0', sastdatetimewritten = '2023-03-01 08:43:37.359', sastdatetimereceived = '2023-03-01 08:43:37.358';
Date: 2023-03-01 11:58:11 Duration: 3h14m33s Database: acaweb_fx User: postgres Remote: 192.168.4.142 Application: [unknown] Bind query: yes
11 166ms 3m2s 31s149ms 145 1h15m16s (( select distinct ? 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 = ? union select distinct ? as patterntype, ar.resultuid as resultuid, ?, ? from autochartist_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = ? inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?))) union all (( select distinct ? 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 = ? union select distinct ? as patterntype, ar.resultuid as resultuid, ?, ? from fibonacci_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = ? inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ?))) union all (( select distinct ? 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 = ? union select distinct ? as patterntype, ar.resultuid as resultuid, ?, ? from keylevels_results ar inner join brokersymbollist bsl on bsl.symbolid = ar.symbolid and bsl.brokerid = ? inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?)));Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Mar 01 11 145 1h15m16s 31s149ms [ User: postgres - Total duration: 1h15m16s - Times executed: 145 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1h15m16s - Times executed: 145 ]
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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 = '692' 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 = '692' 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 = '692' 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 = '692' 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 = '692' 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 = '692' inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1)));
Date: 2023-03-01 11:12:50 Duration: 3m2s Database: acaweb_fx User: postgres Remote: 192.168.1.45 Application: PostgreSQL JDBC Driver Bind query: yes
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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 = '692' 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 = '692' 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 = '692' 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 = '692' 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 = '692' 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 = '692' inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1)));
Date: 2023-03-01 11:36:05 Duration: 2m6s Database: acaweb_fx User: postgres Remote: 192.168.1.45 Application: PostgreSQL JDBC Driver Bind query: yes
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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 = '667' 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 = '667' 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 = '667' 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 = '667' 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 = '667' 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 = '667' inner join symbols s on s.symbolid = bsl.symbolid where resultuid > ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1)));
Date: 2023-03-01 11:11:13 Duration: 1m58s Database: acaweb_fx User: postgres Remote: 192.168.0.239 Application: PostgreSQL JDBC Driver Bind query: yes
12 536ms 2m34s 22s261ms 128 47m29s 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 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 (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 <= ?) ), 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 #12
Day Hour Count Duration Avg duration Mar 01 11 128 47m29s 22s261ms [ User: postgres - Total duration: 47m29s - Times executed: 128 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 47m29s - Times executed: 128 ]
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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 = '479' 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 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 (kr.simulation = 0 OR kr.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 ('263' = 0 OR coalesce(bim.code, s.symbol) in ('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHFNOK', 'EURAUD', 'EURCAD', 'EURCHF', 'EURCZK', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPSEK', 'GBPUSD', 'HKDJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'PnL', 'SGDJPY', 'TRYJPY', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDZAR', 'ZARJPY', 'ACCOR', 'ADIDAS', 'AIR-LIQUIDE', 'AIRBUS-GRP', 'ALLIANZ', 'ALSTOM', 'ARCELORMITL', 'AXA', 'BASF', 'BAYER', 'BEIERSDORF', 'BMW', 'BNP-PARIBAS', 'BOUYGUES', 'CAP-GEMINI', 'CARREFOUR', 'CONTINENTAL', 'CREDIT-AGRI', 'DANONE', 'DEUT-BOERSE', 'DEUT-TELEKM', 'DEUTSCHE-BK', 'DEUTSCHPOST', 'E.ON', 'EDF', 'ENGIE', 'FRESENI-MED', 'FRESENIUS', 'HEIDBGCEMNT', 'HENKEL', 'INFINEONTEC', 'KERING', 'LANXESS', 'LEGRAND', 'LINDE', 'LOREAL', 'LUFTHANSA', 'LVMH', 'MERCK-KGAA', 'MICHELIN', 'MUNICH-RE', 'ORANGE', 'PERNOD-RICD', 'PUBLICIS-GR', 'RENAULT', 'RWE', 'SAFRAN', 'SAINTGOBAIN', 'SANOFI', 'SAP', 'SCHNEIDELEC', 'SIEMENS', 'SOCIETE-GEN', 'SOLVAY', 'THYSSENKRUP', 'TOTAL', 'VALEO', 'VEOLIA-ENV', 'VINCI', 'VIVENDI', 'VOLKSWAGEN', 'XAGUSD', 'XAUUSD', 'ESTOX', 'FRENCH40', 'GERMAN30', 'UK100', 'US30', 'US500', 'USNDX', '3M', '3i-GROUP', 'ADMIRAL', 'AIG', 'ALIBABA', 'AMAZON', 'AMEX', 'ANGLO-AMERI', 'ANTOFAGASTA', 'APPLE', 'ASHTEAD', 'ASTRAZENECA', 'AT&T', 'AVIVA', 'BABCOCK', 'BAE-SYSTEMS', 'BAIDU', 'BALFOUR-B', 'BARCLAYS', 'BARRAT', 'BATS', 'BHP-BILITON', 'BNK-AMER', 'BOEING', 'BP', 'BRIT-FOODS', 'BRIT-LND', 'BT', 'BUNZL', 'BURBERRY', 'CAPITA', 'CARNIVAL', 'CAT', 'CENTRICA', 'CHEVRON', 'CISCO', 'CITI', 'COMPASS', 'CRH', 'DIAGEO', 'DIRECT-LINE', 'DISNEY', 'DRAX', 'EASYJET', 'EBAY', 'EXPERIAN', 'EXXON', 'FACEBOOK', 'FEDEX', 'FERRARI', 'FORD', 'GE', 'GLAXO', 'GLENCORE', 'GM', 'GOLDMANS', 'HALLIBURTON', 'HAMMERSON', 'HOME-DEP', 'HP', 'HSBC', 'IAG', 'IBM', 'IG-GROUP', 'IHG', 'IMI', 'IMP-TOBACCO', 'INCHCAPE', 'INTEL', 'INTERTEK', 'ITV', 'JOHNSON', 'JOHNSON-MAT', 'JPMORGAN', 'KINGFISHER', 'LAND-SEC', 'LEGAL-GEN', 'LLOYDS', 'LSE', 'M&S', 'MAN-GROUP', 'MATCH', 'MERCK', 'META', 'MICROSOFT', 'MONDI', 'MORGAN-S', 'MSTRCARD', 'McD', 'NAT-GRID', 'NETFLIX', 'NEXT', 'NIKE', 'OCADO', 'ORACLE', 'P&G', 'PAYPAL', 'PEARSON', 'PENNON', 'PEPSI', 'PERSIMMON', 'PETROFAC', 'PFIZER', 'PHIL-MOR', 'PRUDENTIAL', 'REED-ELSVR', 'RENTOKIL', 'RIGHTMOVE', 'RIO-TINTO', 'ROLLS-ROYCE', 'SAGE', 'SAINSBURY', 'SCHLUMBERGR', 'SEVERN-TRNT', 'SMITH-NEPH', 'SMITHS', 'SQUARE-INC', 'SSE', 'ST-JAMES', 'STAN-CHARTD', 'STARBUX', 'TAYLOR-WIMP', 'TESCO', 'TESLA', 'THOMAS-COOK', 'TRAVELRS', 'TRAVIS-PERK', 'TUI', 'TULLOW', 'UNILEVER', 'UNITED-UTIL', 'UTD-HLTH', 'VERIZON', 'VISA', 'VODAFONE', 'WALMART', 'WEIR-GROUP', 'WELLS-FG', 'WHITBREAD', 'WPP')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.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: 2023-03-01 11:37:45 Duration: 2m34s Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_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 = '479' 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 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 (kr.simulation = 0 OR kr.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 ('263' = 0 OR coalesce(bim.code, s.symbol) in ('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHFNOK', 'EURAUD', 'EURCAD', 'EURCHF', 'EURCZK', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPSEK', 'GBPUSD', 'HKDJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'PnL', 'SGDJPY', 'TRYJPY', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDZAR', 'ZARJPY', 'ACCOR', 'ADIDAS', 'AIR-LIQUIDE', 'AIRBUS-GRP', 'ALLIANZ', 'ALSTOM', 'ARCELORMITL', 'AXA', 'BASF', 'BAYER', 'BEIERSDORF', 'BMW', 'BNP-PARIBAS', 'BOUYGUES', 'CAP-GEMINI', 'CARREFOUR', 'CONTINENTAL', 'CREDIT-AGRI', 'DANONE', 'DEUT-BOERSE', 'DEUT-TELEKM', 'DEUTSCHE-BK', 'DEUTSCHPOST', 'E.ON', 'EDF', 'ENGIE', 'FRESENI-MED', 'FRESENIUS', 'HEIDBGCEMNT', 'HENKEL', 'INFINEONTEC', 'KERING', 'LANXESS', 'LEGRAND', 'LINDE', 'LOREAL', 'LUFTHANSA', 'LVMH', 'MERCK-KGAA', 'MICHELIN', 'MUNICH-RE', 'ORANGE', 'PERNOD-RICD', 'PUBLICIS-GR', 'RENAULT', 'RWE', 'SAFRAN', 'SAINTGOBAIN', 'SANOFI', 'SAP', 'SCHNEIDELEC', 'SIEMENS', 'SOCIETE-GEN', 'SOLVAY', 'THYSSENKRUP', 'TOTAL', 'VALEO', 'VEOLIA-ENV', 'VINCI', 'VIVENDI', 'VOLKSWAGEN', 'XAGUSD', 'XAUUSD', 'ESTOX', 'FRENCH40', 'GERMAN30', 'UK100', 'US30', 'US500', 'USNDX', '3M', '3i-GROUP', 'ADMIRAL', 'AIG', 'ALIBABA', 'AMAZON', 'AMEX', 'ANGLO-AMERI', 'ANTOFAGASTA', 'APPLE', 'ASHTEAD', 'ASTRAZENECA', 'AT&T', 'AVIVA', 'BABCOCK', 'BAE-SYSTEMS', 'BAIDU', 'BALFOUR-B', 'BARCLAYS', 'BARRAT', 'BATS', 'BHP-BILITON', 'BNK-AMER', 'BOEING', 'BP', 'BRIT-FOODS', 'BRIT-LND', 'BT', 'BUNZL', 'BURBERRY', 'CAPITA', 'CARNIVAL', 'CAT', 'CENTRICA', 'CHEVRON', 'CISCO', 'CITI', 'COMPASS', 'CRH', 'DIAGEO', 'DIRECT-LINE', 'DISNEY', 'DRAX', 'EASYJET', 'EBAY', 'EXPERIAN', 'EXXON', 'FACEBOOK', 'FEDEX', 'FERRARI', 'FORD', 'GE', 'GLAXO', 'GLENCORE', 'GM', 'GOLDMANS', 'HALLIBURTON', 'HAMMERSON', 'HOME-DEP', 'HP', 'HSBC', 'IAG', 'IBM', 'IG-GROUP', 'IHG', 'IMI', 'IMP-TOBACCO', 'INCHCAPE', 'INTEL', 'INTERTEK', 'ITV', 'JOHNSON', 'JOHNSON-MAT', 'JPMORGAN', 'KINGFISHER', 'LAND-SEC', 'LEGAL-GEN', 'LLOYDS', 'LSE', 'M&S', 'MAN-GROUP', 'MATCH', 'MERCK', 'META', 'MICROSOFT', 'MONDI', 'MORGAN-S', 'MSTRCARD', 'McD', 'NAT-GRID', 'NETFLIX', 'NEXT', 'NIKE', 'OCADO', 'ORACLE', 'P&G', 'PAYPAL', 'PEARSON', 'PENNON', 'PEPSI', 'PERSIMMON', 'PETROFAC', 'PFIZER', 'PHIL-MOR', 'PRUDENTIAL', 'REED-ELSVR', 'RENTOKIL', 'RIGHTMOVE', 'RIO-TINTO', 'ROLLS-ROYCE', 'SAGE', 'SAINSBURY', 'SCHLUMBERGR', 'SEVERN-TRNT', 'SMITH-NEPH', 'SMITHS', 'SQUARE-INC', 'SSE', 'ST-JAMES', 'STAN-CHARTD', 'STARBUX', 'TAYLOR-WIMP', 'TESCO', 'TESLA', 'THOMAS-COOK', 'TRAVELRS', 'TRAVIS-PERK', 'TUI', 'TULLOW', 'UNILEVER', 'UNITED-UTIL', 'UTD-HLTH', 'VERIZON', 'VISA', 'VODAFONE', 'WALMART', 'WEIR-GROUP', 'WELLS-FG', 'WHITBREAD', 'WPP')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.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: 2023-03-01 11:37:45 Duration: 2m34s Database: acaweb_fx User: postgres Remote: 192.168.1.145 Application: PostgreSQL JDBC Driver Bind query: yes
-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = '479' 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 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 (kr.simulation = 0 OR kr.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 ('263' = 0 OR coalesce(bim.code, s.symbol) in ('AUDCAD', 'AUDCHF', 'AUDJPY', 'AUDNZD', 'AUDUSD', 'CADCHF', 'CADJPY', 'CHFJPY', 'CHFNOK', 'EURAUD', 'EURCAD', 'EURCHF', 'EURCZK', 'EURGBP', 'EURHUF', 'EURJPY', 'EURNOK', 'EURNZD', 'EURPLN', 'EURSEK', 'EURTRY', 'EURUSD', 'GBPAUD', 'GBPCAD', 'GBPCHF', 'GBPJPY', 'GBPNZD', 'GBPSEK', 'GBPUSD', 'HKDJPY', 'NOKSEK', 'NZDCAD', 'NZDCHF', 'NZDJPY', 'NZDUSD', 'PnL', 'SGDJPY', 'TRYJPY', 'USDCAD', 'USDCHF', 'USDCNH', 'USDCZK', 'USDHKD', 'USDHUF', 'USDJPY', 'USDMXN', 'USDNOK', 'USDPLN', 'USDSEK', 'USDSGD', 'USDTRY', 'USDZAR', 'ZARJPY', 'ACCOR', 'ADIDAS', 'AIR-LIQUIDE', 'AIRBUS-GRP', 'ALLIANZ', 'ALSTOM', 'ARCELORMITL', 'AXA', 'BASF', 'BAYER', 'BEIERSDORF', 'BMW', 'BNP-PARIBAS', 'BOUYGUES', 'CAP-GEMINI', 'CARREFOUR', 'CONTINENTAL', 'CREDIT-AGRI', 'DANONE', 'DEUT-BOERSE', 'DEUT-TELEKM', 'DEUTSCHE-BK', 'DEUTSCHPOST', 'E.ON', 'EDF', 'ENGIE', 'FRESENI-MED', 'FRESENIUS', 'HEIDBGCEMNT', 'HENKEL', 'INFINEONTEC', 'KERING', 'LANXESS', 'LEGRAND', 'LINDE', 'LOREAL', 'LUFTHANSA', 'LVMH', 'MERCK-KGAA', 'MICHELIN', 'MUNICH-RE', 'ORANGE', 'PERNOD-RICD', 'PUBLICIS-GR', 'RENAULT', 'RWE', 'SAFRAN', 'SAINTGOBAIN', 'SANOFI', 'SAP', 'SCHNEIDELEC', 'SIEMENS', 'SOCIETE-GEN', 'SOLVAY', 'THYSSENKRUP', 'TOTAL', 'VALEO', 'VEOLIA-ENV', 'VINCI', 'VIVENDI', 'VOLKSWAGEN', 'XAGUSD', 'XAUUSD', 'ESTOX', 'FRENCH40', 'GERMAN30', 'UK100', 'US30', 'US500', 'USNDX', '3M', '3i-GROUP', 'ADMIRAL', 'AIG', 'ALIBABA', 'AMAZON', 'AMEX', 'ANGLO-AMERI', 'ANTOFAGASTA', 'APPLE', 'ASHTEAD', 'ASTRAZENECA', 'AT&T', 'AVIVA', 'BABCOCK', 'BAE-SYSTEMS', 'BAIDU', 'BALFOUR-B', 'BARCLAYS', 'BARRAT', 'BATS', 'BHP-BILITON', 'BNK-AMER', 'BOEING', 'BP', 'BRIT-FOODS', 'BRIT-LND', 'BT', 'BUNZL', 'BURBERRY', 'CAPITA', 'CARNIVAL', 'CAT', 'CENTRICA', 'CHEVRON', 'CISCO', 'CITI', 'COMPASS', 'CRH', 'DIAGEO', 'DIRECT-LINE', 'DISNEY', 'DRAX', 'EASYJET', 'EBAY', 'EXPERIAN', 'EXXON', 'FACEBOOK', 'FEDEX', 'FERRARI', 'FORD', 'GE', 'GLAXO', 'GLENCORE', 'GM', 'GOLDMANS', 'HALLIBURTON', 'HAMMERSON', 'HOME-DEP', 'HP', 'HSBC', 'IAG', 'IBM', 'IG-GROUP', 'IHG', 'IMI', 'IMP-TOBACCO', 'INCHCAPE', 'INTEL', 'INTERTEK', 'ITV', 'JOHNSON', 'JOHNSON-MAT', 'JPMORGAN', 'KINGFISHER', 'LAND-SEC', 'LEGAL-GEN', 'LLOYDS', 'LSE', 'M&S', 'MAN-GROUP', 'MATCH', 'MERCK', 'META', 'MICROSOFT', 'MONDI', 'MORGAN-S', 'MSTRCARD', 'McD', 'NAT-GRID', 'NETFLIX', 'NEXT', 'NIKE', 'OCADO', 'ORACLE', 'P&G', 'PAYPAL', 'PEARSON', 'PENNON', 'PEPSI', 'PERSIMMON', 'PETROFAC', 'PFIZER', 'PHIL-MOR', 'PRUDENTIAL', 'REED-ELSVR', 'RENTOKIL', 'RIGHTMOVE', 'RIO-TINTO', 'ROLLS-ROYCE', 'SAGE', 'SAINSBURY', 'SCHLUMBERGR', 'SEVERN-TRNT', 'SMITH-NEPH', 'SMITHS', 'SQUARE-INC', 'SSE', 'ST-JAMES', 'STAN-CHARTD', 'STARBUX', 'TAYLOR-WIMP', 'TESCO', 'TESLA', 'THOMAS-COOK', 'TRAVELRS', 'TRAVIS-PERK', 'TUI', 'TULLOW', 'UNILEVER', 'UNITED-UTIL', 'UTD-HLTH', 'VERIZON', 'VISA', 'VODAFONE', 'WALMART', 'WEIR-GROUP', 'WELLS-FG', 'WHITBREAD', 'WPP')) AND ('0' = 0 OR p.patternname in ('')) AND ('2' = 0 OR kr.patternclassid in ('1', '2')) AND ('400' = 0 OR kr.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: 2023-03-01 11:53:23 Duration: 2m5s Database: acaweb_fx User: postgres Remote: 192.168.1.20 Application: PostgreSQL JDBC Driver Bind query: yes
