pgBadger-
Global information
- Generated on Sat Mar 28 07:59:30 2026
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-03-28_090000.log
- Parsed 980,342 log entries in 28s
- Log start from 2026-03-28 09:00:00 to 2026-03-28 09:59:28
-
Overview
Global Stats
- 175 Number of unique normalized queries
- 127,939 Number of queries
- 1h10m46s Total query duration
- 2026-03-28 09:00:00 First query
- 2026-03-28 09:59:28 Last query
- 3,596 queries/s at 2026-03-28 09:00:59 Query peak
- 1h10m46s Total query duration
- 3s5ms Prepare/parse total duration
- 17s952ms Bind total duration
- 1h10m25s Execute total duration
- 238 Number of events
- 2 Number of unique normalized events
- 237 Max number of times the same event was reported
- 0 Number of cancellation
- 10 Total number of automatic vacuums
- 20 Total number of automatic analyzes
- 1,201 Number temporary file
- 577.00 MiB Max size of temporary file
- 104.64 MiB Average size of temporary file
- 1,473 Total number of sessions
- 13 sessions at 2026-03-28 09:58:48 Session peak
- 16d1h6m21s Total duration of sessions
- 15m41s Average duration of sessions
- 86 Average queries per session
- 2s883ms Average queries duration per session
- 15m38s Average idle time per session
- 1,463 Total number of connections
- 27 connections/s at 2026-03-28 09:03:48 Connection peak
- 3 Total number of databases
SQL Traffic
Key values
- 3,596 queries/s Query Peak
- 2026-03-28 09:00:59 Date
SELECT Traffic
Key values
- 1,762 queries/s Query Peak
- 2026-03-28 09:00:59 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 104 queries/s Query Peak
- 2026-03-28 09:16:18 Date
Queries duration
Key values
- 1h10m46s 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 28 09 127,939 0ms 49s42ms 33ms 2m54s 3m30s 3m53s Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Mar 28 09 47,390 0 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Mar 28 09 11,493 690 0 0 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Mar 28 09 10,422 47,735 4.58 16.86% Day Hour Count Average / Second Mar 28 09 1,463 0.41/s Day Hour Count Average Duration Average idle time Mar 28 09 1,473 15m41s 15m38s -
Connections
Established Connections
Key values
- 27 connections Connection Peak
- 2026-03-28 09:03:48 Date
Connections per database
Key values
- acaweb_fx Main Database
- 1,463 connections Total
Connections per user
Key values
- postgres Main User
- 1,463 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 713 connections
- 1,463 Total connections
-
Sessions
Simultaneous sessions
Key values
- 13 sessions Session Peak
- 2026-03-28 09:58:48 Date
Histogram of session times
Key values
- 1,117 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 1,473 sessions Total
Sessions per user
Key values
- postgres Main User
- 1,473 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 1,473 sessions Total
Host Count Total Duration Average Duration 182.165.1.54 2 23h23m40s 11h41m50s 192.168.0.114 2 10m 5m 192.168.0.216 116 7m46s 4s24ms 192.168.0.74 10 2d23h14m32s 7h7m27s 192.168.0.84 2 23h59m15s 11h59m37s 192.168.1.131 2 23h59m13s 11h59m36s 192.168.1.145 22 2d18h26s 3h1s 192.168.1.15 9 2d17h19m6s 7h15m27s 192.168.1.20 44 3d14h41m43s 1h58m13s 192.168.1.238 2 23h59m10s 11h59m35s 192.168.1.239 54 306ms 5ms 192.168.1.90 6 52ms 8ms 192.168.2.126 18 5s738ms 318ms 192.168.3.199 38 22s531ms 592ms 192.168.4.142 713 8m9s 687ms 192.168.4.33 67 1m2s 931ms 192.168.4.98 330 13s933ms 42ms [local] 36 1m30s 2s515ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 1,886 buffers Checkpoint Peak
- 2026-03-28 09:05:47 Date
- 189.041 seconds Highest write time
- 3.224 seconds Sync time
Checkpoints Wal files
Key values
- 1 files Wal files usage Peak
- 2026-03-28 09:49:47 Date
Checkpoints distance
Key values
- 20.20 Mo Distance Peak
- 2026-03-28 09:05:47 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Mar 28 09 10,613 1,060.478s 8.403s 1,075.91s Day Hour Added Removed Recycled Synced files Longest sync Average sync Mar 28 09 0 0 4 904 3.224s 0.114s Day Hour Count Avg time (sec) Mar 28 09 0 0s Day Hour Mean distance Mean estimate Mar 28 09 5,735.50 kB 16,690.92 kB -
Temporary Files
Size of temporary files
Key values
- 577.00 MiB Temp Files size Peak
- 2026-03-28 09:37:14 Date
Number of temporary files
Key values
- 6 per second Temp Files Peak
- 2026-03-28 09:36:44 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Mar 28 09 1,201 122.72 GiB 104.64 MiB Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 237 122.10 GiB 292.72 MiB 577.00 MiB 527.57 MiB classname, case when latestdbwritetime < current_timestamp - interval ? then ? else ? end as is_stale from latest_t15_candle_view order by classname;-
classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;
Date: 2026-03-28 09:00:14 Duration: 0ms
2 180 296.93 MiB 137.65 KiB 3.81 MiB 1.65 MiB with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ), ar as ( select a.*, rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end ), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on sg.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc ;-
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 = $1 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 = $2 AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ($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 ar.pattern in ($16)) AND ($17 = 0 OR ($18 = 1 AND ar.breakout >= 0) OR ($19 = 2 AND ar.breakout < 0)) AND ($20 = 0 OR ar.patternlengthbars <= $21) and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $22 OR relevant = 1) AND ($23 = 0 OR age <= $24) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2026-03-28 09:00:16 Duration: 0ms
3 46 220.10 MiB 4.73 MiB 4.85 MiB 4.78 MiB select resultuid from relevance_fibonacci_results order by resultuid desc limit ?), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp)))), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;-
SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4, $5, $6, $7, $8, $9, $10)) AND ($11 = 0 OR s.exchange in ($12)) AND ($13 = 0 OR coalesce(bim.code, s.symbol) in ($14)) AND ($15 = 0 OR fr.pattern in ($16)) AND ($17 = 0 OR fr.patternlengthbars <= $18) AND ($19 = 0 OR ($20 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($21 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), 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: 2026-03-28 09:00:24 Duration: 0ms
4 19 58.82 MiB 3.02 MiB 3.22 MiB 3.10 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 s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?)), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;-
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 s.deleted = 0 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, $244, $245, $246, $247, $248, $249, $250, $251, $252, $253, $254, $255, $256, $257, $258, $259, $260, $261, $262, $263, $264, $265, $266, $267, $268, $269, $270, $271, $272, $273, $274, $275, $276, $277, $278, $279, $280, $281, $282, $283, $284, $285, $286, $287, $288, $289, $290, $291, $292, $293, $294, $295, $296, $297, $298, $299, $300, $301, $302, $303, $304, $305, $306, $307, $308, $309, $310, $311, $312, $313, $314, $315, $316, $317, $318, $319, $320, $321, $322)) AND ($323 = 0 OR ccr.patternlengthbars <= $324)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $325 OR relevant = 1) AND ($326 = 0 OR age <= $327) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2026-03-28 09:00:57 Duration: 0ms
5 12 21.26 MiB 137.65 KiB 4.26 MiB 1.77 MiB with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ? ;-
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 = $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 autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN relevance_keylevels_results rar ON rar.resultuid = kr.resultuid LEFT JOIN LATERAL calc_kl_signal_filter (kr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4)) AND ($5 = 0 OR s.exchange in ($6)) AND ($7 = 0 OR coalesce(bim.code, s.symbol) in ($8)) AND ($9 = 0 OR p.patternname in ($10)) AND ($11 = 0 OR kr.patternclassid in ($12)) AND ($13 = 0 OR kr.patternlengthbars <= $14) AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $15 OR relevant = 1) AND ($16 = 0 OR age <= $17) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2026-03-28 09:06:11 Duration: 0ms