13 566ms 25s223ms 8s489ms 106 14m59s select * from ( select pricedatetime, open, high, low, close, volume, bsf from t240 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Mar 01 11 106 14m59s 8s489ms [ User: postgres - Total duration: 14m59s - Times executed: 106 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 14m59s - Times executed: 106 ]
-
SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T240 WHERE symbolid = '515840243246556300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:11:57 Duration: 25s223ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T240 WHERE symbolid = '515840243238979300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:11:55 Duration: 21s656ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T240 WHERE symbolid = '515840248269940300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:09:41 Duration: 18s186ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
14 5ms 24s191ms 6s527ms 192 20m53s select * from ( select pricedatetime, open, high, low, close, volume, bsf from t30 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Mar 01 11 192 20m53s 6s527ms [ User: postgres - Total duration: 20m53s - Times executed: 192 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 20m53s - Times executed: 192 ]
-
SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T30 WHERE symbolid = '515840217506801300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:33:08 Duration: 24s191ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T30 WHERE symbolid = '515840243187254300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:23:47 Duration: 23s260ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
-
SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T30 WHERE symbolid = '515840243268503300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:15:53 Duration: 19s771ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
15 2ms 1m21s 3s559ms 234 13m52s select distinct patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, longname, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_autochartist_results order by resultuid desc limit ?) then ? else ? end as relevant from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join autochartist_results a on a.symbolid = s.symbolid inner join patterns p on a.pattern = p.patternname left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and (((s.symbol ilike ? and timegranularity = ?))) and breakout >= ?.? and patternendtime = latestbaratbreakouttime and patternlengthbars >= ? and patternquality >= ?.? and initialtrend >= ?.? and symmetry >= ?.? and noise <= ?.? and volumeincrease >= ?.? and temporarypattern = ? and patternid & ? > ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and a.resultuid > ? and s.nonliquid = ? and dftt.dayofweek = ? order by relevant desc, age asc, patternendtime desc, patternquality desc limit ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Mar 01 11 234 13m52s 3s559ms [ User: postgres - Total duration: 13m52s - Times executed: 234 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 13m52s - Times executed: 234 ]
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 538 AND (((s.symbol ilike '%usdzar%' AND timegranularity = 1440))) AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 601334092758412301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:54:46 Duration: 1m21s Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 538 AND (((s.symbol ilike '%usdzar%' AND timegranularity = 1440))) AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 601334092758412301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:20:56 Duration: 1m14s Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 538 AND (((s.symbol ilike '%gbpusd%' AND timegranularity = 240))) AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 601477691791436301 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50;
Date: 2023-03-01 11:28:53 Duration: 57s485ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
16 0ms 1m7s 2s691ms 4,685 3h30m11s select distinct a.resultuid as ruid, c.symbolid as sid, c.symbol as sym, c.longname as longname, c.shortname, c.exchange as e, c.timegranularity as tg, p.patternid as pid, a.direction as d, cast(atbaridentified as timestamp) as pet, cast(patternstarttime as timestamp) as pst, patternprice as patp, breakoutprice as pe, breakoutbars as be, errormargin as erm, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, cast(x0 as timestamp) as x0, cast(x1 as timestamp) as x1, cast(x2 as timestamp) as x2, cast(( case when x3 = ? then ? else x3 end) as timestamp) as x3, cast(( case when x4 = ? then ? else x4 end) as timestamp) as x4, cast(( case when x5 = ? then ? else x5 end) as timestamp) as x5, cast(( case when x6 = ? then ? else x6 end) as timestamp) as x6, cast(( case when x7 = ? then ? else x7 end) as timestamp) as x7, cast(( case when x8 = ? then ? else x8 end) as timestamp) as x8, cast(( case when x9 = ? then ? else x9 end) as timestamp) as x9, cast(atbaridentified as timestamp) as patternendtime, cast(atbaridentified as timestamp) as atbar, cast(( case when approachingtimestamp = ? then ? else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzos, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as relevant, cast(?.? as double precision) as premium, cast(? as bigint) as instrumentid, ? as derivativeid, ? as underlyingid, ? as isunderlying from symbols c inner join brokersymbollist b on c.symbolid = b.symbolid inner join symbolgroup sg on c.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = c.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join keylevels_results a on a.symbolid = c.symbolid inner join hrspatterns p on a.patternid = p.patternid left outer join relevance_keylevels_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and patternclassid = ? and patternlengthbars >= ? and a.patternid & ? > ? and dftt.dayofweek = ? and a.qtytp >= ? and a.resultuid > ? and c.nonliquid = ? and c.deleted = ? and dss.enabled = ? order by relevant desc, age asc, patternendtime desc, qtp desc limit ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 01 11 4,685 3h30m11s 2s691ms [ User: postgres - Total duration: 3h30m11s - Times executed: 4685 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3h30m11s - Times executed: 4685 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 622 AND sg.groupid = 515852059853768308 AND patternclassid = '1' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '1653660799' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:17:01 Duration: 1m7s Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 621 AND sg.groupid = 515852059852088308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '-936617313' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:11:42 Duration: 1m1s Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 622 AND sg.groupid = 515852059853768308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '39' > 0 AND dftt.dayofweek = '3' AND a.qtytp >= '0' AND a.resultuid > '1329650799' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:12:08 Duration: 1m Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
17 3ms 21s240ms 2s543ms 248 10m30s select * from ( select pricedatetime, open, high, low, close, volume, bsf from t60 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Mar 01 11 248 10m30s 2s543ms [ User: postgres - Total duration: 10m30s - Times executed: 248 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 10m30s - Times executed: 248 ]
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T60 WHERE symbolid = '515840243902252300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:16:48 Duration: 21s240ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T60 WHERE symbolid = '515840243214354300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:16:27 Duration: 16s567ms Database: acaweb_fx User: postgres Remote: 192.168.1.201 Application: PostgreSQL JDBC Driver Bind query: yes
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T60 WHERE symbolid = '515840248632535300' AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2023-03-01 11:10:41 Duration: 14s971ms Database: acaweb_fx User: postgres Remote: 192.168.1.23 Application: PostgreSQL JDBC Driver Bind query: yes
18 0ms 44s281ms 910ms 2,225 33m46s select distinct a.resultuid as ruid, c.symbolid as sid, c.symbol as sym, c.longname as longname, c.shortname, c.exchange as e, c.timegranularity as tg, p.patternid as pid, a.direction as d, cast(atbaridentified as timestamp) as pet, cast(patternstarttime as timestamp) as pst, patternprice as patp, breakoutprice as pe, breakoutbars as be, errormargin as erm, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, cast(x0 as timestamp) as x0, cast(x1 as timestamp) as x1, cast(x2 as timestamp) as x2, cast(( case when x3 = ? then ? else x3 end) as timestamp) as x3, cast(( case when x4 = ? then ? else x4 end) as timestamp) as x4, cast(( case when x5 = ? then ? else x5 end) as timestamp) as x5, cast(( case when x6 = ? then ? else x6 end) as timestamp) as x6, cast(( case when x7 = ? then ? else x7 end) as timestamp) as x7, cast(( case when x8 = ? then ? else x8 end) as timestamp) as x8, cast(( case when x9 = ? then ? else x9 end) as timestamp) as x9, cast(atbaridentified as timestamp) as patternendtime, cast(atbaridentified as timestamp) as atbar, cast(( case when approachingtimestamp = ? then ? else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzos, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) then ? else ? end as relevant, cast(?.? as double precision) as premium, cast(? as bigint) as instrumentid, ? as derivativeid, ? as underlyingid, ? as isunderlying from symbols c inner join brokersymbollist b on c.symbolid = b.symbolid inner join symbolgroup sg on c.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = c.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join keylevels_results a on a.symbolid = c.symbolid inner join hrspatterns p on a.patternid = p.patternid left outer join relevance_keylevels_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and patternclassid = ? and patternlengthbars >= ? and a.patternid & ? > ? and dftt.dayofweek = ? and a.resultuid > ? and c.nonliquid = ? and c.deleted = ? and dss.enabled = ? order by relevant desc, age asc, patternendtime desc, qtp desc limit ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Mar 01 11 2,225 33m46s 910ms [ User: postgres - Total duration: 33m46s - Times executed: 2225 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 33m46s - Times executed: 2225 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 538 AND sg.groupid = 515852059729069308 AND patternclassid = '1' AND patternlengthbars >= '20' AND a.PatternID & '3' > 0 AND dftt.dayofweek = '3' AND a.resultuid > '-1227948089' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:35:45 Duration: 44s281ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 538 AND sg.groupid = 515852059729069308 AND patternclassid = '2' AND patternlengthbars >= '20' AND a.PatternID & '3' > 0 AND dftt.dayofweek = '3' AND a.resultuid > '776704799' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:35:45 Duration: 43s938ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 667 AND sg.groupid = 500996399199151208 AND patternclassid = '1' AND patternlengthbars >= '20' AND a.PatternID & '3' > 0 AND dftt.dayofweek = '3' AND a.resultuid > '-1792441497' AND c.nonliquid = '0' AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:35:00 Duration: 41s335ms Database: acaweb_fx User: postgres Remote: 192.168.0.239 Application: PostgreSQL JDBC Driver Bind query: yes
19 0ms 1s916ms 126ms 4,809 10m10s insert into keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errormargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestprice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) values (?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?, ?, ?.?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?.?, ?::timestamp without time zone, ?, ?.?, ?.?, ?, ?, ?.?, ?.?, ?::timestamp without time zone, ?, ?, ?.?, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Mar 01 11 4,809 10m10s 126ms [ User: postgres - Total duration: 10m10s - Times executed: 4809 ]
[ Application: [unknown] - Total duration: 10m10s - Times executed: 4809 ]
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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, 2, '2023-03-01 09:27:40'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 81, 19.960000000000000850000000000000, '2023-02-28 10:00:00', '2023-02-22 08:00:00', '2023-02-22 07:30:00', '', '', '', '', '', '', '', 162, 19.919000000000000480000000000000, '2023-03-01 04:00:00'::timestamp without time zone, '2023-03-01 04:00:00', 0.000000000000000000000000000000, 0.041000000000000015600000000000, 1, 515840221503096300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840221503096300|19.96|2|2023-03-01 04:00:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2023-02-22 07:30:00', 19.629999999999999000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:30:29 Duration: 1s916ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
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INSERT INTO keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errorMargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestPrice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) VALUES (5.000000000000000000000000000000, - 1, 2, '2023-03-01 09:27:40'::timestamp without time zone, '', 0.500000000000000000000000000000, 3, 81, 19.960000000000000850000000000000, '2023-02-28 10:00:00', '2023-02-22 08:00:00', '2023-02-22 07:30:00', '', '', '', '', '', '', '', 162, 19.919000000000000480000000000000, '2023-03-01 04:00:00'::timestamp without time zone, '2023-03-01 04:00:00', 0.000000000000000000000000000000, 0.041000000000000015600000000000, 1, 515840221503096300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840221503096300|19.96|2|2023-03-01 04:00:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2023-02-22 07:30:00', 19.629999999999999000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:30:29 Duration: 1s912ms 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 (4.000000000000000000000000000000, - 1, 2, '2023-03-01 09:12:34'::timestamp without time zone, '', 0.500000000000000000000000000000, 4, 68, 7239.300000000000182000000000000000, '2023-03-01 09:30:00', '2023-02-28 00:30:00', '2023-02-27 18:00:00', '2023-02-27 17:30:00', '', '', '', '', '', '', 170, 7236.239999999999782000000000000000, '2023-03-01 10:30:00'::timestamp without time zone, '2023-03-01 10:30:00', 0.000000000000000000000000000000, 3.059999999999991172000000000000, 1, 515840248015340300, 0.000000000000000000000000000000, 0.000000000000000000000000000000, '1900-01-01 00:00:00'::timestamp without time zone, 0, '|515840248015340300|7239.3|2|2023-03-01 10:30:00|1|-1', 0.000000000000000000000000000000, 0.000000000000000000000000000000, 3, '2023-02-27 17:30:00', 7206.300000000000182000000000000000, 0, CURRENT_TIMESTAMP::timestamp without time zone) ON CONFLICT DO NOTHING;
Date: 2023-03-01 11:15:22 Duration: 1s607ms Database: acaweb_fx User: postgres Remote: 127.0.0.1 Application: [unknown]
20 0ms 16s89ms 89ms 3,231 4m48s select distinct a.resultuid as ruid, s.symbolid as sid, symbol as sym, longname, shortname, exchange as e, timegranularity as tg, p.patternid as pid, direction as d, patternstarttime as pst, patternendtime as pet, patternstartprice as psp, patternendprice as pep, pricex as px, timex as tx, pricea as pa, timea as ta, priceb as pb, timeb as tb, pricec as pc, timec as tc, priced as pd, timed as td, averagequality as aq, timequality as tq, errormargin as rq, (? - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, patternlengthbars as l, temporarypattern as tp, bandwidth as bw, qtytp as qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzos, dftt.timezone as tz, case when rar.age is not null then rar.age when a.resultuid <= ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ?) then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= ( select resultuid from relevance_fibonacci_results order by resultuid desc limit ?) then ? else ? end as relevant from symbols s inner join brokersymbollist b on s.symbolid = b.symbolid inner join symbolgroup sg on s.symbolid = sg.symbolid inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dftt on dftt.classname = dss.classname inner join fibonacci_results a on a.symbolid = s.symbolid inner join fibonaccipatterns p on a.pattern = p.patternname left outer join relevance_fibonacci_results rar on rar.resultuid = a.resultuid where b.brokerid = ? and sg.groupid = ? and patternlengthbars >= ? and averagequality >= ?.? and (timequality >= ?.? or timequality = ?) and errormargin >= ?.? and ? - noise >= ?.? and s.nonliquid = ? and patternid & ? > ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and patternendprice > ? and a.resultuid > ? and dftt.dayofweek = ? order by relevant desc, age asc, patternendtime desc, averagequality desc limit ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Mar 01 11 3,231 4m48s 89ms [ User: postgres - Total duration: 4m48s - Times executed: 3231 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 4m48s - Times executed: 3231 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 622 AND sg.groupid = 515852059853768308 AND patternlengthbars >= 20 AND averagequality >= 0.3 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice > - 1 AND a.resultuid > 601555599750214302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2023-03-01 11:16:38 Duration: 16s89ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 692 AND sg.groupid = 515852059916698308 AND patternlengthbars >= 20 AND averagequality >= 0.0 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice > - 1 AND a.resultuid > 601555656822457302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2023-03-01 11:56:54 Duration: 9s419ms Database: acaweb_fx User: postgres Remote: 192.168.1.45 Application: PostgreSQL JDBC Driver Bind query: yes
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN symbolgroup sg ON s.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 622 AND sg.groupid = 515852059853768308 AND patternlengthbars >= 20 AND averagequality >= 0.3 AND (timequality >= 0.0 OR timequality = - 1) AND errormargin >= 0.0 AND 1 - noise >= 0.0 AND s.nonliquid = 0 AND PatternID & 39 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND PatternEndPrice > - 1 AND a.resultuid > 601555599750214302 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, averagequality DESC LIMIT 50;
Date: 2023-03-01 11:12:21 Duration: 9s182ms Database: acaweb_fx User: postgres Remote: 192.168.0.42 Application: PostgreSQL JDBC Driver Bind query: yes
Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 2s159ms 2,105 0ms 68ms 1ms WITH rar_max as ( ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Mar 01 11 2,105 2s159ms 1ms [ User: postgres - Total duration: 2h22m26s - Times executed: 2105 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2h22m26s - Times executed: 2105 ]
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WITH rar_max as ( ;
Date: 2023-03-01 11:28:18 Duration: 68ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
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WITH rar_max as ( ;
Date: 2023-03-01 11:41:22 Duration: 58ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
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WITH rar_max as ( ;
Date: 2023-03-01 11:29:51 Duration: 27ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
2 1s703ms 10,308 0ms 10ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 11 10,308 1s703ms 0ms [ User: postgres - Total duration: 100ms - Times executed: 10308 ]
[ Application: [unknown] - Total duration: 100ms - Times executed: 10308 ]
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SET extra_float_digits = 3;
Date: 2023-03-01 11:28:23 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42
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SET extra_float_digits = 3;
Date: 2023-03-01 11:33:30 Duration: 10ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201
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SET extra_float_digits = 3;
Date: 2023-03-01 11:00:27 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
3 1s668ms 22,143 0ms 17ms 0ms select 1;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 11 22,143 1s668ms 0ms [ User: postgres - Total duration: 151ms - Times executed: 22143 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 151ms - Times executed: 22143 ]
-
select 1;
Date: 2023-03-01 11:00:54 Duration: 17ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
-
select 1;
Date: 2023-03-01 11:00:27 Duration: 9ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
-
select 1;
Date: 2023-03-01 11:42:37 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201
4 1s157ms 3,926 0ms 126ms 0ms SELECT ;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 11 3,926 1s157ms 0ms [ User: postgres - Total duration: 19m1s - Times executed: 3926 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 18m55s - Times executed: 2496 ]
[ Application: [unknown] - Total duration: 6s239ms - Times executed: 1430 ]
-
SELECT ;
Date: 2023-03-01 11:57:02 Duration: 126ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT ;
Date: 2023-03-01 11:55:00 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
SELECT ;
Date: 2023-03-01 11:37:21 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
5 1s100ms 737 0ms 3ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 11 737 1s100ms 1ms [ User: postgres - Total duration: 17s318ms - Times executed: 737 ]
[ Application: [unknown] - Total duration: 17s318ms - Times executed: 737 ]
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2023-03-01 11:30:18 Duration: 3ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2023-03-01 11:49:32 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2023-03-01 11:15:31 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
6 862ms 1,839 0ms 7ms 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 prepare #6
Day Hour Count Duration Avg duration 11 1,839 862ms 0ms [ User: postgres - Total duration: 252ms - Times executed: 1839 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 252ms - Times executed: 1839 ]
-
/*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: 2023-03-01 11:03:17 Duration: 7ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
-
/*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: 2023-03-01 11:49:28 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
-
/*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: 2023-03-01 11:59:19 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201
7 558ms 5,925 0ms 1ms 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 #7
Day Hour Count Duration Avg duration 11 5,925 558ms 0ms [ User: postgres - Total duration: 2m35s - Times executed: 5925 ]
[ Application: [unknown] - Total duration: 2m35s - Times executed: 5925 ]
-
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: 2023-03-01 11:04:33 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2023-03-01 11:04:50 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2023-03-01 11:04:24 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
8 546ms 18 2ms 170ms 30ms 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 #8
Day Hour Count Duration Avg duration 11 18 546ms 30ms [ User: postgres - Total duration: 44ms - Times executed: 18 ]
[ Application: [unknown] - Total duration: 44ms - Times executed: 18 ]
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2023-03-01 11:10:03 Duration: 170ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2023-03-01 11:00:04 Duration: 151ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2023-03-01 11:30:03 Duration: 102ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.2.126
9 540ms 695 0ms 2ms 0ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 11 695 540ms 0ms [ User: postgres - Total duration: 36s607ms - Times executed: 695 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 36s607ms - Times executed: 695 ]
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2023-03-01 11:35:04 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2023-03-01 11:05:01 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2023-03-01 11:45:41 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250
10 535ms 1,341 0ms 1ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 11 1,341 535ms 0ms [ User: postgres - Total duration: 1m8s - Times executed: 1341 ]
[ Application: [unknown] - Total duration: 1m8s - Times executed: 1341 ]
-
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: 2023-03-01 11:49:42 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2023-03-01 11:01:27 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2023-03-01 11:15:41 Duration: 1ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
11 492ms 353 0ms 15ms 1ms /*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%xauusd%' AND timegranularity <= 1440);Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 11 353 492ms 1ms [ User: postgres - Total duration: 2s23ms - Times executed: 353 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s23ms - Times executed: 353 ]
-
/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:00:27 Duration: 15ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
-
/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:00:27 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
-
/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:07:36 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
12 461ms 41 1ms 150ms 11ms with wh_patitioned as ( select row_number() over (partition by symbol, a.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset as timezoneoffset, ar.patternlengthbars as length, ar.patternquality as quality FROM whatshot_probability whp INNER JOIN autochartist_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_autochartist_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $1 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $2 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $3) AND interval >= 60 AND percent >= 60 AND type = 'cp' and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a ), wh_patitioned2 as ( select row_number() over (partition by symbol, a2.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $4 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $5 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $6) AND interval >= 60 AND percent >= 60 AND type = 'kl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a2 ), wh_patitioned3 as ( select row_number() over (partition by symbol, a3.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, patternprice as predictionpricefrom, patternprice as predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $7 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $8 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $9) AND interval >= 60 AND percent >= 60 AND type = 'ekl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a3 ) select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, timezoneoffset, length, quality from wh_patitioned where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned2 where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned3 where rn = 1;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 11 41 461ms 11ms [ User: postgres - Total duration: 12s346ms - Times executed: 41 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12s346ms - Times executed: 41 ]