6 6 30.51 MiB 3.06 MiB 9.14 MiB 5.09 MiB jr.resultuid as resultuid, jr.direction as direction, jr.patternendtime as identified, jr.patternlengthbars as length, jr.patternstarttime as patternstarttime, case when jr.trendchangeid = ? then ? else ? end as trendchange, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, jp.patternname as pattern_name, dtt.timezone as timezone, ? as age, cps.pip, g.basegroupname from japsticks_results jr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = jr.symbolid inner join relevance_japsticks_results rar on rar.resultuid = jr.resultuid inner join symbols s on jr.symbolid = s.symbolid and s.nonliquid = ? inner join japsticks_patterns jp on jr.patternid = jp.id inner join downloadersymbolsettings dss on jr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where jr.gmttimefound > now() - interval ? and s.deleted = ? and (jr.simulation = ? or jr.simulation is null) and (rar.relevant = ?) --and (semicolon_age = ? or rar.age <= semicolon_age) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or jp.patternname in (...)) and (? = ? or jr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results order by symbolid, resultuid ) select * from results order by identified desc, length desc ;-
jr.resultuid AS resultuid, jr.direction AS direction, jr.patternendtime AS identified, jr.patternlengthbars AS length, jr.patternstarttime AS patternstarttime, case when jr.trendchangeid = 1 then 'Continuation' else 'Reversal' end AS trendchange, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, jp.patternname AS pattern_name, dtt.timezone AS timezone, 0 AS age, cps.pip, g.basegroupname FROM japsticks_results jr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = jr.symbolid INNER JOIN relevance_japsticks_results rar ON rar.resultuid = jr.resultuid INNER JOIN symbols s ON jr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN japsticks_patterns jp ON jr.patternid = jp.id INNER JOIN downloadersymbolsettings dss ON jr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE jr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (jr.simulation = 0 OR jr.simulation IS NULL) AND (rar.relevant = 1) --AND (semicolon_age = 0 OR rar.age <= semicolon_age) AND ($2 = 0 OR s.timegranularity in ($3)) AND ($4 = 0 OR s.exchange in ($5)) AND ($6 = 0 OR coalesce(bim.code, s.symbol) in ($7)) AND ($8 = 0 OR jp.patternname in ($9)) AND ($10 = 0 OR jr.patternlengthbars <= $11)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2026-03-28 09:01:18 Duration: 0ms
Queries generating the largest temporary files
Rank Size Query 1 577.00 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:37:14 ]
2 574.01 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:43:13 ]
3 574.01 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:43:58 ]
4 571.01 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:05:14 ]
5 571.01 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:33:13 ]
6 568.01 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:11:29 ]
7 565.02 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:14:15 ]
8 565.02 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:33:29 ]
9 565.02 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:39:59 ]
10 565.02 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:52:01 ]
11 565.02 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:56:45 ]
12 562.02 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:03:43 ]
13 562.02 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:15:13 ]
14 562.02 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:34:13 ]
15 562.02 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:47:30 ]
16 562.02 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:48:13 ]
17 562.02 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:51:01 ]
18 562.02 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:53:00 ]
19 562.02 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:57:58 ]
20 559.05 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-28 09:19:13 ]
-
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
- pg_catalog.pg_type (4) Main table analyzed (database acaweb_fx)
- 20 analyzes Total
Table Number of analyzes acaweb_fx.pg_catalog.pg_type 4 acaweb_fx.pg_catalog.pg_attribute 4 acaweb_fx.public.datafeeds_latestrun 3 acaweb_fx.pg_catalog.pg_class 3 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.pg_catalog.pg_depend 2 socialmedia.public.processes 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 Total 20 Vacuums per table
Key values
- public.datafeeds_latestrun (3) Main table vacuumed on database acaweb_fx
- 10 vacuums Total
Index Buffer usage Skipped WAL usage Table Vacuums scans hits misses dirtied pins frozen records full page bytes acaweb_fx.public.datafeeds_latestrun 3 0 369 0 8 0 0 37 8 41,277 acaweb_fx.pg_catalog.pg_type 2 2 368 0 34 0 0 144 36 218,380 acaweb_fx.pg_catalog.pg_attribute 2 2 1,932 0 200 0 134 702 198 1,259,588 acaweb_fx.public.latest_t15_candle_view 1 1 94 0 1 0 0 6 1 9,055 acaweb_fx.pg_catalog.pg_statistic 1 1 855 0 67 0 651 303 59 280,846 acaweb_fx.pg_catalog.pg_class 1 1 329 0 43 0 78 122 44 259,324 Total 10 7 3,947 931 353 0 863 1,314 346 2,068,470 Tuples removed per table
Key values
- pg_catalog.pg_attribute (3350) Main table with removed tuples on database acaweb_fx
- 5119 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.pg_catalog.pg_attribute 2 2 3,350 21,314 0 0 536 acaweb_fx.pg_catalog.pg_statistic 1 1 822 4,002 0 0 1,194 acaweb_fx.pg_catalog.pg_type 2 2 638 2,910 0 0 88 acaweb_fx.public.datafeeds_latestrun 3 0 166 42 0 0 48 acaweb_fx.pg_catalog.pg_class 1 1 84 2,594 0 0 150 acaweb_fx.public.latest_t15_candle_view 1 1 59 12 0 0 1 Total 10 7 5,119 30,874 0 0 2,017 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.public.latest_t15_candle_view 1 1 59 0 acaweb_fx.pg_catalog.pg_type 2 2 638 0 acaweb_fx.public.datafeeds_latestrun 3 0 166 0 acaweb_fx.pg_catalog.pg_statistic 1 1 822 0 acaweb_fx.pg_catalog.pg_attribute 2 2 3350 0 acaweb_fx.pg_catalog.pg_class 1 1 84 0 Total 10 7 5,119 0 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Mar 28 09 10 20 - 0 sec Highest CPU-cost vacuum
-
Locks
Locks by types
Key values
- AccessShareLock Main Lock Type
- 1 locks Total
Most frequent waiting queries (N)
Rank Count Total time Min time Max time Avg duration Query 1 1 1s353ms 1s353ms 1s353ms 1s353ms select datetimeupdate from latest_candle_datetime_per_receng where recognitionengine ilike ?;-
SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'Alpari - 1';
Date: 2026-03-28 09:17:02
Queries that waited the most
Rank Wait time Query 1 1s353ms SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'Alpari - 1';[ Date: 2026-03-28 09:17:02 ]
-
Queries
Queries by type
Key values
- 47,390 Total read queries
- 14,427 Total write queries
Queries by database
Key values
- unknown Main database
- 127,296 Requests
- 1h10m25s (unknown)
- Main time consuming database
Queries by user
Key values
- unknown Main user
- 127,296 Requests
User Request type Count Duration postgres Total 643 0ms others 212 0ms select 71 0ms tcl 332 0ms update 28 0ms unknown Total 127,296 1h10m25s cte 1,580 0ms insert 11,493 0ms others 2,058 0ms select 47,319 0ms tcl 332 0ms update 662 0ms Duration by user
Key values
- 1h10m25s (unknown) Main time consuming user
User Request type Count Duration postgres Total 643 0ms others 212 0ms select 71 0ms tcl 332 0ms update 28 0ms unknown Total 127,296 1h10m25s cte 1,580 0ms insert 11,493 0ms others 2,058 0ms select 47,319 0ms tcl 332 0ms update 662 0ms Queries by host
Key values
- unknown Main host
- 127,939 Requests
- 1h10m25s (unknown)
- Main time consuming host
Queries by application
Key values
- unknown Main application
- 127,903 Requests
- 1h10m25s (unknown)
- Main time consuming application
Number of cancelled queries
Key values
- 1 per second Cancelled query Peak
- 2026-03-28 09:13:28 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 48,214 0-1ms duration
Slowest individual queries
Rank Duration Query NO DATASET
Time consuming queries