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with wh_patitioned as ( select row_number() over (partition by symbol, a.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset as timezoneoffset, ar.patternlengthbars as length, ar.patternquality as quality FROM whatshot_probability whp INNER JOIN autochartist_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_autochartist_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $1 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $2 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $3) AND interval >= 60 AND percent >= 60 AND type = 'cp' and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a ), wh_patitioned2 as ( select row_number() over (partition by symbol, a2.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $4 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $5 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $6) AND interval >= 60 AND percent >= 60 AND type = 'kl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a2 ), wh_patitioned3 as ( select row_number() over (partition by symbol, a3.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, patternprice as predictionpricefrom, patternprice as predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $7 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $8 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $9) AND interval >= 60 AND percent >= 60 AND type = 'ekl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a3 ) select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, timezoneoffset, length, quality from wh_patitioned where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned2 where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned3 where rn = 1;
Date: 2023-03-01 11:54:33 Duration: 150ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42
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with wh_patitioned as ( select row_number() over (partition by symbol, a.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset as timezoneoffset, ar.patternlengthbars as length, ar.patternquality as quality FROM whatshot_probability whp INNER JOIN autochartist_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_autochartist_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $1 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $2 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $3) AND interval >= 60 AND percent >= 60 AND type = 'cp' and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a ), wh_patitioned2 as ( select row_number() over (partition by symbol, a2.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $4 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $5 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $6) AND interval >= 60 AND percent >= 60 AND type = 'kl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a2 ), wh_patitioned3 as ( select row_number() over (partition by symbol, a3.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, patternprice as predictionpricefrom, patternprice as predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $7 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $8 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $9) AND interval >= 60 AND percent >= 60 AND type = 'ekl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a3 ) select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, timezoneoffset, length, quality from wh_patitioned where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned2 where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned3 where rn = 1;
Date: 2023-03-01 11:29:11 Duration: 126ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42
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with wh_patitioned as ( select row_number() over (partition by symbol, a.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset as timezoneoffset, ar.patternlengthbars as length, ar.patternquality as quality FROM whatshot_probability whp INNER JOIN autochartist_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_autochartist_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $1 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $2 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $3) AND interval >= 60 AND percent >= 60 AND type = 'cp' and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a ), wh_patitioned2 as ( select row_number() over (partition by symbol, a2.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $4 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $5 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $6) AND interval >= 60 AND percent >= 60 AND type = 'kl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a2 ), wh_patitioned3 as ( select row_number() over (partition by symbol, a3.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, patternprice as predictionpricefrom, patternprice as predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $7 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $8 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $9) AND interval >= 60 AND percent >= 60 AND type = 'ekl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a3 ) select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, timezoneoffset, length, quality from wh_patitioned where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned2 where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned3 where rn = 1;
Date: 2023-03-01 11:44:25 Duration: 59ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
13 433ms 1,317 0ms 2ms 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 prepare #13
Day Hour Count Duration Avg duration 11 1,317 433ms 0ms [ User: postgres - Total duration: 168ms - Times executed: 1317 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 168ms - Times executed: 1317 ]
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2023-03-01 11:17:09 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2023-03-01 11:24:25 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2023-03-01 11:45:33 Duration: 2ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
14 313ms 286 0ms 9ms 1ms /*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 11 286 313ms 1ms [ User: postgres - Total duration: 1s250ms - Times executed: 286 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s250ms - Times executed: 286 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:02:19 Duration: 9ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:49:05 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:15:32 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201
15 306ms 3,001 0ms 1ms 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 #15
Day Hour Count Duration Avg duration 11 3,001 306ms 0ms [ User: postgres - Total duration: 1m5s - Times executed: 3001 ]
[ Application: [unknown] - Total duration: 1m5s - Times executed: 3001 ]
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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: 2023-03-01 11:05:17 Duration: 1ms 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: 2023-03-01 11:15:35 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2023-03-01 11:04:33 Duration: 0ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.142
16 279ms 248 0ms 4ms 1ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((c.symbol ilike '%xauusd%' AND timegranularity <= 1440);Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 11 248 279ms 1ms [ User: postgres - Total duration: 9s676ms - Times executed: 248 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 9s676ms - Times executed: 248 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((c.symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:08:27 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((c.symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:12:27 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((c.symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:08:27 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
17 276ms 59 0ms 66ms 4ms SELECT (cast(substring(tz.gmoffset from 1 for 3) as float) * 60 + cast(substring(tz.gmoffset from 5 for 2) as float)) / 60 as offset FROM timezones tz WHERE tz.timezone = $1;Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 11 59 276ms 4ms [ User: postgres - Total duration: 366ms - Times executed: 59 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 366ms - Times executed: 59 ]
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SELECT (cast(substring(tz.gmoffset from 1 for 3) as float) * 60 + cast(substring(tz.gmoffset from 5 for 2) as float)) / 60 as offset FROM timezones tz WHERE tz.timezone = $1;
Date: 2023-03-01 11:36:00 Duration: 66ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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SELECT (cast(substring(tz.gmoffset from 1 for 3) as float) * 60 + cast(substring(tz.gmoffset from 5 for 2) as float)) / 60 as offset FROM timezones tz WHERE tz.timezone = $1;
Date: 2023-03-01 11:36:00 Duration: 59ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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SELECT (cast(substring(tz.gmoffset from 1 for 3) as float) * 60 + cast(substring(tz.gmoffset from 5 for 2) as float)) / 60 as offset FROM timezones tz WHERE tz.timezone = $1;
Date: 2023-03-01 11:30:02 Duration: 48ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201
18 255ms 177 0ms 9ms 1ms /*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((s.symbol ilike '%xauusd%' AND timegranularity <= 1440);Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 11 177 255ms 1ms [ User: postgres - Total duration: 7s741ms - Times executed: 177 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 7s741ms - Times executed: 177 ]
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((s.symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:02:07 Duration: 9ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((s.symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:06:01 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((s.symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:42:25 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
19 255ms 178 0ms 5ms 1ms /*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 11 178 255ms 1ms [ User: postgres - Total duration: 1s460ms - Times executed: 178 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s460ms - Times executed: 178 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:12:25 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:25:32 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:02:01 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
20 239ms 16 4ms 119ms 14ms with sym_info as ( ;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 11 16 239ms 14ms [ User: postgres - Total duration: 3s247ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s247ms - Times executed: 16 ]
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with sym_info as ( ;
Date: 2023-03-01 11:06:37 Duration: 119ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
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with sym_info as ( ;
Date: 2023-03-01 11:51:36 Duration: 47ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
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with sym_info as ( ;
Date: 2023-03-01 11:36:40 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 16s178ms 2,877 0ms 188ms 5ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Mar 01 11 2,877 16s178ms 5ms [ User: postgres - Total duration: 3h46s - Times executed: 2877 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3h46s - Times executed: 2861 ]
[ Application: [unknown] - Total duration: 8ms - Times executed: 16 ]
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WITH rar_max as ( ;
Date: 2023-03-01 11:41:22 Duration: 188ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '479', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '263', $13 = 'AUDCAD', $14 = 'AUDCHF', $15 = 'AUDJPY', $16 = 'AUDNZD', $17 = 'AUDUSD', $18 = 'CADCHF', $19 = 'CADJPY', $20 = 'CHFJPY', $21 = 'CHFNOK', $22 = 'EURAUD', $23 = 'EURCAD', $24 = 'EURCHF', $25 = 'EURCZK', $26 = 'EURGBP', $27 = 'EURHUF', $28 = 'EURJPY', $29 = 'EURNOK', $30 = 'EURNZD', $31 = 'EURPLN', $32 = 'EURSEK', $33 = 'EURTRY', $34 = 'EURUSD', $35 = 'GBPAUD', $36 = 'GBPCAD', $37 = 'GBPCHF', $38 = 'GBPJPY', $39 = 'GBPNZD', $40 = 'GBPSEK', $41 = 'GBPUSD', $42 = 'HKDJPY', $43 = 'NOKSEK', $44 = 'NZDCAD', $45 = 'NZDCHF', $46 = 'NZDJPY', $47 = 'NZDUSD', $48 = 'PnL', $49 = 'SGDJPY', $50 = 'TRYJPY', $51 = 'USDCAD', $52 = 'USDCHF', $53 = 'USDCNH', $54 = 'USDCZK', $55 = 'USDHKD', $56 = 'USDHUF', $57 = 'USDJPY', $58 = 'USDMXN', $59 = 'USDNOK', $60 = 'USDPLN', $61 = 'USDSEK', $62 = 'USDSGD', $63 = 'USDTRY', $64 = 'USDZAR', $65 = 'ZARJPY', $66 = 'ACCOR', $67 = 'ADIDAS', $68 = 'AIR-LIQUIDE', $69 = 'AIRBUS-GRP', $70 = 'ALLIANZ', $71 = 'ALSTOM', $72 = 'ARCELORMITL', $73 = 'AXA', $74 = 'BASF', $75 = 'BAYER', $76 = 'BEIERSDORF', $77 = 'BMW', $78 = 'BNP-PARIBAS', $79 = 'BOUYGUES', $80 = 'CAP-GEMINI', $81 = 'CARREFOUR', $82 = 'CONTINENTAL', $83 = 'CREDIT-AGRI', $84 = 'DANONE', $85 = 'DEUT-BOERSE', $86 = 'DEUT-TELEKM', $87 = 'DEUTSCHE-BK', $88 = 'DEUTSCHPOST', $89 = 'E.ON', $90 = 'EDF', $91 = 'ENGIE', $92 = 'FRESENI-MED', $93 = 'FRESENIUS', $94 = 'HEIDBGCEMNT', $95 = 'HENKEL', $96 = 'INFINEONTEC', $97 = 'KERING', $98 = 'LANXESS', $99 = 'LEGRAND', $100 = 'LINDE', $101 = 'LOREAL', $102 = 'LUFTHANSA', $103 = 'LVMH', $104 = 'MERCK-KGAA', $105 = 'MICHELIN', $106 = 'MUNICH-RE', $107 = 'ORANGE', $108 = 'PERNOD-RICD', $109 = 'PUBLICIS-GR', $110 = 'RENAULT', $111 = 'RWE', $112 = 'SAFRAN', $113 = 'SAINTGOBAIN', $114 = 'SANOFI', $115 = 'SAP', $116 = 'SCHNEIDELEC', $117 = 'SIEMENS', $118 = 'SOCIETE-GEN', $119 = 'SOLVAY', $120 = 'THYSSENKRUP', $121 = 'TOTAL', $122 = 'VALEO', $123 = 'VEOLIA-ENV', $124 = 'VINCI', $125 = 'VIVENDI', $126 = 'VOLKSWAGEN', $127 = 'XAGUSD', $128 = 'XAUUSD', $129 = 'ESTOX', $130 = 'FRENCH40', $131 = 'GERMAN30', $132 = 'UK100', $133 = 'US30', $134 = 'US500', $135 = 'USNDX', $136 = '3M', $137 = '3i-GROUP', $138 = 'ADMIRAL', $139 = 'AIG', $140 = 'ALIBABA', $141 = 'AMAZON', $142 = 'AMEX', $143 = 'ANGLO-AMERI', $144 = 'ANTOFAGASTA', $145 = 'APPLE', $146 = 'ASHTEAD', $147 = 'ASTRAZENECA', $148 = 'AT&T', $149 = 'AVIVA', $150 = 'BABCOCK', $151 = 'BAE-SYSTEMS', $152 = 'BAIDU', $153 = 'BALFOUR-B', $154 = 'BARCLAYS', $155 = 'BARRAT', $156 = 'BATS', $157 = 'BHP-BILITON', $158 = 'BNK-AMER', $159 = 'BOEING', $160 = 'BP', $161 = 'BRIT-FOODS', $162 = 'BRIT-LND', $163 = 'BT', $164 = 'BUNZL', $165 = 'BURBERRY', $166 = 'CAPITA', $167 = 'CARNIVAL', $168 = 'CAT', $169 = 'CENTRICA', $170 = 'CHEVRON', $171 = 'CISCO', $172 = 'CITI', $173 = 'COMPASS', $174 = 'CRH', $175 = 'DIAGEO', $176 = 'DIRECT-LINE', $177 = 'DISNEY', $178 = 'DRAX', $179 = 'EASYJET', $180 = 'EBAY', $181 = 'EXPERIAN', $182 = 'EXXON', $183 = 'FACEBOOK', $184 = 'FEDEX', $185 = 'FERRARI', $186 = 'FORD', $187 = 'GE', $188 = 'GLAXO', $189 = 'GLENCORE', $190 = 'GM', $191 = 'GOLDMANS', $192 = 'HALLIBURTON', $193 = 'HAMMERSON', $194 = 'HOME-DEP', $195 = 'HP', $196 = 'HSBC', $197 = 'IAG', $198 = 'IBM', $199 = 'IG-GROUP', $200 = 'IHG', $201 = 'IMI', $202 = 'IMP-TOBACCO', $203 = 'INCHCAPE', $204 = 'INTEL', $205 = 'INTERTEK', $206 = 'ITV', $207 = 'JOHNSON', $208 = 'JOHNSON-MAT', $209 = 'JPMORGAN', $210 = 'KINGFISHER', $211 = 'LAND-SEC', $212 = 'LEGAL-GEN', $213 = 'LLOYDS', $214 = 'LSE', $215 = 'M&S', $216 = 'MAN-GROUP', $217 = 'MATCH', $218 = 'MERCK', $219 = 'META', $220 = 'MICROSOFT', $221 = 'MONDI', $222 = 'MORGAN-S', $223 = 'MSTRCARD', $224 = 'McD', $225 = 'NAT-GRID', $226 = 'NETFLIX', $227 = 'NEXT', $228 = 'NIKE', $229 = 'OCADO', $230 = 'ORACLE', $231 = 'P&G', $232 = 'PAYPAL', $233 = 'PEARSON', $234 = 'PENNON', $235 = 'PEPSI', $236 = 'PERSIMMON', $237 = 'PETROFAC', $238 = 'PFIZER', $239 = 'PHIL-MOR', $240 = 'PRUDENTIAL', $241 = 'REED-ELSVR', $242 = 'RENTOKIL', $243 = 'RIGHTMOVE', $244 = 'RIO-TINTO', $245 = 'ROLLS-ROYCE', $246 = 'SAGE', $247 = 'SAINSBURY', $248 = 'SCHLUMBERGR', $249 = 'SEVERN-TRNT', $250 = 'SMITH-NEPH', $251 = 'SMITHS', $252 = 'SQUARE-INC', $253 = 'SSE', $254 = 'ST-JAMES', $255 = 'STAN-CHARTD', $256 = 'STARBUX', $257 = 'TAYLOR-WIMP', $258 = 'TESCO', $259 = 'TESLA', $260 = 'THOMAS-COOK', $261 = 'TRAVELRS', $262 = 'TRAVIS-PERK', $263 = 'TUI', $264 = 'TULLOW', $265 = 'UNILEVER', $266 = 'UNITED-UTIL', $267 = 'UTD-HLTH', $268 = 'VERIZON', $269 = 'VISA', $270 = 'VODAFONE', $271 = 'WALMART', $272 = 'WEIR-GROUP', $273 = 'WELLS-FG', $274 = 'WHITBREAD', $275 = 'WPP', $276 = '400', $277 = '400', $278 = 't', $279 = '10', $280 = '10'
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WITH rar_max as ( ;
Date: 2023-03-01 11:30:46 Duration: 163ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = 't', $2 = '627', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '231', $14 = '#ADBE', $15 = '#AIRF', $16 = '#ALVG', $17 = '#AMZN', $18 = '#APPL', $19 = '#BA', $20 = '#BABA', $21 = '#BAYGn', $22 = '#BMWG', $23 = '#BNPP', $24 = '#BP', $25 = '#CAT', $26 = '#CBKG', $27 = '#DAIGn', $28 = '#DBKGn', $29 = '#DIS', $30 = '#EA', $31 = '#FB', $32 = '#FDX', $33 = '#GE', $34 = '#GM', $35 = '#GOOGL', $36 = '#GS', $37 = '#INTC', $38 = '#JPM', $39 = '#KO', $40 = '#META', $41 = '#MSFT', $42 = '#NFLX', $43 = '#RDSa', $44 = '#TSLA', $45 = '#VOWG', $46 = '#WMT', $47 = '#XOM', $48 = 'AUDCAD', $49 = 'AUDCHF', $50 = 'AUDJPY', $51 = 'AUDNZD', $52 = 'AUDUSD', $53 = 'AUS_200', $54 = 'BTCEUR', $55 = 'BTCGBP', $56 = 'BTCUSD', $57 = 'CADCHF', $58 = 'CADJPY', $59 = 'CHFJPY', $60 = 'CL_BRENT', $61 = 'DASHUSD', $62 = 'EOSUSD', $63 = 'ESP_35', $64 = 'ETHEUR', $65 = 'ETHGBP', $66 = 'ETHUSD', $67 = 'EURAUD', $68 = 'EURCAD', $69 = 'EURCHF', $70 = 'EURGBP', $71 = 'EURHUF', $72 = 'EURJPY', $73 = 'EURMXN', $74 = 'EURNOK', $75 = 'EURNZD', $76 = 'EURPLN', $77 = 'EURSEK', $78 = 'EURTRY', $79 = 'EURUSD', $80 = 'EUR_50', $81 = 'FRA_40', $82 = 'GBPAUD', $83 = 'GBPCAD', $84 = 'GBPCHF', $85 = 'GBPJPY', $86 = 'GBPNZD', $87 = 'GBPUSD', $88 = 'GBPZAR', $89 = 'GBR_100', $90 = 'GER_30', $91 = 'HKDJPY', $92 = 'HKG_50', $93 = 'IOTAUSD', $94 = 'LTCEUR', $95 = 'LTCUSD', $96 = 'NAS100', $97 = 'NEOUSD', $98 = 'NOKJPY', $99 = 'NOKSEK', $100 = 'NZDCAD', $101 = 'NZDCHF', $102 = 'NZDJPY', $103 = 'NZDUSD', $104 = 'OMGUSD', $105 = 'SPX500', $106 = 'TRXUSD', $107 = 'US30', $108 = 'USDCAD', $109 = 'USDCHF', $110 = 'USDCNH', $111 = 'USDCZK', $112 = 'USDDKK', $113 = 'USDHUF', $114 = 'USDJPY', $115 = 'USDMXN', $116 = 'USDNOK', $117 = 'USDPLN', $118 = 'USDSEK', $119 = 'USDSGD', $120 = 'USDZAR', $121 = 'USOIL', $122 = 'XAGUSD', $123 = 'XAUEUR', $124 = 'XAUUSD', $125 = 'XMRUSD', $126 = 'XPTUSD', $127 = 'XRPUSD', $128 = 'ZARJPY', $129 = 'ZECUSD', $130 = '#BP', $131 = 'AUDCAD', $132 = 'AUDCHF', $133 = 'AUDJPY', $134 = 'AUDNZD', $135 = 'AUDUSD', $136 = 'CADCHF', $137 = 'CADJPY', $138 = 'CHFJPY', $139 = 'EURAUD', $140 = 'EURCAD', $141 = 'EURCHF', $142 = 'EURGBP', $143 = 'EURHUF', $144 = 'EURJPY', $145 = 'EURMXN', $146 = 'EURNOK', $147 = 'EURNZD', $148 = 'EURPLN', $149 = 'EURSEK', $150 = 'EURTRY', $151 = 'EURUSD', $152 = 'GBPAUD', $153 = 'GBPCAD', $154 = 'GBPCHF', $155 = 'GBPJPY', $156 = 'GBPNZD', $157 = 'GBPUSD', $158 = 'GBPZAR', $159 = 'HKDJPY', $160 = 'NOKJPY', $161 = 'NOKSEK', $162 = 'NZDCAD', $163 = 'NZDCHF', $164 = 'NZDJPY', $165 = 'NZDUSD', $166 = 'USDCAD', $167 = 'USDCHF', $168 = 'USDCNH', $169 = 'USDCZK', $170 = 'USDDKK', $171 = 'USDHUF', $172 = 'USDJPY', $173 = 'USDMXN', $174 = 'USDNOK', $175 = 'USDPLN', $176 = 'USDSEK', $177 = 'USDSGD', $178 = 'USDZAR', $179 = 'ZARJPY', $180 = 'BTCEUR', $181 = 'BTCGBP', $182 = 'BTCUSD', $183 = 'DASHUSD', $184 = 'EOSUSD', $185 = 'ETHEUR', $186 = 'ETHGBP', $187 = 'ETHUSD', $188 = 'IOTAUSD', $189 = 'LTCEUR', $190 = 'LTCUSD', $191 = 'NEOUSD', $192 = 'OMGUSD', $193 = 'TRXUSD', $194 = 'XMRUSD', $195 = 'XRPUSD', $196 = 'ZECUSD', $197 = 'XAGUSD', $198 = 'XAUEUR', $199 = 'XAUUSD', $200 = 'XPTUSD', $201 = 'CL_BRENT', $202 = 'USOIL', $203 = '#AIRF', $204 = '#ALVG', $205 = '#BAYGn', $206 = '#BMWG', $207 = '#BNPP', $208 = '#CBKG', $209 = '#DAIGn', $210 = '#DBKGn', $211 = '#RDSa', $212 = '#VOWG', $213 = 'AUS_200', $214 = 'ESP_35', $215 = 'EUR_50', $216 = 'FRA_40', $217 = 'GBR_100', $218 = 'GER_30', $219 = 'HKG_50', $220 = 'NAS100', $221 = 'SPX500', $222 = 'US30', $223 = '#ADBE', $224 = '#AMZN', $225 = '#APPL', $226 = '#BA', $227 = '#BABA', $228 = '#CAT', $229 = '#DIS', $230 = '#EA', $231 = '#FB', $232 = '#FDX', $233 = '#GE', $234 = '#GM', $235 = '#GOOGL', $236 = '#GS', $237 = '#INTC', $238 = '#JPM', $239 = '#KO', $240 = '#MSFT', $241 = '#NFLX', $242 = '#TSLA', $243 = '#WMT', $244 = '#XOM', $245 = '0', $246 = '', $247 = '400', $248 = '400', $249 = '0', $250 = '0', $251 = '0', $252 = 't', $253 = '10', $254 = '10'
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WITH rar_max as ( ;
Date: 2023-03-01 11:34:47 Duration: 136ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = 't', $2 = '479', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '263', $14 = 'AUDCAD', $15 = 'AUDCHF', $16 = 'AUDJPY', $17 = 'AUDNZD', $18 = 'AUDUSD', $19 = 'CADCHF', $20 = 'CADJPY', $21 = 'CHFJPY', $22 = 'CHFNOK', $23 = 'EURAUD', $24 = 'EURCAD', $25 = 'EURCHF', $26 = 'EURCZK', $27 = 'EURGBP', $28 = 'EURHUF', $29 = 'EURJPY', $30 = 'EURNOK', $31 = 'EURNZD', $32 = 'EURPLN', $33 = 'EURSEK', $34 = 'EURTRY', $35 = 'EURUSD', $36 = 'GBPAUD', $37 = 'GBPCAD', $38 = 'GBPCHF', $39 = 'GBPJPY', $40 = 'GBPNZD', $41 = 'GBPSEK', $42 = 'GBPUSD', $43 = 'HKDJPY', $44 = 'NOKSEK', $45 = 'NZDCAD', $46 = 'NZDCHF', $47 = 'NZDJPY', $48 = 'NZDUSD', $49 = 'PnL', $50 = 'SGDJPY', $51 = 'TRYJPY', $52 = 'USDCAD', $53 = 'USDCHF', $54 = 'USDCNH', $55 = 'USDCZK', $56 = 'USDHKD', $57 = 'USDHUF', $58 = 'USDJPY', $59 = 'USDMXN', $60 = 'USDNOK', $61 = 'USDPLN', $62 = 'USDSEK', $63 = 'USDSGD', $64 = 'USDTRY', $65 = 'USDZAR', $66 = 'ZARJPY', $67 = 'ACCOR', $68 = 'ADIDAS', $69 = 'AIR-LIQUIDE', $70 = 'AIRBUS-GRP', $71 = 'ALLIANZ', $72 = 'ALSTOM', $73 = 'ARCELORMITL', $74 = 'AXA', $75 = 'BASF', $76 = 'BAYER', $77 = 'BEIERSDORF', $78 = 'BMW', $79 = 'BNP-PARIBAS', $80 = 'BOUYGUES', $81 = 'CAP-GEMINI', $82 = 'CARREFOUR', $83 = 'CONTINENTAL', $84 = 'CREDIT-AGRI', $85 = 'DANONE', $86 = 'DEUT-BOERSE', $87 = 'DEUT-TELEKM', $88 = 'DEUTSCHE-BK', $89 = 'DEUTSCHPOST', $90 = 'E.ON', $91 = 'EDF', $92 = 'ENGIE', $93 = 'FRESENI-MED', $94 = 'FRESENIUS', $95 = 'HEIDBGCEMNT', $96 = 'HENKEL', $97 = 'INFINEONTEC', $98 = 'KERING', $99 = 'LANXESS', $100 = 'LEGRAND', $101 = 'LINDE', $102 = 'LOREAL', $103 = 'LUFTHANSA', $104 = 'LVMH', $105 = 'MERCK-KGAA', $106 = 'MICHELIN', $107 = 'MUNICH-RE', $108 = 'ORANGE', $109 = 'PERNOD-RICD', $110 = 'PUBLICIS-GR', $111 = 'RENAULT', $112 = 'RWE', $113 = 'SAFRAN', $114 = 'SAINTGOBAIN', $115 = 'SANOFI', $116 = 'SAP', $117 = 'SCHNEIDELEC', $118 = 'SIEMENS', $119 = 'SOCIETE-GEN', $120 = 'SOLVAY', $121 = 'THYSSENKRUP', $122 = 'TOTAL', $123 = 'VALEO', $124 = 'VEOLIA-ENV', $125 = 'VINCI', $126 = 'VIVENDI', $127 = 'VOLKSWAGEN', $128 = 'XAGUSD', $129 = 'XAUUSD', $130 = 'ESTOX', $131 = 'FRENCH40', $132 = 'GERMAN30', $133 = 'UK100', $134 = 'US30', $135 = 'US500', $136 = 'USNDX', $137 = '3M', $138 = '3i-GROUP', $139 = 'ADMIRAL', $140 = 'AIG', $141 = 'ALIBABA', $142 = 'AMAZON', $143 = 'AMEX', $144 = 'ANGLO-AMERI', $145 = 'ANTOFAGASTA', $146 = 'APPLE', $147 = 'ASHTEAD', $148 = 'ASTRAZENECA', $149 = 'AT&T', $150 = 'AVIVA', $151 = 'BABCOCK', $152 = 'BAE-SYSTEMS', $153 = 'BAIDU', $154 = 'BALFOUR-B', $155 = 'BARCLAYS', $156 = 'BARRAT', $157 = 'BATS', $158 = 'BHP-BILITON', $159 = 'BNK-AMER', $160 = 'BOEING', $161 = 'BP', $162 = 'BRIT-FOODS', $163 = 'BRIT-LND', $164 = 'BT', $165 = 'BUNZL', $166 = 'BURBERRY', $167 = 'CAPITA', $168 = 'CARNIVAL', $169 = 'CAT', $170 = 'CENTRICA', $171 = 'CHEVRON', $172 = 'CISCO', $173 = 'CITI', $174 = 'COMPASS', $175 = 'CRH', $176 = 'DIAGEO', $177 = 'DIRECT-LINE', $178 = 'DISNEY', $179 = 'DRAX', $180 = 'EASYJET', $181 = 'EBAY', $182 = 'EXPERIAN', $183 = 'EXXON', $184 = 'FACEBOOK', $185 = 'FEDEX', $186 = 'FERRARI', $187 = 'FORD', $188 = 'GE', $189 = 'GLAXO', $190 = 'GLENCORE', $191 = 'GM', $192 = 'GOLDMANS', $193 = 'HALLIBURTON', $194 = 'HAMMERSON', $195 = 'HOME-DEP', $196 = 'HP', $197 = 'HSBC', $198 = 'IAG', $199 = 'IBM', $200 = 'IG-GROUP', $201 = 'IHG', $202 = 'IMI', $203 = 'IMP-TOBACCO', $204 = 'INCHCAPE', $205 = 'INTEL', $206 = 'INTERTEK', $207 = 'ITV', $208 = 'JOHNSON', $209 = 'JOHNSON-MAT', $210 = 'JPMORGAN', $211 = 'KINGFISHER', $212 = 'LAND-SEC', $213 = 'LEGAL-GEN', $214 = 'LLOYDS', $215 = 'LSE', $216 = 'M&S', $217 = 'MAN-GROUP', $218 = 'MATCH', $219 = 'MERCK', $220 = 'META', $221 = 'MICROSOFT', $222 = 'MONDI', $223 = 'MORGAN-S', $224 = 'MSTRCARD', $225 = 'McD', $226 = 'NAT-GRID', $227 = 'NETFLIX', $228 = 'NEXT', $229 = 'NIKE', $230 = 'OCADO', $231 = 'ORACLE', $232 = 'P&G', $233 = 'PAYPAL', $234 = 'PEARSON', $235 = 'PENNON', $236 = 'PEPSI', $237 = 'PERSIMMON', $238 = 'PETROFAC', $239 = 'PFIZER', $240 = 'PHIL-MOR', $241 = 'PRUDENTIAL', $242 = 'REED-ELSVR', $243 = 'RENTOKIL', $244 = 'RIGHTMOVE', $245 = 'RIO-TINTO', $246 = 'ROLLS-ROYCE', $247 = 'SAGE', $248 = 'SAINSBURY', $249 = 'SCHLUMBERGR', $250 = 'SEVERN-TRNT', $251 = 'SMITH-NEPH', $252 = 'SMITHS', $253 = 'SQUARE-INC', $254 = 'SSE', $255 = 'ST-JAMES', $256 = 'STAN-CHARTD', $257 = 'STARBUX', $258 = 'TAYLOR-WIMP', $259 = 'TESCO', $260 = 'TESLA', $261 = 'THOMAS-COOK', $262 = 'TRAVELRS', $263 = 'TRAVIS-PERK', $264 = 'TUI', $265 = 'TULLOW', $266 = 'UNILEVER', $267 = 'UNITED-UTIL', $268 = 'UTD-HLTH', $269 = 'VERIZON', $270 = 'VISA', $271 = 'VODAFONE', $272 = 'WALMART', $273 = 'WEIR-GROUP', $274 = 'WELLS-FG', $275 = 'WHITBREAD', $276 = 'WPP', $277 = '0', $278 = '', $279 = '0', $280 = '0', $281 = '0', $282 = '400', $283 = '400', $284 = 't', $285 = '10', $286 = '10'
2 5s326ms 7,316 0ms 562ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 11 7,316 5s326ms 0ms [ User: postgres - Total duration: 19m40s - Times executed: 7316 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 19m31s - Times executed: 5852 ]
[ Application: [unknown] - Total duration: 9s224ms - Times executed: 1464 ]
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SELECT ;
Date: 2023-03-01 11:45:05 Duration: 562ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '515840243037840300'
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SELECT ;
Date: 2023-03-01 11:21:22 Duration: 426ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '515840221159974300'
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SELECT ;
Date: 2023-03-01 11:15:05 Duration: 283ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '515840241636747300'
3 4s907ms 2,444 0ms 86ms 2ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 11 2,444 4s907ms 2ms [ User: postgres - Total duration: 1m3s - Times executed: 2444 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1m3s - Times executed: 2444 ]
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2023-03-01 11:41:00 Duration: 86ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '627', $2 = '627'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2023-03-01 11:07:35 Duration: 16ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '667', $2 = '667'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2023-03-01 11:29:21 Duration: 16ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.250 parameters: $1 = '660', $2 = '660'
4 4s33ms 63 0ms 440ms 64ms WITH last_candle AS ( ;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 11 63 4s33ms 64ms [ User: postgres - Total duration: 8m31s - Times executed: 63 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 8m31s - Times executed: 63 ]
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WITH last_candle AS ( ;
Date: 2023-03-01 11:12:00 Duration: 440ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.20 parameters: $1 = '529', $2 = '529'
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WITH last_candle AS ( ;
Date: 2023-03-01 11:12:00 Duration: 440ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529'
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WITH last_candle AS ( ;
Date: 2023-03-01 11:52:00 Duration: 389ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.145 parameters: $1 = '529', $2 = '529'