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 0ms 7 0ms 0ms 0ms select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 28 09 7 0ms 0ms 2 0ms 103 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Mar 28 09 103 0ms 0ms 3 0ms 2,451 0ms 0ms 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Mar 28 09 2,451 0ms 0ms 4 0ms 317 0ms 0ms 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, timegranularity as interval, direction as direction, patternendtime as patternendtime, patternstartprice as psp, patternendprice as pep, target03 as t03, target16 as t16, patternlengthbars as length, p.patternname as patternname, dtt.timezone, cps.pip from fibonacci_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 fibonaccipatterns p on a.pattern = p.patternname left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Mar 28 09 317 0ms 0ms 5 0ms 238 0ms 0ms 0ms select * from ( select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity) as k order by timegranularity;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Mar 28 09 238 0ms 0ms 6 0ms 299 0ms 0ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Mar 28 09 299 0ms 0ms 7 0ms 1 0ms 0ms 0ms insert into resultmedia (processresultsid, type, name, filename) values (?, ?, ?, ?) returning id;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Mar 28 09 1 0ms 0ms 8 0ms 18 0ms 0ms 0ms select cast(count(*) / cast(setting as numeric) * ? as int) from pg_stat_activity, pg_settings where name = ? group by setting;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Mar 28 09 18 0ms 0ms 9 0ms 238 0ms 0ms 0ms select v.datname, c.relname, v.phase, v.heap_blks_total, v.heap_blks_scanned, v.heap_blks_vacuumed, v.index_vacuum_count, v.max_dead_tuples, v.num_dead_tuples from pg_stat_progress_vacuum as v join pg_class c on c.oid = v.relid;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Mar 28 09 238 0ms 0ms 10 0ms 232 0ms 0ms 0ms select distinct s.statsid as statsid, sy.exchange as name from stats s inner join broker b on s.brokerid = b.brokerid inner join brokerconfig bc on b.brokerid = bc.brokerid inner join stats_symbols ss on s.statsid = ss.statsid inner join downloadersymbolsettings dss on ss.symbolid = dss.symbolid inner join symbols sy on dss.symbolid = sy.symbolid where dss.enabled = ? and s.brokerid is not null and b.brokerid = ? and s.groupingtype ilike ? and s.description ilike ? || b.name || ? and s.description ilike ? || sy.exchange || ? and s.description not ilike ? || ? || ? union all select distinct s.statsid as statsid, basegroupname as name from stats s inner join broker b on s.brokerid = b.brokerid inner join brokerconfig bc on b.brokerid = bc.brokerid inner join stats_symbols ss on s.statsid = ss.statsid inner join downloadersymbolsettings dss on ss.symbolid = dss.symbolid inner join symbolgroup sg on dss.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bg.brokerid = b.brokerid where dss.enabled = ? and s.brokerid is not null and b.brokerid = ? and s.groupingtype not ilike ? and s.description ilike ? || b.name || ? and s.description ilike ? || g.basegroupname || ? and s.description not ilike ? || ? || ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 28 09 232 0ms 0ms 11 0ms 422 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) and name in (...) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) and name in (...) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Mar 28 09 422 0ms 0ms 12 0ms 17 0ms 0ms 0ms 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 #12
Day Hour Count Duration Avg duration Mar 28 09 17 0ms 0ms 13 0ms 332 0ms 0ms 0ms commit;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Mar 28 09 332 0ms 0ms 14 0ms 131 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Mar 28 09 131 0ms 0ms 15 0ms 4 0ms 0ms 0ms select psd.symbolid, psd.hourlysymbolid as intervalsymbolid, s.symbol, dtt.timezone, dtt.absolutetimezoneoffset, psh.hour as index, psh.ave, psh.stddev, ((psh.ave - psh.stddev) / ?.?) as low, ((psh.ave + psh.stddev) / ?.?) as high, ee.timezone as exchangetimezone, ee.mon_t1start as exchangestart, ee.mon_t1end as exchangeend from powerstats_symboldata psd 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 mat_ps_hourly_symbolid_max_enddate e on psh.enddate = e.enddate and psh.symbolid = e.symbolid inner join exchanges ee on ee.exchange = s.exchange where psd.symbolid = ? and dtt.dayofweek = ? order by hour asc;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Mar 28 09 4 0ms 0ms 16 0ms 238 0ms 0ms 0ms select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 28 09 238 0ms 0ms 17 0ms 10 0ms 0ms 0ms 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 #17
Day Hour Count Duration Avg duration Mar 28 09 10 0ms 0ms 18 0ms 6 0ms 0ms 0ms select pid, datname, client_addr from pg_stat_activity where query ilike ? and pid <> pg_backend_pid() and state = ? and datname = ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Mar 28 09 6 0ms 0ms 19 0ms 7 0ms 0ms 0ms update executions set isrunning = false, has_results = false, response = ? where id = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Mar 28 09 7 0ms 0ms 20 0ms 238 0ms 0ms 0ms select system_identifier from pg_control_system ();Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Mar 28 09 238 0ms 0ms Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 16,628 0ms 0ms 0ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 28 09 16,628 0ms 0ms 2 4,638 0ms 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Mar 28 09 4,638 0ms 0ms 3 3,562 0ms 0ms 0ms 0ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Mar 28 09 3,562 0ms 0ms 4 3,474 0ms 0ms 0ms 0ms select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Mar 28 09 3,474 0ms 0ms 5 3,055 0ms 0ms 0ms 0ms insert into t15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Mar 28 09 3,055 0ms 0ms 6 2,526 0ms 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Mar 28 09 2,526 0ms 0ms 7 2,517 0ms 0ms 0ms 0ms insert into t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Mar 28 09 2,517 0ms 0ms 8 2,451 0ms 0ms 0ms 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Mar 28 09 2,451 0ms 0ms 9 2,435 0ms 0ms 0ms 0ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Mar 28 09 2,435 0ms 0ms 10 1,095 0ms 0ms 0ms 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars as length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternstartprice, resy1, supporty1, dtt.timezone, cps.pip, newlevels.profit from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern left join currencypips cps on cps.symbol = s.symbol left join lateral calc_cp_signal (a.resultuid) newlevels on true where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 28 09 1,095 0ms 0ms 11 972 0ms 0ms 0ms 0ms select datetimeupdate from latest_candle_datetime_per_receng where recognitionengine ilike ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Mar 28 09 972 0ms 0ms -
SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'Alpari - 1';
Date: 2026-03-28 09:17:02 Duration: 0ms
12 808 0ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Mar 28 09 808 0ms 0ms 13 796 0ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Mar 28 09 796 0ms 0ms 14 525 0ms 0ms 0ms 0ms select symbolid, pricedatetime, classname, downloadfrequency, downloadersymbol, open, high, low, close, volume, bsf, sastdatetimereceived from ( select pricedatetime, dss.classname, dss.downloadfrequency, dss.symbolid, dss.downloadersymbol, t.open, t.high, t.low, t.close, t.volume, t.bsf, t.sastdatetimereceived, row_number() over (partition by t.symbolid order by t.pricedatetime desc) as rn from t15 t, downloadersymbolsettings dss, symbols s where dss.classname = ? and dss.downloadfrequency = ? and dss.symbolid = t.symbolid and s.symbolid = dss.symbolid and dss.enabled = ? and s.deleted = ? and dss.downloadersymbol in (...) and t.pricedatetime > now() - interval ?) as ranked_candles_table where rn = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Mar 28 09 525 0ms 0ms 15 422 0ms 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) and name in (...) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) and name in (...) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Mar 28 09 422 0ms 0ms 16 422 0ms 0ms 0ms 0ms select distinct category from ( select * from stats_hrsapproaches_summary where statsid = ?) as data;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 28 09 422 0ms 0ms 17 422 0ms 0ms 0ms 0ms select absolutetimezoneoffset from symbols s inner join brokersymbollist bsl on s.symbolid = bsl.symbolid inner join downloadersymbolsettings dss on bsl.symbolid = dss.symbolid inner join datafeedstimetable df on dss.classname = df.classname where brokerid = ? and lower(exchange) = lower(?) group by absolutetimezoneoffset;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Mar 28 09 422 0ms 0ms 18 422 0ms 0ms 0ms 0ms select distinct category from ( select * from stats_summary where statsid = ? union select * from stats_hrs_summary where statsid = ?) as data;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Mar 28 09 422 0ms 0ms 19 422 0ms 0ms 0ms 0ms select name from ( select * from ( select * from stats_summary ss where statsid = ? union select * from stats_hrs_summary where statsid = ?) as data where lower(category) = ? order by correct desc limit ?) a;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Mar 28 09 422 0ms 0ms 20 421 0ms 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = ? and category = lower(?) and name in (...) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Mar 28 09 421 0ms 0ms Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 0ms 0ms 0ms 7 0ms select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 28 09 7 0ms 0ms 2 0ms 0ms 0ms 103 0ms with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Mar 28 09 103 0ms 0ms 3 0ms 0ms 0ms 2,451 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Mar 28 09 2,451 0ms 0ms 4 0ms 0ms 0ms 317 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, timegranularity as interval, direction as direction, patternendtime as patternendtime, patternstartprice as psp, patternendprice as pep, target03 as t03, target16 as t16, patternlengthbars as length, p.patternname as patternname, dtt.timezone, cps.pip from fibonacci_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 fibonaccipatterns p on a.pattern = p.patternname left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Mar 28 09 317 0ms 0ms 5 0ms 0ms 0ms 238 0ms select * from ( select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity) as k order by timegranularity;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Mar 28 09 238 0ms 0ms 6 0ms 0ms 0ms 299 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Mar 28 09 299 0ms 0ms 7 0ms 0ms 0ms 1 0ms insert into resultmedia (processresultsid, type, name, filename) values (?, ?, ?, ?) returning id;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Mar 28 09 1 0ms 0ms 8 0ms 0ms 0ms 18 0ms select cast(count(*) / cast(setting as numeric) * ? as int) from pg_stat_activity, pg_settings where name = ? group by setting;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Mar 28 09 18 0ms 0ms 9 0ms 0ms 0ms 238 0ms select v.datname, c.relname, v.phase, v.heap_blks_total, v.heap_blks_scanned, v.heap_blks_vacuumed, v.index_vacuum_count, v.max_dead_tuples, v.num_dead_tuples from pg_stat_progress_vacuum as v join pg_class c on c.oid = v.relid;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Mar 28 09 238 0ms 0ms 10 0ms 0ms 0ms 232 0ms select distinct s.statsid as statsid, sy.exchange as name from stats s inner join broker b on s.brokerid = b.brokerid inner join brokerconfig bc on b.brokerid = bc.brokerid inner join stats_symbols ss on s.statsid = ss.statsid inner join downloadersymbolsettings dss on ss.symbolid = dss.symbolid inner join symbols sy on dss.symbolid = sy.symbolid where dss.enabled = ? and s.brokerid is not null and b.brokerid = ? and s.groupingtype ilike ? and s.description ilike ? || b.name || ? and s.description ilike ? || sy.exchange || ? and s.description not ilike ? || ? || ? union all select distinct s.statsid as statsid, basegroupname as name from stats s inner join broker b on s.brokerid = b.brokerid inner join brokerconfig bc on b.brokerid = bc.brokerid inner join stats_symbols ss on s.statsid = ss.statsid inner join downloadersymbolsettings dss on ss.symbolid = dss.symbolid inner join symbolgroup sg on dss.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bg.brokerid = b.brokerid where dss.enabled = ? and s.brokerid is not null and b.brokerid = ? and s.groupingtype not ilike ? and s.description ilike ? || b.name || ? and s.description ilike ? || g.basegroupname || ? and s.description not ilike ? || ? || ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 28 09 232 0ms 0ms 11 0ms 0ms 0ms 422 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) and name in (...) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) and name in (...) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Mar 28 09 422 0ms 0ms 12 0ms 0ms 0ms 17 0ms 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 #12
Day Hour Count Duration Avg duration Mar 28 09 17 0ms 0ms 13 0ms 0ms 0ms 332 0ms commit;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Mar 28 09 332 0ms 0ms 14 0ms 0ms 0ms 131 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Mar 28 09 131 0ms 0ms 15 0ms 0ms 0ms 4 0ms select psd.symbolid, psd.hourlysymbolid as intervalsymbolid, s.symbol, dtt.timezone, dtt.absolutetimezoneoffset, psh.hour as index, psh.ave, psh.stddev, ((psh.ave - psh.stddev) / ?.?) as low, ((psh.ave + psh.stddev) / ?.?) as high, ee.timezone as exchangetimezone, ee.mon_t1start as exchangestart, ee.mon_t1end as exchangeend from powerstats_symboldata psd 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 mat_ps_hourly_symbolid_max_enddate e on psh.enddate = e.enddate and psh.symbolid = e.symbolid inner join exchanges ee on ee.exchange = s.exchange where psd.symbolid = ? and dtt.dayofweek = ? order by hour asc;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Mar 28 09 4 0ms 0ms 16 0ms 0ms 0ms 238 0ms select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 28 09 238 0ms 0ms 17 0ms 0ms 0ms 10 0ms 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 #17
Day Hour Count Duration Avg duration Mar 28 09 10 0ms 0ms 18 0ms 0ms 0ms 6 0ms select pid, datname, client_addr from pg_stat_activity where query ilike ? and pid <> pg_backend_pid() and state = ? and datname = ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Mar 28 09 6 0ms 0ms 19 0ms 0ms 0ms 7 0ms update executions set isrunning = false, has_results = false, response = ? where id = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Mar 28 09 7 0ms 0ms 20 0ms 0ms 0ms 238 0ms select system_identifier from pg_control_system ();Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Mar 28 09 238 0ms 0ms Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 1s156ms 629 0ms 2ms 1ms SELECT symbolid, ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Mar 28 09 629 1s156ms 1ms -
SELECT symbolid, ;
Date: 2026-03-28 09:00:07 Duration: 2ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-03-28 09:05:52 Duration: 2ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-03-28 09:06:02 Duration: 2ms Database: postgres
2 433ms 471 0ms 9ms 0ms WITH rar_max as ( ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 09 471 433ms 0ms -
WITH rar_max as ( ;
Date: 2026-03-28 09:40:59 Duration: 9ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-03-28 09:40:59 Duration: 7ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-03-28 09:03:59 Duration: 5ms Database: postgres
3 257ms 2,312 0ms 0ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 09 2,312 257ms 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;
Date: 2026-03-28 09:11:02 Duration: 0ms Database: postgres
-
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: 2026-03-28 09:01:58 Duration: 0ms Database: postgres
-
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: 2026-03-28 09:11:58 Duration: 0ms Database: postgres
4 212ms 2,394 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 #4
Day Hour Count Duration Avg duration 09 2,394 212ms 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;
Date: 2026-03-28 09:35:59 Duration: 1ms Database: postgres
-
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: 2026-03-28 09:31:57 Duration: 0ms Database: postgres
-
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: 2026-03-28 09:10:43 Duration: 0ms Database: postgres
5 147ms 557 0ms 2ms 0ms SELECT ;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 09 557 147ms 0ms -
SELECT ;
Date: 2026-03-28 09:04:00 Duration: 2ms Database: postgres
-
SELECT ;
Date: 2026-03-28 09:30:03 Duration: 2ms Database: postgres
-
SELECT ;
Date: 2026-03-28 09:56:01 Duration: 2ms Database: postgres
6 139ms 107 0ms 1ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #6
Day Hour Count Duration Avg duration 09 107 139ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-28 09:16:08 Duration: 1ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-28 09:16:28 Duration: 1ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-28 09:30:09 Duration: 1ms Database: postgres
7 128ms 808 0ms 0ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 09 808 128ms 0ms -
SET extra_float_digits = 3;
Date: 2026-03-28 09:40:59 Duration: 0ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-03-28 09:40:59 Duration: 0ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-03-28 09:36:06 Duration: 0ms Database: postgres
8 125ms 594 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 #8
Day Hour Count Duration Avg duration 09 594 125ms 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;
Date: 2026-03-28 09:30:53 Duration: 1ms Database: postgres
-
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: 2026-03-28 09:01:36 Duration: 0ms Database: postgres
-
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: 2026-03-28 09:25:43 Duration: 0ms Database: postgres
9 112ms 666 0ms 0ms 0ms select category, ;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 09 666 112ms 0ms -
select category, ;
Date: 2026-03-28 09:10:56 Duration: 0ms Database: postgres
-
select category, ;
Date: 2026-03-28 09:00:51 Duration: 0ms Database: postgres
-
select category, ;
Date: 2026-03-28 09:10:56 Duration: 0ms Database: postgres
10 47ms 18 2ms 3ms 2ms select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 09 18 47ms 2ms -
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-03-28 09:51:01 Duration: 3ms Database: postgres
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-03-28 09:41:04 Duration: 3ms Database: postgres
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-03-28 09:41:04 Duration: 3ms Database: postgres
11 47ms 284 0ms 0ms 0ms INSERT INTO T1440_underlying (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 #11
Day Hour Count Duration Avg duration 09 284 47ms 0ms -
INSERT INTO T1440_underlying (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: 2026-03-28 09:31:22 Duration: 0ms Database: postgres
-
INSERT INTO T1440_underlying (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: 2026-03-28 09:47:07 Duration: 0ms Database: postgres
-
INSERT INTO T1440_underlying (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: 2026-03-28 09:47:09 Duration: 0ms Database: postgres
12 38ms 22 0ms 5ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 09 22 38ms 1ms -
WITH last_candle AS ( ;
Date: 2026-03-28 09:04:00 Duration: 5ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-03-28 09:52:05 Duration: 4ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-03-28 09:52:00 Duration: 4ms Database: postgres
13 35ms 288 0ms 1ms 0ms INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 09 288 35ms 0ms -
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-28 09:00:53 Duration: 1ms Database: postgres
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-28 09:31:01 Duration: 0ms Database: postgres
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-28 09:16:04 Duration: 0ms Database: postgres
14 26ms 40 0ms 2ms 0ms select distinct s.statsid as statsid, sy.exchange as name;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 09 40 26ms 0ms -
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-03-28 09:36:06 Duration: 2ms Database: postgres
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-03-28 09:10:54 Duration: 2ms Database: postgres
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-03-28 09:10:54 Duration: 2ms Database: postgres
15 18ms 7 1ms 5ms 2ms with wh_patitioned as ( ;Times Reported Time consuming prepare #15
Day Hour Count Duration Avg duration 09 7 18ms 2ms -
with wh_patitioned as ( ;
Date: 2026-03-28 09:03:58 Duration: 5ms Database: postgres
-
with wh_patitioned as ( ;
Date: 2026-03-28 09:40:54 Duration: 4ms Database: postgres
-
with wh_patitioned as ( ;
Date: 2026-03-28 09:05:59 Duration: 3ms Database: postgres
16 14ms 6 2ms 2ms 2ms select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 09 6 14ms 2ms -
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2026-03-28 09:00:05 Duration: 2ms Database: postgres
-
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2026-03-28 09:40:04 Duration: 2ms Database: postgres
-
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2026-03-28 09:20:05 Duration: 2ms Database: postgres
17 11ms 40 0ms 1ms 0ms select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 09 40 11ms 0ms -
select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;
Date: 2026-03-28 09:36:05 Duration: 1ms Database: postgres
-
select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;
Date: 2026-03-28 09:10:54 Duration: 1ms Database: postgres
-
select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;
Date: 2026-03-28 09:10:54 Duration: 1ms Database: postgres
18 10ms 206 0ms 0ms 0ms select 1;Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 09 206 10ms 0ms -
select 1;
Date: 2026-03-28 09:50:50 Duration: 0ms Database: postgres
-
select 1;
Date: 2026-03-28 09:40:59 Duration: 0ms Database: postgres
-
select 1;
Date: 2026-03-28 09:51:13 Duration: 0ms Database: postgres
19 10ms 796 0ms 0ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 09 796 10ms 0ms -
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-03-28 09:11:02 Duration: 0ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-03-28 09:36:05 Duration: 0ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-03-28 09:32:52 Duration: 0ms Database: postgres
20 9ms 40 0ms 0ms 0ms SELECT absolutetimezoneoffset;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 09 40 9ms 0ms -
SELECT absolutetimezoneoffset;
Date: 2026-03-28 09:10:56 Duration: 0ms Database: postgres
-
SELECT absolutetimezoneoffset;
Date: 2026-03-28 09:10:56 Duration: 0ms Database: postgres
-
SELECT absolutetimezoneoffset;
Date: 2026-03-28 09:10:57 Duration: 0ms Database: postgres
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 8s627ms 667 0ms 69ms 12ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Mar 28 09 667 8s627ms 12ms -
WITH rar_max as ( ;
Date: 2026-03-28 09:40:59 Duration: 69ms Database: postgres parameters: $1 = 't', $2 = '667', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '84', $14 = 'AUDCAD', $15 = 'AUDCHF', $16 = 'AUDJPY', $17 = 'AUDNZD', $18 = 'AUDSGD', $19 = 'CADCHF', $20 = 'CADJPY', $21 = 'CHFJPY', $22 = 'EURAUD', $23 = 'EURCAD', $24 = 'EURCHF', $25 = 'EURCZK', $26 = 'EURGBP', $27 = 'EURHUF', $28 = 'EURJPY', $29 = 'EURNOK', $30 = 'EURNZD', $31 = 'EURPLN', $32 = 'EURSEK', $33 = 'EURSGD', $34 = 'EURTRY', $35 = 'EURZAR', $36 = 'GBPAUD', $37 = 'GBPCAD', $38 = 'GBPCHF', $39 = 'GBPJPY', $40 = 'GBPNZD', $41 = 'GBPPLN', $42 = 'GBPSEK', $43 = 'GBPSGD', $44 = 'NZDCAD', $45 = 'NZDCHF', $46 = 'NZDJPY', $47 = 'NZDSGD', $48 = 'USDCNH', $49 = 'USDCZK', $50 = 'USDHUF', $51 = 'USDNOK', $52 = 'USDPLN', $53 = 'USDSEK', $54 = 'USDSGD', $55 = 'USDTRY', $56 = 'USDZAR', $57 = 'WTI', $58 = 'XBRUSD', $59 = 'XTIUSD', $60 = 'BTCUSD', $61 = 'XAGAUD', $62 = 'XAGUSD', $63 = 'XAUAUD', $64 = 'XAUUSD', $65 = 'XPTUSD', $66 = 'XPDUSD', $67 = 'AUDUSD', $68 = 'EURUSD', $69 = 'GBPUSD', $70 = 'NZDUSD', $71 = 'USDCAD', $72 = 'USDCHF', $73 = 'USDHKD', $74 = 'USDJPY', $75 = 'AUS200', $76 = 'CHINA300', $77 = 'CHINA50', $78 = 'DJ30', $79 = 'ESP35t', $80 = 'EUR50', $81 = 'EURO50', $82 = 'FRA40', $83 = 'GDAXI', $84 = 'GDAXIm', $85 = 'HK50', $86 = 'ITA40', $87 = 'J225', $88 = 'JP225', $89 = 'NAS100', $90 = 'SING30', $91 = 'SPA35', $92 = 'STOXX50', $93 = 'SUI20', $94 = 'UK100', $95 = 'US100', $96 = 'US30', $97 = 'US500', $98 = '0', $99 = '', $100 = '0', $101 = '0', $102 = '0', $103 = '500', $104 = '500', $105 = 't', $106 = '10', $107 = '10'
-
WITH rar_max as ( ;