5 3s651ms 41 23ms 894ms 89ms with wh_patitioned as ( select row_number() over (partition by symbol, a.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset as timezoneoffset, ar.patternlengthbars as length, ar.patternquality as quality FROM whatshot_probability whp INNER JOIN autochartist_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_autochartist_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $1 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $2 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $3) AND interval >= 60 AND percent >= 60 AND type = 'cp' and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a ), wh_patitioned2 as ( select row_number() over (partition by symbol, a2.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $4 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $5 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $6) AND interval >= 60 AND percent >= 60 AND type = 'kl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a2 ), wh_patitioned3 as ( select row_number() over (partition by symbol, a3.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, patternprice as predictionpricefrom, patternprice as predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $7 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $8 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $9) AND interval >= 60 AND percent >= 60 AND type = 'ekl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a3 ) select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, timezoneoffset, length, quality from wh_patitioned where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned2 where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned3 where rn = 1;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 11 41 3s651ms 89ms [ User: postgres - Total duration: 12s346ms - Times executed: 41 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 12s346ms - Times executed: 41 ]
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with wh_patitioned as ( select row_number() over (partition by symbol, a.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset as timezoneoffset, ar.patternlengthbars as length, ar.patternquality as quality FROM whatshot_probability whp INNER JOIN autochartist_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_autochartist_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $1 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $2 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $3) AND interval >= 60 AND percent >= 60 AND type = 'cp' and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a ), wh_patitioned2 as ( select row_number() over (partition by symbol, a2.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $4 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $5 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $6) AND interval >= 60 AND percent >= 60 AND type = 'kl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a2 ), wh_patitioned3 as ( select row_number() over (partition by symbol, a3.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, patternprice as predictionpricefrom, patternprice as predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $7 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $8 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $9) AND interval >= 60 AND percent >= 60 AND type = 'ekl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a3 ) select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, timezoneoffset, length, quality from wh_patitioned where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned2 where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned3 where rn = 1;
Date: 2023-03-01 11:54:34 Duration: 894ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42 parameters: $1 = '125', $2 = '125', $3 = '125', $4 = '125', $5 = '125', $6 = '125', $7 = '125', $8 = '125', $9 = '125'
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with wh_patitioned as ( select row_number() over (partition by symbol, a.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset as timezoneoffset, ar.patternlengthbars as length, ar.patternquality as quality FROM whatshot_probability whp INNER JOIN autochartist_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_autochartist_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $1 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $2 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $3) AND interval >= 60 AND percent >= 60 AND type = 'cp' and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a ), wh_patitioned2 as ( select row_number() over (partition by symbol, a2.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $4 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $5 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $6) AND interval >= 60 AND percent >= 60 AND type = 'kl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a2 ), wh_patitioned3 as ( select row_number() over (partition by symbol, a3.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, patternprice as predictionpricefrom, patternprice as predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $7 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $8 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $9) AND interval >= 60 AND percent >= 60 AND type = 'ekl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a3 ) select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, timezoneoffset, length, quality from wh_patitioned where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned2 where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned3 where rn = 1;
Date: 2023-03-01 11:44:26 Duration: 679ms 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', $7 = '529', $8 = '529', $9 = '529'
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with wh_patitioned as ( select row_number() over (partition by symbol, a.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset as timezoneoffset, ar.patternlengthbars as length, ar.patternquality as quality FROM whatshot_probability whp INNER JOIN autochartist_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_autochartist_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $1 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $2 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $3) AND interval >= 60 AND percent >= 60 AND type = 'cp' and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a ), wh_patitioned2 as ( select row_number() over (partition by symbol, a2.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $4 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $5 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $6) AND interval >= 60 AND percent >= 60 AND type = 'kl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a2 ), wh_patitioned3 as ( select row_number() over (partition by symbol, a3.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, type, whid, whp.exchange, whp.symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime + (interval || ' minutes')::interval as patternendtime, patternprice as predictionpricefrom, patternprice as predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $7 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $8 WHERE whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $9) AND interval >= 60 AND percent >= 60 AND type = 'ekl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 and dftt.dayofweek = 3) a3 ) select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, timezoneoffset, length, quality from wh_patitioned where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned2 where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality from wh_patitioned3 where rn = 1;
Date: 2023-03-01 11:59:07 Duration: 286ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.0.42 parameters: $1 = '621', $2 = '621', $3 = '621', $4 = '621', $5 = '621', $6 = '621', $7 = '621', $8 = '621', $9 = '621'
6 3s375ms 353 4ms 37ms 9ms /*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%xauusd%' AND timegranularity <= 1440);Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 11 353 3s375ms 9ms [ User: postgres - Total duration: 2s23ms - Times executed: 353 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s23ms - Times executed: 353 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:49:32 Duration: 37ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:00:27 Duration: 35ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:22:25 Duration: 32ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
7 3s104ms 2,489 0ms 16ms 1ms /*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 #7
Day Hour Count Duration Avg duration 11 2,489 3s104ms 1ms [ User: postgres - Total duration: 348ms - Times executed: 2489 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 348ms - Times executed: 2489 ]
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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: 2023-03-01 11:25:32 Duration: 16ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '601544697017945303'
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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: 2023-03-01 11:03:49 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '601555775508795303'
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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: 2023-03-01 11:05:21 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '601555777398207303'
8 2s641ms 16 61ms 652ms 165ms with sym_info as ( ;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 11 16 2s641ms 165ms [ User: postgres - Total duration: 3s247ms - Times executed: 16 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s247ms - Times executed: 16 ]
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with sym_info as ( ;
Date: 2023-03-01 11:06:38 Duration: 652ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '617', $2 = 'Forex', $3 = 'Forex', $4 = '617', $5 = 'Forex', $6 = '617', $7 = '617', $8 = 'Forex'
-
with sym_info as ( ;
Date: 2023-03-01 11:36:35 Duration: 636ms 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'
-
with sym_info as ( ;
Date: 2023-03-01 11:51:36 Duration: 404ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.4.238 parameters: $1 = '617', $2 = 'Forex', $3 = 'Forex', $4 = '617', $5 = 'Forex', $6 = '617', $7 = '617', $8 = 'Forex'
9 2s363ms 332 4ms 33ms 7ms /*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((symbol ilike '%xauusd%' AND timegranularity <= 1440);Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 11 332 2s363ms 7ms [ User: postgres - Total duration: 1s81ms - Times executed: 332 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s81ms - Times executed: 332 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:22:25 Duration: 33ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:42:26 Duration: 26ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:38:25 Duration: 25ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201
10 2s342ms 286 5ms 35ms 8ms /*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 11 286 2s342ms 8ms [ User: postgres - Total duration: 1s250ms - Times executed: 286 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s250ms - Times executed: 286 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:13:11 Duration: 35ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:07:32 Duration: 27ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:51:07 Duration: 27ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201
11 2s213ms 141 10ms 27ms 15ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #11
Day Hour Count Duration Avg duration 11 141 2s213ms 15ms [ User: postgres - Total duration: 5s338ms - Times executed: 141 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 5s338ms - Times executed: 141 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:07:35 Duration: 27ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '704151087', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:19:33 Duration: 26ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '3', $4 = '3', $5 = '6', $6 = '704151087', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059706590308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:31:33 Duration: 26ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '3', $4 = '3', $5 = '6', $6 = '704151087', $7 = '0'
12 2s201ms 23 4ms 729ms 95ms SELECT dss.downloadersymbol, psh.symbolid, s.symbol, s.longname, s.exchange, hour, ee.timezone as exchangetimezone, ee.mon_t1start as exchangestart, ee.mon_t1end as exchangeend, (psh.ave - psh.stddev / 2.0) AS low, psh.ave, (psh.ave + psh.stddev / 2.0) AS high, psh.enddate, dtt.absolutetimezoneoffset datafeedtimezoneoffset, dtt.timezone datafeedtimezonename FROM brokersymbollist bsl INNER JOIN powerstats_symboldata psd ON bsl.symbolid = psd.symbolid INNER JOIN powerstats_hourly psh ON psd.hourlysymbolID = psh.symbolid INNER JOIN symbols s ON psh.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN exchanges ee on ee.exchange = s.exchange INNER JOIN mat_ps_hourly_symbolid_max_enddate e ON psh.enddate = e.enddate AND psh.symbolid = e.symbolid WHERE psd.symbolid = $1 AND bsl.brokerid = $2 AND dtt.dayofweek = 3 GROUP BY dss.downloadersymbol, psh.symbolid, s.symbol, s.longname, s.exchange, psh.hour, (psh.ave - psh.stddev / 2.0), psh.ave, (psh.ave + psh.stddev / 2.0), psh.enddate, dtt.absolutetimezoneoffset, dtt.timezone, ee.timezone, ee.mon_t1start, ee.mon_t1end ORDER BY hour ASC;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 11 23 2s201ms 95ms [ User: postgres - Total duration: 2s749ms - Times executed: 23 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 2s749ms - Times executed: 23 ]