Date: 2026-03-28 09:11:05 Duration: 63ms Database: postgres parameters: $1 = '558', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '160', $13 = 'AUDSGD', $14 = 'CHFSGD', $15 = 'EURDKK', $16 = 'EURHKD', $17 = 'EURNOK', $18 = 'EURPLN', $19 = 'EURSEK', $20 = 'EURSGD', $21 = 'EURTRY', $22 = 'EURZAR', $23 = 'GBPDKK', $24 = 'GBPNOK', $25 = 'GBPSEK', $26 = 'GBPSGD', $27 = 'NOKJPY', $28 = 'NOKSEK', $29 = 'SEKJPY', $30 = 'SGDJPY', $31 = 'USDCNH', $32 = 'USDCZK', $33 = 'USDDKK', $34 = 'USDHKD', $35 = 'USDHUF', $36 = 'USDMXN', $37 = 'USDNOK', $38 = 'USDPLN', $39 = 'USDRUB', $40 = 'USDSEK', $41 = 'USDTHB', $42 = 'USDTRY', $43 = 'USDZAR', $44 = 'AUDUSD', $45 = 'EURUSD', $46 = 'GBPUSD', $47 = 'USDCAD', $48 = 'USDCHF', $49 = 'USDJPY', $50 = 'AUDCAD', $51 = 'AUDCHF', $52 = 'AUDJPY', $53 = 'AUDNZD', $54 = 'CADCHF', $55 = 'CADJPY', $56 = 'CHFJPY', $57 = 'EURAUD', $58 = 'EURCAD', $59 = 'EURCHF', $60 = 'EURGBP', $61 = 'EURJPY', $62 = 'EURNZD', $63 = 'GBPAUD', $64 = 'GBPCAD', $65 = 'GBPCHF', $66 = 'GBPJPY', $67 = 'GBPNZD', $68 = 'NZDCAD', $69 = 'NZDCHF', $70 = 'NZDJPY', $71 = 'NZDUSD', $72 = 'USDSGD', $73 = 'AUS200', $74 = 'DE30', $75 = 'ES35', $76 = 'F40', $77 = 'HK50', $78 = 'IT40', $79 = 'JP225', $80 = 'STOXX50', $81 = 'UK100', $82 = 'US2000', $83 = 'US30', $84 = 'US500', $85 = 'CHINA50', $86 = 'USTEC', $87 = 'XAGEUR', $88 = 'XAGUSD', $89 = 'XAUUSD', $90 = 'XAUEUR', $91 = 'XPDUSD', $92 = 'XPTUSD', $93 = 'AUDSGD', $94 = 'CHFSGD', $95 = 'EURDKK', $96 = 'EURHKD', $97 = 'EURNOK', $98 = 'EURPLN', $99 = 'EURSEK', $100 = 'EURSGD', $101 = 'EURTRY', $102 = 'EURZAR', $103 = 'GBPDKK', $104 = 'GBPNOK', $105 = 'GBPSEK', $106 = 'GBPSGD', $107 = 'NOKJPY', $108 = 'NOKSEK', $109 = 'SEKJPY', $110 = 'SGDJPY', $111 = 'USDCNH', $112 = 'USDCZK', $113 = 'USDDKK', $114 = 'USDHKD', $115 = 'USDHUF', $116 = 'USDMXN', $117 = 'USDNOK', $118 = 'USDPLN', $119 = 'USDRUB', $120 = 'USDSEK', $121 = 'USDTHB', $122 = 'USDTRY', $123 = 'USDZAR', $124 = 'AUDUSD', $125 = 'EURUSD', $126 = 'GBPUSD', $127 = 'USDCAD', $128 = 'USDCHF', $129 = 'USDJPY', $130 = 'AUDCAD', $131 = 'AUDCHF', $132 = 'AUDJPY', $133 = 'AUDNZD', $134 = 'CADCHF', $135 = 'CADJPY', $136 = 'CHFJPY', $137 = 'EURAUD', $138 = 'EURCAD', $139 = 'EURCHF', $140 = 'EURGBP', $141 = 'EURJPY', $142 = 'EURNZD', $143 = 'GBPAUD', $144 = 'GBPCAD', $145 = 'GBPCHF', $146 = 'GBPJPY', $147 = 'GBPNZD', $148 = 'NZDCAD', $149 = 'NZDCHF', $150 = 'NZDJPY', $151 = 'NZDUSD', $152 = 'USDSGD', $153 = 'AUS200', $154 = 'DE30', $155 = 'ES35', $156 = 'F40', $157 = 'HK50', $158 = 'IT40', $159 = 'JP225', $160 = 'STOXX50', $161 = 'UK100', $162 = 'US2000', $163 = 'US30', $164 = 'US500', $165 = 'CHINA50', $166 = 'USTEC', $167 = 'XAGEUR', $168 = 'XAGUSD', $169 = 'XAUUSD', $170 = 'XAUEUR', $171 = 'XPDUSD', $172 = 'XPTUSD', $173 = '700', $174 = '700', $175 = 't', $176 = '10', $177 = '10'
-
WITH rar_max as ( ;
Date: 2026-03-28 09:31:07 Duration: 58ms Database: postgres parameters: $1 = '627', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '213', $13 = '#ADBE', $14 = '#ALVG', $15 = '#AMZN', $16 = '#APPL', $17 = '#BA', $18 = '#BABA', $19 = '#BAYGn', $20 = '#BMWG', $21 = '#BNPP', $22 = '#CAT', $23 = '#CBKG', $24 = '#DAIGn', $25 = '#DIS', $26 = '#EA', $27 = '#FB', $28 = '#FDX', $29 = '#GE', $30 = '#GM', $31 = '#GOOGL', $32 = '#GS', $33 = '#INTC', $34 = '#JPM', $35 = '#KO', $36 = '#META', $37 = '#MSFT', $38 = '#NFLX', $39 = '#TSLA', $40 = '#VOWG', $41 = '#WMT', $42 = '#XOM', $43 = 'AUDCAD', $44 = 'AUDCHF', $45 = 'AUDJPY', $46 = 'AUDNZD', $47 = 'AUDUSD', $48 = 'AUS_200', $49 = 'BTCEUR', $50 = 'BTCGBP', $51 = 'BTCUSD', $52 = 'CADCHF', $53 = 'CADJPY', $54 = 'CHFJPY', $55 = 'CL_BRENT', $56 = 'DASHUSD', $57 = 'EOSUSD', $58 = 'ESP_35', $59 = 'ETHEUR', $60 = 'ETHGBP', $61 = 'ETHUSD', $62 = 'EURAUD', $63 = 'EURCAD', $64 = 'EURCHF', $65 = 'EURGBP', $66 = 'EURJPY', $67 = 'EURMXN', $68 = 'EURNOK', $69 = 'EURNZD', $70 = 'EURPLN', $71 = 'EURSEK', $72 = 'EURTRY', $73 = 'EURUSD', $74 = 'EUR_50', $75 = 'FRA_40', $76 = 'GBPAUD', $77 = 'GBPCAD', $78 = 'GBPCHF', $79 = 'GBPJPY', $80 = 'GBPNZD', $81 = 'GBPUSD', $82 = 'GBPZAR', $83 = 'GBR_100', $84 = 'HKDJPY', $85 = 'HKG_50', $86 = 'IOTAUSD', $87 = 'LTCEUR', $88 = 'LTCUSD', $89 = 'NAS100', $90 = 'NEOUSD', $91 = 'NOKJPY', $92 = 'NZDCAD', $93 = 'NZDCHF', $94 = 'NZDJPY', $95 = 'NZDUSD', $96 = 'OMGUSD', $97 = 'SPX500', $98 = 'TRXUSD', $99 = 'US30', $100 = 'USDCAD', $101 = 'USDCHF', $102 = 'USDCNH', $103 = 'USDDKK', $104 = 'USDJPY', $105 = 'USDMXN', $106 = 'USDNOK', $107 = 'USDPLN', $108 = 'USDSEK', $109 = 'USDSGD', $110 = 'USDZAR', $111 = 'USOIL', $112 = 'XAGUSD', $113 = 'XAUEUR', $114 = 'XAUUSD', $115 = 'XMRUSD', $116 = 'XPTUSD', $117 = 'XRPUSD', $118 = 'ZARJPY', $119 = 'ZECUSD', $120 = 'AUDCAD', $121 = 'AUDCHF', $122 = 'AUDJPY', $123 = 'AUDNZD', $124 = 'AUDUSD', $125 = 'CADCHF', $126 = 'CADJPY', $127 = 'CHFJPY', $128 = 'EURAUD', $129 = 'EURCAD', $130 = 'EURCHF', $131 = 'EURGBP', $132 = 'EURJPY', $133 = 'EURMXN', $134 = 'EURNOK', $135 = 'EURNZD', $136 = 'EURPLN', $137 = 'EURSEK', $138 = 'EURTRY', $139 = 'EURUSD', $140 = 'GBPAUD', $141 = 'GBPCAD', $142 = 'GBPCHF', $143 = 'GBPJPY', $144 = 'GBPNZD', $145 = 'GBPUSD', $146 = 'GBPZAR', $147 = 'HKDJPY', $148 = 'NOKJPY', $149 = 'NZDCAD', $150 = 'NZDCHF', $151 = 'NZDJPY', $152 = 'NZDUSD', $153 = 'USDCAD', $154 = 'USDCHF', $155 = 'USDCNH', $156 = 'USDDKK', $157 = 'USDJPY', $158 = 'USDMXN', $159 = 'USDNOK', $160 = 'USDPLN', $161 = 'USDSEK', $162 = 'USDSGD', $163 = 'USDZAR', $164 = 'ZARJPY', $165 = 'BTCEUR', $166 = 'BTCGBP', $167 = 'BTCUSD', $168 = 'DASHUSD', $169 = 'EOSUSD', $170 = 'ETHEUR', $171 = 'ETHGBP', $172 = 'ETHUSD', $173 = 'IOTAUSD', $174 = 'LTCEUR', $175 = 'LTCUSD', $176 = 'NEOUSD', $177 = 'OMGUSD', $178 = 'TRXUSD', $179 = 'XMRUSD', $180 = 'XRPUSD', $181 = 'ZECUSD', $182 = 'XAGUSD', $183 = 'XAUEUR', $184 = 'XAUUSD', $185 = 'XPTUSD', $186 = 'CL_BRENT', $187 = 'USOIL', $188 = '#ALVG', $189 = '#BAYGn', $190 = '#BMWG', $191 = '#BNPP', $192 = '#CBKG', $193 = '#DAIGn', $194 = '#VOWG', $195 = 'AUS_200', $196 = 'ESP_35', $197 = 'EUR_50', $198 = 'FRA_40', $199 = 'GBR_100', $200 = 'HKG_50', $201 = 'NAS100', $202 = 'SPX500', $203 = 'US30', $204 = '#ADBE', $205 = '#AMZN', $206 = '#APPL', $207 = '#BA', $208 = '#BABA', $209 = '#CAT', $210 = '#DIS', $211 = '#EA', $212 = '#FB', $213 = '#FDX', $214 = '#GE', $215 = '#GM', $216 = '#GOOGL', $217 = '#GS', $218 = '#INTC', $219 = '#JPM', $220 = '#KO', $221 = '#MSFT', $222 = '#NFLX', $223 = '#TSLA', $224 = '#WMT', $225 = '#XOM', $226 = '500', $227 = '500', $228 = 't', $229 = '10', $230 = '10'
2 3s56ms 9,092 0ms 9ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 09 9,092 3s56ms 0ms -
SELECT ;
Date: 2026-03-28 09:04:00 Duration: 9ms Database: postgres parameters: $1 = '515840243198780300'
-
SELECT ;
Date: 2026-03-28 09:56:00 Duration: 7ms Database: postgres parameters: $1 = '607914481342329303', $2 = '607914481342329303', $3 = '607914481342329303'
-
SELECT ;
Date: 2026-03-28 09:36:56 Duration: 6ms Database: postgres parameters: $1 = '515840243198780300'
3 1s837ms 629 0ms 5ms 2ms SELECT symbolid, ;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 09 629 1s837ms 2ms -
SELECT symbolid, ;
Date: 2026-03-28 09:11:02 Duration: 5ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '15', $3 = 'SPX500', $4 = 'US30'
-
SELECT symbolid, ;
Date: 2026-03-28 09:03:01 Duration: 4ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '30', $3 = 'NAS100'
-
SELECT symbolid, ;
Date: 2026-03-28 09:01:08 Duration: 4ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '15', $3 = 'XMRUSD'
4 1s354ms 232 0ms 22ms 5ms select distinct s.statsid as statsid, sy.exchange as name;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 09 232 1s354ms 5ms -
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-03-28 09:10:54 Duration: 22ms Database: postgres parameters: $1 = '1436', $2 = '1436'
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-03-28 09:10:54 Duration: 21ms Database: postgres parameters: $1 = '1436', $2 = '1436'
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-03-28 09:10:54 Duration: 21ms Database: postgres parameters: $1 = '1436', $2 = '1436'
5 660ms 8,007 0ms 1ms 0ms select category, ;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 09 8,007 660ms 0ms -
select category, ;
Date: 2026-03-28 09:10:56 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307', $2 = 'symbol', $3 = 'XAUUSD', $4 = 'XAGUSD', $5 = 'DOW30', $6 = 'USDJPY', $7 = 'AUDJPY', $8 = 'NZDJPY', $9 = 'GBPJPY', $10 = 'CHFJPY', $11 = 'OIL', $12 = 'NASDAQ100', $13 = 'EURJPY', $14 = 'SP500', $15 = 'GBPAUD', $16 = 'EURAUD', $17 = 'USDCAD', $18 = 'GBPCHF', $19 = 'EURGBP', $20 = 'EURCHF', $21 = 'OIL', $22 = 'EURCAD', $23 = 'DOW30', $24 = 'EURCAD', $25 = 'GBPUSD', $26 = 'NZDUSD', $27 = 'CHFJPY', $28 = 'EURJPY', $29 = 'EURUSD', $30 = 'AUDJPY', $31 = 'GBPAUD', $32 = 'EURUSD', $33 = 'EURAUD', $34 = 'XAGUSD', $35 = 'USDCHF', $36 = 'GBPUSD', $37 = 'AUDNZD', $38 = 'SP500', $39 = 'GBPJPY', $40 = 'NZDJPY', $41 = 'USDCAD', $42 = 'XAUUSD', $43 = 'USDJPY', $44 = 'RK_SSI', $45 = 'R_SSI', $46 = 'NASDAQ100', $47 = 'AUDUSD', $48 = 'NZDUSD', $49 = 'AUDUSD', $50 = 'GBPCHF', $51 = 'USDCHF', $52 = 'AUDNZD', $53 = '515852059317765307', $54 = 'symbol', $55 = 'XAUUSD', $56 = 'XAGUSD', $57 = 'DOW30', $58 = 'USDJPY', $59 = 'AUDJPY', $60 = 'NZDJPY', $61 = 'GBPJPY', $62 = 'CHFJPY', $63 = 'OIL', $64 = 'NASDAQ100', $65 = 'EURJPY', $66 = 'SP500', $67 = 'GBPAUD', $68 = 'EURAUD', $69 = 'USDCAD', $70 = 'GBPCHF', $71 = 'EURGBP', $72 = 'EURCHF', $73 = 'OIL', $74 = 'EURCAD', $75 = 'DOW30', $76 = 'EURCAD', $77 = 'GBPUSD', $78 = 'NZDUSD', $79 = 'CHFJPY', $80 = 'EURJPY', $81 = 'EURUSD', $82 = 'AUDJPY', $83 = 'GBPAUD', $84 = 'EURUSD', $85 = 'EURAUD', $86 = 'XAGUSD', $87 = 'USDCHF', $88 = 'GBPUSD', $89 = 'AUDNZD', $90 = 'SP500', $91 = 'GBPJPY', $92 = 'NZDJPY', $93 = 'USDCAD', $94 = 'XAUUSD', $95 = 'USDJPY', $96 = 'RK_SSI', $97 = 'R_SSI', $98 = 'NASDAQ100', $99 = 'AUDUSD', $100 = 'NZDUSD', $101 = 'AUDUSD', $102 = 'GBPCHF', $103 = 'USDCHF', $104 = 'AUDNZD'