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SELECT dss.downloadersymbol, psh.symbolid, s.symbol, s.longname, s.exchange, hour, ee.timezone as exchangetimezone, ee.mon_t1start as exchangestart, ee.mon_t1end as exchangeend, (psh.ave - psh.stddev / 2.0) AS low, psh.ave, (psh.ave + psh.stddev / 2.0) AS high, psh.enddate, dtt.absolutetimezoneoffset datafeedtimezoneoffset, dtt.timezone datafeedtimezonename FROM brokersymbollist bsl INNER JOIN powerstats_symboldata psd ON bsl.symbolid = psd.symbolid INNER JOIN powerstats_hourly psh ON psd.hourlysymbolID = psh.symbolid INNER JOIN symbols s ON psh.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN exchanges ee on ee.exchange = s.exchange INNER JOIN mat_ps_hourly_symbolid_max_enddate e ON psh.enddate = e.enddate AND psh.symbolid = e.symbolid WHERE psd.symbolid = $1 AND bsl.brokerid = $2 AND dtt.dayofweek = 3 GROUP BY dss.downloadersymbol, psh.symbolid, s.symbol, s.longname, s.exchange, psh.hour, (psh.ave - psh.stddev / 2.0), psh.ave, (psh.ave + psh.stddev / 2.0), psh.enddate, dtt.absolutetimezoneoffset, dtt.timezone, ee.timezone, ee.mon_t1start, ee.mon_t1end ORDER BY hour ASC;
Date: 2023-03-01 11:01:05 Duration: 729ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '515840243239577300', $2 = '558'
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SELECT dss.downloadersymbol, psh.symbolid, s.symbol, s.longname, s.exchange, hour, ee.timezone as exchangetimezone, ee.mon_t1start as exchangestart, ee.mon_t1end as exchangeend, (psh.ave - psh.stddev / 2.0) AS low, psh.ave, (psh.ave + psh.stddev / 2.0) AS high, psh.enddate, dtt.absolutetimezoneoffset datafeedtimezoneoffset, dtt.timezone datafeedtimezonename FROM brokersymbollist bsl INNER JOIN powerstats_symboldata psd ON bsl.symbolid = psd.symbolid INNER JOIN powerstats_hourly psh ON psd.hourlysymbolID = psh.symbolid INNER JOIN symbols s ON psh.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN exchanges ee on ee.exchange = s.exchange INNER JOIN mat_ps_hourly_symbolid_max_enddate e ON psh.enddate = e.enddate AND psh.symbolid = e.symbolid WHERE psd.symbolid = $1 AND bsl.brokerid = $2 AND dtt.dayofweek = 3 GROUP BY dss.downloadersymbol, psh.symbolid, s.symbol, s.longname, s.exchange, psh.hour, (psh.ave - psh.stddev / 2.0), psh.ave, (psh.ave + psh.stddev / 2.0), psh.enddate, dtt.absolutetimezoneoffset, dtt.timezone, ee.timezone, ee.mon_t1start, ee.mon_t1end ORDER BY hour ASC;
Date: 2023-03-01 11:52:57 Duration: 605ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '515840243239577300', $2 = '558'
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SELECT dss.downloadersymbol, psh.symbolid, s.symbol, s.longname, s.exchange, hour, ee.timezone as exchangetimezone, ee.mon_t1start as exchangestart, ee.mon_t1end as exchangeend, (psh.ave - psh.stddev / 2.0) AS low, psh.ave, (psh.ave + psh.stddev / 2.0) AS high, psh.enddate, dtt.absolutetimezoneoffset datafeedtimezoneoffset, dtt.timezone datafeedtimezonename FROM brokersymbollist bsl INNER JOIN powerstats_symboldata psd ON bsl.symbolid = psd.symbolid INNER JOIN powerstats_hourly psh ON psd.hourlysymbolID = psh.symbolid INNER JOIN symbols s ON psh.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss ON s.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname INNER JOIN exchanges ee on ee.exchange = s.exchange INNER JOIN mat_ps_hourly_symbolid_max_enddate e ON psh.enddate = e.enddate AND psh.symbolid = e.symbolid WHERE psd.symbolid = $1 AND bsl.brokerid = $2 AND dtt.dayofweek = 3 GROUP BY dss.downloadersymbol, psh.symbolid, s.symbol, s.longname, s.exchange, psh.hour, (psh.ave - psh.stddev / 2.0), psh.ave, (psh.ave + psh.stddev / 2.0), psh.enddate, dtt.absolutetimezoneoffset, dtt.timezone, ee.timezone, ee.mon_t1start, ee.mon_t1end ORDER BY hour ASC;
Date: 2023-03-01 11:06:25 Duration: 445ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '515840243241002300', $2 = '558'
13 2s40ms 1,479 0ms 6ms 1ms /*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 #13
Day Hour Count Duration Avg duration 11 1,479 2s40ms 1ms [ User: postgres - Total duration: 180ms - Times executed: 1479 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 180ms - Times executed: 1479 ]
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2023-03-01 11:24:34 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '601555542469792301'
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2023-03-01 11:05:21 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '601555773874522301'
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2023-03-01 11:24:34 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '601552248238567301'
14 1s974ms 248 4ms 38ms 7ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((c.symbol ilike '%xauusd%' AND timegranularity <= 1440);Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 11 248 1s974ms 7ms [ User: postgres - Total duration: 9s676ms - Times executed: 248 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 9s676ms - Times executed: 248 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((c.symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:37:18 Duration: 38ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '65535', $4 = '3', $5 = '348166439', $6 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((c.symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:49:07 Duration: 23ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '65535', $4 = '3', $5 = '-327832305', $6 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((c.symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:00:27 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '3', $4 = '3', $5 = '-1711913209', $6 = '0'
15 1s912ms 174 5ms 59ms 10ms /*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%eurusd%' AND timegranularity = 15);Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 11 174 1s912ms 10ms [ User: postgres - Total duration: 710ms - Times executed: 174 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 710ms - Times executed: 174 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%eurusd%' AND timegranularity = 15);
Date: 2023-03-01 11:25:32 Duration: 59ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%eurusd%' AND timegranularity = 15);
Date: 2023-03-01 11:37:34 Duration: 28ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%eurusd%' AND timegranularity = 15);
Date: 2023-03-01 11:00:27 Duration: 27ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
16 1s836ms 68,086 0ms 6ms 0ms select 1;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 11 68,085 1s835ms 0ms 12 1 0ms 0ms [ User: postgres - Total duration: 357ms - Times executed: 68086 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 357ms - Times executed: 68015 ]
[ Application: [unknown] - Total duration: 0ms - Times executed: 71 ]
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select 1;
Date: 2023-03-01 11:31:07 Duration: 6ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201
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select 1;
Date: 2023-03-01 11:02:01 Duration: 5ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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select 1;
Date: 2023-03-01 11:51:50 Duration: 4ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201
17 1s831ms 119 10ms 27ms 15ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 11 119 1s831ms 15ms [ User: postgres - Total duration: 4s105ms - Times executed: 119 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 4s105ms - Times executed: 119 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:50:25 Duration: 27ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '1', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '-706881497', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:16:56 Duration: 25ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '916658087', $7 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN symbolgroup sg ON c.symbolid = sg.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND sg.groupid = 515852059715831308 AND patternclassid = $1 AND patternlengthbars >= $2 AND a.PatternID & $3 > 0 AND dftt.dayofweek = $4 AND a.qtytp >= $5 AND a.resultuid > $6 AND c.nonliquid = $7 AND c.deleted = 0 AND dss.enabled = 1 ORDER BY relevant DESC, age asc, PatternEndTime DESC, qtp DESC LIMIT 50;
Date: 2023-03-01 11:12:56 Duration: 25ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23 parameters: $1 = '2', $2 = '20', $3 = '39', $4 = '3', $5 = '0', $6 = '916658087', $7 = '0'
18 1s710ms 178 4ms 51ms 9ms /*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 11 178 1s710ms 9ms [ User: postgres - Total duration: 1s460ms - Times executed: 178 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 1s460ms - Times executed: 178 ]
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:25:32 Duration: 51ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:49:32 Duration: 31ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.FibonacciResultList*/ SELECT DISTINCT a.ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, errormargin as rq, (1 - noise) as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, averagequality, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN fibonacci_results a ON a.symbolid = s.symbolid INNER JOIN FibonacciPatterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_fibonacci_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((symbol ilike '%eurusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:00:27 Duration: 24ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
19 1s675ms 224 4ms 35ms 7ms /*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((c.symbol ilike '%eurusd%' AND timegranularity <= 1440);Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 11 224 1s675ms 7ms [ User: postgres - Total duration: 3s536ms - Times executed: 224 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 3s536ms - Times executed: 224 ]
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((c.symbol ilike '%eurusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:59:08 Duration: 35ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '2', $2 = '20', $3 = '3', $4 = '3', $5 = '-926609193', $6 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((c.symbol ilike '%eurusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:31:07 Duration: 30ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '2', $2 = '20', $3 = '3', $4 = '3', $5 = '-892056761', $6 = '0'
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/*server.KeyLevelResultList*/ SELECT DISTINCT a.ResultUID AS ruid, c.symbolid AS sid, c.symbol AS sym, c.longname as longname, c.shortname, c.Exchange AS e, c.timegranularity AS tg, p.PatternID AS pid, a.direction AS d, cast(atbaridentified as timestamp) AS pet, cast(patternstarttime as timestamp) AS pst, PatternPrice AS patp, breakoutprice as pE, breakoutbars as bE, errorMargin as erm, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, cast(x0 as timestamp) AS x0, cast(x1 as timestamp) AS x1, cast(x2 as timestamp) AS x2, cast(( case when x3 = '' then '1900-01-01' else x3 end) as timestamp) AS x3, cast((case when x4 = '' then '1900-01-01' else x4 end) as timestamp) AS x4, cast(( case when x5 = '' then '1900-01-01' else x5 end) as timestamp) AS x5, cast((case when x6 = '' then '1900-01-01' else x6 end) as timestamp) AS x6, cast(( case when x7 = '' then '1900-01-01' else x7 end) as timestamp) AS x7, cast((case when x8 = '' then '1900-01-01' else x8 end) as timestamp) AS x8, cast(( case when x9 = '' then '1900-01-01' else x9 end) as timestamp) AS x9, cast(atbaridentified as timestamp) as PatternEndTime, cast(atbaridentified as timestamp) as atBar, cast((case when approachingtimestamp = '' then '1900-01-01' else approachingtimestamp end) as timestamp) as apr, dftt.timezone as tz, dftt.absolutetimezoneoffset as tzOs, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant, cast(0.0 as double precision) as premium, cast(0 as bigint) as instrumentid, 0 as derivativeid, 0 as underlyingid, 0 as isunderlying FROM symbols c INNER JOIN brokersymbollist b ON c.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = c.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN keylevels_results a ON a.symbolid = c.symbolid INNER JOIN hrspatterns p ON a.patternid = p.patternid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 558 AND (((c.symbol ilike '%eurusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:31:07 Duration: 27ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.201 parameters: $1 = '1', $2 = '20', $3 = '3', $4 = '3', $5 = '-213586921', $6 = '0'
20 1s668ms 177 4ms 37ms 9ms /*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((s.symbol ilike '%xauusd%' AND timegranularity <= 1440);Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 11 177 1s668ms 9ms [ User: postgres - Total duration: 7s741ms - Times executed: 177 ]
[ Application: PostgreSQL JDBC Driver - Total duration: 7s741ms - Times executed: 177 ]
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((s.symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:02:01 Duration: 37ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((s.symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:37:18 Duration: 21ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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/*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, a.resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname, CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND (((s.symbol ilike '%xauusd%' AND timegranularity <= 1440);
Date: 2023-03-01 11:42:25 Duration: 20ms Database: postgres User: acaweb_fx Remote: postgres Application: 192.168.1.23
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Events
Log levels
Key values
- 688,339 Log entries
Events distribution
Key values
- 0 PANIC entries
- 93 FATAL entries
- 699 ERROR entries
- 0 WARNING entries
Most Frequent Errors/Events
Key values
- 350 Max number of times the same event was reported
- 792 Total events found
Rank Times reported Error 1 350 ERROR: Downloader symbol ... on classname ... already exists. Use the add_downloadersymboltobroker_retool function instead.
Times Reported Most Frequent Error / Event #1
Day Hour Count Mar 01 11 350 - ERROR: Downloader symbol [F_TLREF1M0223] on classname [LEADERCAPITAL2] already exists. Use the add_downloadersymboltobroker_retool function instead.
- ERROR: Downloader symbol [F_USDTRY1123] on classname [LEADERCAPITAL2] already exists. Use the add_downloadersymboltobroker_retool function instead.
- ERROR: Downloader symbol [F_CNHTRY1223] on classname [LEADERCAPITAL2] already exists. Use the add_downloadersymboltobroker_retool function instead.
Context: PL/pgSQL function addsymbolsv8_retool(character varying,character varying,character varying,character varying,character varying,character varying,integer,character varying,bigint,integer,boolean,boolean) line 64 at RAISE
Statement: SELECT * FROM "public"."addsymbolsv8_retool"($1, $2, $3, $4, $5, $6, $7, $8, $9, $10, $11, $12)Date: 2023-03-01 11:05:38 Database: acaweb_fx Application: dreamfactory User: postgres Remote: 192.168.1.44
Context: PL/pgSQL function addsymbolsv8_retool(character varying,character varying,character varying,character varying,character varying,character varying,integer,character varying,bigint,integer,boolean,boolean) line 64 at RAISE
Statement: SELECT * FROM "public"."addsymbolsv8_retool"($1, $2, $3, $4, $5, $6, $7, $8, $9, $10, $11, $12)Date: 2023-03-01 11:05:38 Database: acaweb_fx Application: dreamfactory User: postgres Remote: 192.168.1.44
Context: PL/pgSQL function addsymbolsv8_retool(character varying,character varying,character varying,character varying,character varying,character varying,integer,character varying,bigint,integer,boolean,boolean) line 64 at RAISE
Statement: SELECT * FROM "public"."addsymbolsv8_retool"($1, $2, $3, $4, $5, $6, $7, $8, $9, $10, $11, $12)Date: 2023-03-01 11:05:39 Database: acaweb_fx Application: dreamfactory User: postgres Remote: 192.168.1.44
2 132 ERROR: canceling statement due to user request
Times Reported Most Frequent Error / Event #2
Day Hour Count Mar 01 11 132 - ERROR: canceling statement due to user request
Statement: /*server.CPResultList*/ SELECT DISTINCT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, s.symbol,shortname,timegranularity, patternendtime,pattern,a.direction,trendchange,patternlengthbars,patternquality,a.resultuid as uid,breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, gmttimefound, dftt.absolutetimezoneoffset as tzOs, dftt.timezone as tz, longname , CASE WHEN rar.age IS NOT NULL THEN rar.age WHEN a.resultuid <= (SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= (SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1) THEN 0 ELSE 1 END as relevant FROM symbols s INNER JOIN brokersymbollist b ON s.symbolid = b.symbolid INNER JOIN downloadersymbolsettings dss ON dss.symbolid = s.symbolid INNER JOIN datafeedstimetable dftt ON dftt.classname = dss.classname INNER JOIN autochartist_results a ON a.symbolid = s.symbolid INNER JOIN Patterns p ON a.pattern = p.patternname LEFT OUTER JOIN relevance_autochartist_results rar ON rar.resultuid = a.resultuid WHERE b.brokerid = 529 AND ((( s.symbol ilike '%audusd%' AND timegranularity = 60 ) ) OR (( s.symbol ilike '%audusd%' AND timegranularity <= 1440 ) ) OR (( s.symbol ilike '%euraud%' AND timegranularity <= 1440 ) ) OR (( s.symbol ilike '%eurusd%' AND timegranularity <= 1440 ) )) AND breakout >= 0.0 AND patternendtime = LatestBarAtBreakoutTime AND patternlengthbars >= 20 AND patternquality >= 0.3 AND initialtrend >= 0.0 AND symmetry >= 0.0 AND noise <= 1.0 AND volumeincrease >= 0.0 AND TemporaryPattern = 0 AND PatternID & 65535 > 0 AND s.nonliquid = 0 AND s.deleted = 0 AND dss.enabled = 1 AND a.resultuid > 0 AND s.nonliquid = 0 AND dftt.dayofweek = 3 ORDER BY relevant DESC, age asc, PatternEndTime DESC, PatternQuality DESC LIMIT 50
Date: 2023-03-01 11:00:07 Database: acaweb_fx Application: PostgreSQL JDBC Driver User: postgres Remote: 192.168.1.23
3 99 LOG: process ... still waiting for AccessExclusiveLock on object 0 of class 1262 of database ... after ... ms
Times Reported Most Frequent Error / Event #3
Day Hour Count Mar 01 11 99 - LOG: process 16603 still waiting for AccessExclusiveLock on object 0 of class 1262 of database 0 after 1000.042 ms
- LOG: process 16619 still waiting for AccessExclusiveLock on object 0 of class 1262 of database 0 after 1000.040 ms
- LOG: process 16657 still waiting for AccessExclusiveLock on object 0 of class 1262 of database 0 after 1000.033 ms
Detail: Process holding the lock: 16662. Wait queue: 16603, 16619, 16657, 16658, 16652, 16645, 16620, 16613, 16654, 16626, 16688, 16692, 16664, 16690, 16691, 16640, 16689.
Date: 2023-03-01 11:04:26 Database: acaweb_fx Application: [unknown] User: postgres Remote: 192.168.4.142
Detail: Process holding the lock: 16662. Wait queue: 16603, 16619, 16657, 16658, 16652, 16645, 16620, 16613, 16654, 16626, 16688, 16692, 16664, 16690, 16691, 16640, 16689.
Date: 2023-03-01 11:04:27 Database: acaweb_fx Application: [unknown] User: postgres Remote: 192.168.4.142
Detail: Process holding the lock: 16745. Wait queue: 16657, 16613, 16620, 16692, 16626, 16664, 16691, 16640, 16603, 16619, 16783, 16782, 16662, 16752, 16658, 16645.
Date: 2023-03-01 11:04:30 Database: acaweb_fx Application: [unknown] User: postgres Remote: 192.168.4.142
4 95 LOG: process ... still waiting for ShareLock on transaction ... after ... ms
Times Reported Most Frequent Error / Event #4
Day Hour Count Mar 01 11 95 - LOG: process 14138 still waiting for ShareLock on transaction 428702892 after 1000.063 ms
- LOG: process 14597 still waiting for ShareLock on transaction 428702887 after 1000.085 ms
- LOG: process 14661 still waiting for ShareLock on transaction 428702887 after 1000.066 ms
Detail: Process holding the lock: 21848. Wait queue: 27597, 28136, 28687, 28744, 29224, 29751, 30364, 30837, 1356, 1470, 1727, 2430, 2590, 2646, 3216, 5914, 7581, 12237, 12566, 13338, 14313, 16022, 16624, 18668, 22307, 22699, 22706, 23568, 23585, 24925, 24955, 27796, 28177, 28377, 29400, 30049, 30340, 32392, 2844, 4099, 12920, 14138.
Context: while inserting index tuple (7495,17) in relation "t30"
Statement: 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=$18Date: 2023-03-01 11:00:21 Database: acaweb_fx Application: [unknown] User: postgres Remote: 192.168.4.142
Detail: Process holding the lock: 20037. Wait queue: 22930, 23010, 23225, 23311, 23827, 23934, 23970, 23982, 24089, 24104, 24349, 24423, 24713, 24811, 25603, 29151, 32047, 558, 1467, 5501, 5625, 5902, 6671, 7090, 7732, 8107, 9500, 12513, 14207, 18701, 18750, 22136, 22683, 23398, 27523, 27688, 27914, 28037, 28912, 29380, 29553, 30609, 2934, 2999, 3622, 4153, 4808, 5098, 7326, 7405, 7434, 7892, 7930, 8868, 9002, 9072, 9185, 9243, 9501, 9627, 9699, 9892, 9926, 10027, 12522, 14597.
Context: while inserting index tuple (38989,81) in relation "t15"
Statement: 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=$18Date: 2023-03-01 11:00:35 Database: acaweb_fx Application: [unknown] User: postgres Remote: 192.168.4.142
Detail: Process holding the lock: 20037. Wait queue: 22930, 23010, 23225, 23311, 23827, 23934, 23970, 23982, 24089, 24104, 24349, 24423, 24713, 24811, 25603, 29151, 32047, 558, 1467, 5501, 5625, 5902, 6671, 7090, 7732, 8107, 9500, 12513, 14207, 18701, 18750, 22136, 22683, 23398, 27523, 27688, 27914, 28037, 28912, 29380, 29553, 30609, 2934, 2999, 3622, 4153, 4808, 5098, 7326, 7405, 7434, 7892, 7930, 8868, 9002, 9072, 9185, 9243, 9501, 9627, 9699, 9892, 9926, 10027, 12522, 14597, 14661.
Context: while inserting index tuple (35046,99) in relation "t15"
Statement: 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=$18Date: 2023-03-01 11:00:45 Database: acaweb_fx Application: [unknown] User: postgres Remote: 192.168.4.142
5 93 FATAL: connection to client lost
Times Reported Most Frequent Error / Event #5
Day Hour Count Mar 01 11 93 - FATAL: connection to client lost
Date: 2023-03-01 11:00:07 Database: acaweb_fx Application: PostgreSQL JDBC Driver User: postgres Remote: 192.168.1.23
6 9 LOG: process ... still waiting for ExclusiveLock on relation ... of database ... after ... ms
Times Reported Most Frequent Error / Event #6
Day Hour Count Mar 01 11 9 - LOG: process 27322 still waiting for ExclusiveLock on relation 5894536 of database 5881926 after 1000.053 ms
- LOG: process 29913 still waiting for ExclusiveLock on relation 5894453 of database 5881926 after 1000.053 ms
- LOG: process 30732 still waiting for ExclusiveLock on relation 5894453 of database 5881926 after 1000.044 ms
Detail: Processes holding the lock: 24352, 9754, 12748, 24661, 25190, 15771, 24056, 24941, 24057, 24100, 25556, 27390, 27372. Wait queue: 27322.
Context: SQL statement "REFRESH MATERIALIZED VIEW CONCURRENTLY relevance_autochartist_results" PL/pgSQL function updateresultsmaterializedview() line 5 at SQL statement
Statement: select updateresultsmaterializedview()Date: 2023-03-01 11:08:46 Database: acaweb_fx Application: psql User: postgres Remote: [local]
Detail: Process holding the lock: 28299. Wait queue: 29913.
Statement: refresh materialized view concurrently latest_t15_candle_view;Date: 2023-03-01 11:13:52 Database: acaweb_fx Application: [unknown] User: postgres Remote: 192.168.4.98
Detail: Process holding the lock: 29913. Wait queue: 30732.
Statement: refresh materialized view concurrently latest_t15_candle_view;Date: 2023-03-01 11:16:49 Database: acaweb_fx Application: [unknown] User: postgres Remote: 192.168.4.98
7 7 ERROR: canceling autovacuum task
Times Reported Most Frequent Error / Event #7
Day Hour Count Mar 01 11 7 - ERROR: canceling autovacuum task
Context: while vacuuming index "pk_relevance_autochartist_results" of relation "public.relevance_autochartist_results" automatic vacuum of table "acaweb_fx.public.relevance_autochartist_results"
Date: 2023-03-01 11:08:46
8 4 ERROR: duplicate key value violates unique constraint "..."
Times Reported Most Frequent Error / Event #8
Day Hour Count Mar 01 11 4 - ERROR: duplicate key value violates unique constraint "idx_uniq_mt4datafeederrors_des"
Detail: Key (datafeedname, eventtimestamp, status)=(LEADERCAPITAL2, 2023-03-01 09:05:16, OK) already exists.
Statement: insert into "public"."mt4datafeederrors" ("datafeedname", "eventtimestamp", "errordescription", "status", "serveraddress", "username") values ($1, $2, $3, $4, $5, $6) returning "id"Date: 2023-03-01 11:05:16 Database: acaweb_fx Application: dreamfactory User: postgres Remote: 192.168.1.44
9 3 ERROR: relation "..." does not exist
Times Reported Most Frequent Error / Event #9
Day Hour Count Mar 01 11 3 - ERROR: relation "t0" does not exist at character 83
- ERROR: relation "timezones_vi_vn" does not exist at character 191
Statement: SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T0 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050 ) a ORDER BY PriceDateTime ASC
Date: 2023-03-01 11:21:57 Database: acaweb_fx Application: PostgreSQL JDBC Driver User: postgres Remote: 192.168.1.23
Statement: SELECT tl.timezone langTimezone, t.timezone as timezone, (cast(substring(t.gmoffset,0,4) as double precision)*60 + cast(substring(t.gmoffset,5,2) as double precision))/60 as gmoffset FROM timezones_vi_VN tl INNER JOIN timezones t ON tl.timezoneid = t.timezoneid ORDER BY t.timezone
Date: 2023-03-01 11:46:36 Database: acaweb_fx Application: PostgreSQL JDBC Driver User: postgres Remote: 192.168.1.201