-
select category, ;
Date: 2026-03-28 09:10:58 Duration: 1ms Database: postgres parameters: $1 = '601729875344536307', $2 = 'symbol', $3 = 'USDMXN', $4 = 'USDSEK', $5 = 'USDZAR', $6 = 'AUDJPY', $7 = 'CADJPY', $8 = 'XAUUSD', $9 = 'NZDJPY', $10 = 'XAGUSD', $11 = 'XAGEUR', $12 = 'USDHUF', $13 = 'USDJPY', $14 = 'ZARJPY', $15 = 'XAUEUR', $16 = 'EURJPY', $17 = 'GBPZAR', $18 = 'GBPJPY', $19 = 'USDCZK', $20 = 'CHFJPY', $21 = 'USDPLN', $22 = 'USDDKK', $23 = 'EURHUF', $24 = 'GBPAUD', $25 = 'USDCNH', $26 = 'USDNOK', $27 = 'GBPNZD', $28 = 'EURNOK', $29 = 'USDTRY', $30 = 'EURHUF', $31 = 'EURPLN', $32 = 'ZARJPY', $33 = 'USDCAD', $34 = 'EURGBP', $35 = 'EURNZD', $36 = 'EURAUD', $37 = 'CADCHF', $38 = 'USDHUF', $39 = 'EURCHF', $40 = 'USDHKD', $41 = 'GBPCAD', $42 = 'USDSGD', $43 = 'AUDNZD', $44 = 'CADJPY', $45 = 'USDZAR', $46 = 'USDMXN', $47 = 'EURCAD', $48 = 'GBPUSD', $49 = 'EURNZD', $50 = 'GBPCHF', $51 = 'GBPCAD', $52 = 'EURCAD', $53 = '601729875344536307', $54 = 'symbol', $55 = 'USDMXN', $56 = 'USDSEK', $57 = 'USDZAR', $58 = 'AUDJPY', $59 = 'CADJPY', $60 = 'XAUUSD', $61 = 'NZDJPY', $62 = 'XAGUSD', $63 = 'XAGEUR', $64 = 'USDHUF', $65 = 'USDJPY', $66 = 'ZARJPY', $67 = 'XAUEUR', $68 = 'EURJPY', $69 = 'GBPZAR', $70 = 'GBPJPY', $71 = 'USDCZK', $72 = 'CHFJPY', $73 = 'USDPLN', $74 = 'USDDKK', $75 = 'EURHUF', $76 = 'GBPAUD', $77 = 'USDCNH', $78 = 'USDNOK', $79 = 'GBPNZD', $80 = 'EURNOK', $81 = 'USDTRY', $82 = 'EURHUF', $83 = 'EURPLN', $84 = 'ZARJPY', $85 = 'USDCAD', $86 = 'EURGBP', $87 = 'EURNZD', $88 = 'EURAUD', $89 = 'CADCHF', $90 = 'USDHUF', $91 = 'EURCHF', $92 = 'USDHKD', $93 = 'GBPCAD', $94 = 'USDSGD', $95 = 'AUDNZD', $96 = 'CADJPY', $97 = 'USDZAR', $98 = 'USDMXN', $99 = 'EURCAD', $100 = 'GBPUSD', $101 = 'EURNZD', $102 = 'GBPCHF', $103 = 'GBPCAD', $104 = 'EURCAD'
-
select category, ;
Date: 2026-03-28 09:53:40 Duration: 1ms Database: postgres parameters: $1 = '515852059324736307', $2 = 'symbol', $3 = 'USDMXN', $4 = 'CHFZAR', $5 = 'AUDJPY', $6 = 'USDZAR', $7 = 'CADJPY', $8 = 'USDJPY', $9 = 'ZARJPY', $10 = 'CHFJPY', $11 = 'GBPZAR', $12 = 'EURMXN', $13 = 'TRYJPY', $14 = 'EURCNH', $15 = 'NZDJPY', $16 = 'GBPJPY', $17 = 'AUDZAR', $18 = 'EURNOK', $19 = 'USDHUF', $20 = 'EURZAR', $21 = 'USDNOK', $22 = 'EURTRY', $23 = 'USDSEK', $24 = 'EURHKD', $25 = 'USDCZK', $26 = 'USDDKK', $27 = 'SGDJPY', $28 = 'EURSEK', $29 = 'EURJPY', $30 = 'CHFHUF', $31 = 'NZDSEK', $32 = 'EURHUF', $33 = 'USDPLN', $34 = 'GBPNZD', $35 = 'USDCNH', $36 = 'EURCZK', $37 = 'USDILS', $38 = 'EURNZD', $39 = 'EURPLN', $40 = 'GBPAUD', $41 = 'EURGBP', $42 = 'EURAUD', $43 = 'EURCZK', $44 = 'TRYJPY', $45 = 'EURHUF', $46 = 'CHFHUF', $47 = 'USDCAD', $48 = 'ZARJPY', $49 = 'USDTRY', $50 = 'GBPCAD', $51 = 'USDZAR', $52 = 'AUDZAR', $53 = '515852059324736307', $54 = 'symbol', $55 = 'USDMXN', $56 = 'CHFZAR', $57 = 'AUDJPY', $58 = 'USDZAR', $59 = 'CADJPY', $60 = 'USDJPY', $61 = 'ZARJPY', $62 = 'CHFJPY', $63 = 'GBPZAR', $64 = 'EURMXN', $65 = 'TRYJPY', $66 = 'EURCNH', $67 = 'NZDJPY', $68 = 'GBPJPY', $69 = 'AUDZAR', $70 = 'EURNOK', $71 = 'USDHUF', $72 = 'EURZAR', $73 = 'USDNOK', $74 = 'EURTRY', $75 = 'USDSEK', $76 = 'EURHKD', $77 = 'USDCZK', $78 = 'USDDKK', $79 = 'SGDJPY', $80 = 'EURSEK', $81 = 'EURJPY', $82 = 'CHFHUF', $83 = 'NZDSEK', $84 = 'EURHUF', $85 = 'USDPLN', $86 = 'GBPNZD', $87 = 'USDCNH', $88 = 'EURCZK', $89 = 'USDILS', $90 = 'EURNZD', $91 = 'EURPLN', $92 = 'GBPAUD', $93 = 'EURGBP', $94 = 'EURAUD', $95 = 'EURCZK', $96 = 'TRYJPY', $97 = 'EURHUF', $98 = 'CHFHUF', $99 = 'USDCAD', $100 = 'ZARJPY', $101 = 'USDTRY', $102 = 'GBPCAD', $103 = 'USDZAR', $104 = 'AUDZAR'
6 398ms 9 20ms 98ms 44ms with wh_patitioned as ( ;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 09 9 398ms 44ms -
with wh_patitioned as ( ;
Date: 2026-03-28 09:05:59 Duration: 98ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
-
with wh_patitioned as ( ;
Date: 2026-03-28 09:40:54 Duration: 88ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
-
with wh_patitioned as ( ;
Date: 2026-03-28 09:36:54 Duration: 43ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
7 319ms 40 4ms 15ms 7ms WITH last_candle AS ( ;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 09 40 319ms 7ms -
WITH last_candle AS ( ;
Date: 2026-03-28 09:04:00 Duration: 15ms Database: postgres parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2026-03-28 09:40:28 Duration: 15ms Database: postgres parameters: $1 = '667', $2 = '667'
-
WITH last_candle AS ( ;
Date: 2026-03-28 09:36:00 Duration: 14ms Database: postgres parameters: $1 = '558', $2 = '558'
8 310ms 422 0ms 1ms 0ms SELECT absolutetimezoneoffset;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 09 422 310ms 0ms -
SELECT absolutetimezoneoffset;
Date: 2026-03-28 09:00:59 Duration: 1ms Database: postgres parameters: $1 = '632', $2 = 'Shares UK'
-
SELECT absolutetimezoneoffset;
Date: 2026-03-28 09:10:59 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'BROKER'
-
SELECT absolutetimezoneoffset;
Date: 2026-03-28 09:00:54 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'BROKER'
9 295ms 16,521 0ms 14ms 0ms select 1;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 09 16,521 295ms 0ms -
select 1;
Date: 2026-03-28 09:36:00 Duration: 14ms Database: postgres
-
select 1;
Date: 2026-03-28 09:35:52 Duration: 13ms Database: postgres
-
select 1;
Date: 2026-03-28 09:35:52 Duration: 7ms Database: postgres
10 227ms 107 1ms 2ms 2ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 09 107 227ms 2ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-28 09:16:08 Duration: 2ms Database: postgres parameters: $1 = 'BDSWISS'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-28 09:30:42 Duration: 2ms Database: postgres parameters: $1 = 'AXIORY'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-28 09:00:38 Duration: 2ms Database: postgres parameters: $1 = 'ICMARKETS'
11 203ms 2,451 0ms 0ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #11
Day Hour Count Duration Avg duration 09 2,451 203ms 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;
Date: 2026-03-28 09:01:58 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 17:00:00', $2 = '24754.7', $3 = '24824.7', $4 = '24703.9', $5 = '24724.3', $6 = '19136', $7 = '515840247933961300', $8 = '0', $9 = '2026-03-28 09:01:58.726', $10 = '2026-03-28 09:01:58.606', $11 = '24754.7', $12 = '24824.7', $13 = '24703.9', $14 = '24724.3', $15 = '19136', $16 = '0', $17 = '2026-03-28 09:01:58.726', $18 = '2026-03-28 09:01:58.606'
-
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: 2026-03-28 09:11:02 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 21:00:00', $2 = '45188.35', $3 = '45231.35', $4 = '45057.25', $5 = '45097.75', $6 = '16178', $7 = '515840248000890300', $8 = '0', $9 = '2026-03-28 09:11:02.148', $10 = '2026-03-28 09:11:02.043', $11 = '45188.35', $12 = '45231.35', $13 = '45057.25', $14 = '45097.75', $15 = '16178', $16 = '0', $17 = '2026-03-28 09:11:02.148', $18 = '2026-03-28 09:11:02.043'
-
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: 2026-03-28 09:11:58 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 17:00:00', $2 = '24754.7', $3 = '24824.7', $4 = '24703.9', $5 = '24724.3', $6 = '19136', $7 = '515840247933961300', $8 = '0', $9 = '2026-03-28 09:11:58.637', $10 = '2026-03-28 09:11:58.535', $11 = '24754.7', $12 = '24824.7', $13 = '24703.9', $14 = '24724.3', $15 = '19136', $16 = '0', $17 = '2026-03-28 09:11:58.637', $18 = '2026-03-28 09:11:58.535'
12 176ms 2,517 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 09 2,517 176ms 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;
Date: 2026-03-28 09:41:01 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 22:00:00', $2 = '23103.6', $3 = '23113.5', $4 = '23046.6', $5 = '23063.2', $6 = '9223', $7 = '515840248039147300', $8 = '0', $9 = '2026-03-28 09:41:01.182', $10 = '2026-03-28 09:41:01.113', $11 = '23103.6', $12 = '23113.5', $13 = '23046.6', $14 = '23063.2', $15 = '9223', $16 = '0', $17 = '2026-03-28 09:41:01.182', $18 = '2026-03-28 09:41:01.113'
-
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: 2026-03-28 09:10:43 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 21:00:00', $2 = '8432.8', $3 = '8443.9', $4 = '8431.4', $5 = '8436.5', $6 = '5367', $7 = '515840248015340300', $8 = '0', $9 = '2026-03-28 09:10:43.911', $10 = '2026-03-28 09:10:43.814', $11 = '8432.8', $12 = '8443.9', $13 = '8431.4', $14 = '8436.5', $15 = '5367', $16 = '0', $17 = '2026-03-28 09:10:43.911', $18 = '2026-03-28 09:10:43.814'
-
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: 2026-03-28 09:41:43 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 21:00:00', $2 = '8432.8', $3 = '8443.9', $4 = '8431.4', $5 = '8436.5', $6 = '5367', $7 = '515840248015340300', $8 = '0', $9 = '2026-03-28 09:41:43.471', $10 = '2026-03-28 09:41:43.363', $11 = '8432.8', $12 = '8443.9', $13 = '8431.4', $14 = '8436.5', $15 = '5367', $16 = '0', $17 = '2026-03-28 09:41:43.471', $18 = '2026-03-28 09:41:43.363'
13 142ms 3,055 0ms 2ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 09 3,055 142ms 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;
Date: 2026-03-28 09:46:03 Duration: 2ms Database: postgres parameters: $1 = '2026-03-27 23:45:00', $2 = '1.67398', $3 = '1.674665', $4 = '1.673425', $5 = '1.67389', $6 = '1270', $7 = '515840249382700300', $8 = '0', $9 = '2026-03-28 09:46:03.247', $10 = '2026-03-28 09:46:03.15', $11 = '1.67398', $12 = '1.674665', $13 = '1.673425', $14 = '1.67389', $15 = '1270', $16 = '0', $17 = '2026-03-28 09:46:03.247', $18 = '2026-03-28 09:46:03.15'
-
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: 2026-03-28 09:46:37 Duration: 1ms Database: postgres parameters: $1 = '2026-03-27 22:30:00', $2 = '8433.88', $3 = '8438.88', $4 = '8421.88', $5 = '8436.88', $6 = '542', $7 = '515840238058964300', $8 = '0', $9 = '2026-03-28 09:46:37.47', $10 = '2026-03-28 09:46:37.43', $11 = '8433.88', $12 = '8438.88', $13 = '8421.88', $14 = '8436.88', $15 = '542', $16 = '0', $17 = '2026-03-28 09:46:37.47', $18 = '2026-03-28 09:46:37.43'
-
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: 2026-03-28 09:47:07 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 23:45:00', $2 = '1.151345', $3 = '1.15143', $4 = '1.150825', $5 = '1.15086', $6 = '736', $7 = '515840249372435300', $8 = '0', $9 = '2026-03-28 09:47:07.776', $10 = '2026-03-28 09:47:07.729', $11 = '1.151345', $12 = '1.15143', $13 = '1.150825', $14 = '1.15086', $15 = '736', $16 = '0', $17 = '2026-03-28 09:47:07.776', $18 = '2026-03-28 09:47:07.729'
14 48ms 844 0ms 0ms 0ms select distinct category;Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 09 844 48ms 0ms -
select distinct category;
Date: 2026-03-28 09:53:00 Duration: 0ms Database: postgres parameters: $1 = '515852059324253307'
-
select distinct category;
Date: 2026-03-28 09:00:54 Duration: 0ms Database: postgres parameters: $1 = '515852059305993307', $2 = '515852059305993307'
-
select distinct category;
Date: 2026-03-28 09:00:54 Duration: 0ms Database: postgres parameters: $1 = '515852059305993307', $2 = '515852059305993307'
15 46ms 422 0ms 1ms 0ms SELECT name;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 09 422 46ms 0ms -
SELECT name;
Date: 2026-03-28 09:10:56 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307', $2 = '515852059317765307'
-
SELECT name;
Date: 2026-03-28 09:10:56 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307', $2 = '515852059317765307'
-
SELECT name;
Date: 2026-03-28 09:00:51 Duration: 0ms Database: postgres parameters: $1 = '515852059317765307', $2 = '515852059317765307'
16 46ms 284 0ms 0ms 0ms INSERT INTO T1440_underlying (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 09 284 46ms 0ms -
INSERT INTO T1440_underlying (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: 2026-03-28 09:31:22 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 00:00:00', $2 = '0.795105', $3 = '0.799355', $4 = '0.79415', $5 = '0.799035', $6 = '50447', $7 = '515840249379276300', $8 = '0', $9 = '2026-03-28 09:31:22.027', $10 = '2026-03-28 09:31:22.027', $11 = '0.795105', $12 = '0.799355', $13 = '0.79415', $14 = '0.799035', $15 = '50447', $16 = '0', $17 = '2026-03-28 09:31:22.027', $18 = '2026-03-28 09:31:22.027'
-
INSERT INTO T1440_underlying (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: 2026-03-28 09:47:09 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 00:00:00', $2 = '213.01', $3 = '213.104', $4 = '212.236', $5 = '212.5615', $6 = '190323', $7 = '515840249382462300', $8 = '0', $9 = '2026-03-28 09:47:09.84', $10 = '2026-03-28 09:47:09.839', $11 = '213.01', $12 = '213.104', $13 = '212.236', $14 = '212.5615', $15 = '190323', $16 = '0', $17 = '2026-03-28 09:47:09.84', $18 = '2026-03-28 09:47:09.839'
-
INSERT INTO T1440_underlying (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: 2026-03-28 09:47:07 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 00:00:00', $2 = '1.15276', $3 = '1.15479', $4 = '1.150185', $5 = '1.15086', $6 = '81087', $7 = '515840249373173300', $8 = '0', $9 = '2026-03-28 09:47:07.811', $10 = '2026-03-28 09:47:07.81', $11 = '1.15276', $12 = '1.15479', $13 = '1.150185', $14 = '1.15086', $15 = '81087', $16 = '0', $17 = '2026-03-28 09:47:07.811', $18 = '2026-03-28 09:47:07.81'
17 36ms 294 0ms 0ms 0ms INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 09 294 36ms 0ms -
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-28 09:16:14 Duration: 0ms Database: postgres parameters: $1 = '2026-03-28 00:00:00', $2 = '23.6773', $3 = '23.75635', $4 = '23.61275', $5 = '23.7083', $6 = '27935', $7 = '515840249405670300', $8 = '0', $9 = '2026-03-28 09:16:14.741', $10 = '2026-03-28 09:16:12.812', $11 = '23.6773', $12 = '23.75635', $13 = '23.61275', $14 = '23.7083', $15 = '27935', $16 = '0', $17 = '2026-03-28 09:16:14.741', $18 = '2026-03-28 09:16:12.812'
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INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-28 09:16:04 Duration: 0ms Database: postgres parameters: $1 = '2026-03-28 00:00:00', $2 = '1.9425e-05', $3 = '1.954e-05', $4 = '1.9295e-05', $5 = '1.93e-05', $6 = '2800', $7 = '515840249470879300', $8 = '0', $9 = '2026-03-28 09:16:04.523', $10 = '2026-03-28 09:16:02.624', $11 = '1.9425e-05', $12 = '1.954e-05', $13 = '1.9295e-05', $14 = '1.93e-05', $15 = '2800', $16 = '0', $17 = '2026-03-28 09:16:04.523', $18 = '2026-03-28 09:16:02.624'
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INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-28 09:30:10 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 20:00:00', $2 = '1.673315', $3 = '1.67668', $4 = '1.672215', $5 = '1.67389', $6 = '27570', $7 = '515840249383314300', $8 = '0', $9 = '2026-03-28 09:30:10.76', $10 = '2026-03-28 09:30:10.669', $11 = '1.673315', $12 = '1.67668', $13 = '1.672215', $14 = '1.67389', $15 = '27570', $16 = '0', $17 = '2026-03-28 09:30:10.76', $18 = '2026-03-28 09:30:10.669'
18 28ms 232 0ms 1ms 0ms select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 09 232 28ms 0ms -
select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;
Date: 2026-03-28 09:36:05 Duration: 1ms Database: postgres parameters: $1 = '1436'
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select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;
Date: 2026-03-28 09:10:54 Duration: 1ms Database: postgres parameters: $1 = '1436'
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select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;
Date: 2026-03-28 09:10:54 Duration: 1ms Database: postgres parameters: $1 = '1436'
19 25ms 5 3ms 6ms 5ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 09 5 25ms 5ms -
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-03-28 09:40:59 Duration: 6ms Database: postgres parameters: $1 = '667', $2 = '667'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-03-28 09:01:14 Duration: 6ms Database: postgres parameters: $1 = '627', $2 = '627'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-03-28 09:01:01 Duration: 6ms Database: postgres parameters: $1 = '627', $2 = '627'
20 18ms 53 0ms 4ms 0ms /*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 09 53 18ms 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;
Date: 2026-03-28 09:52:43 Duration: 4ms Database: postgres parameters: $1 = '607911881289503301'
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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: 2026-03-28 09:25:24 Duration: 2ms Database: postgres parameters: $1 = '607911820903305301'
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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: 2026-03-28 09:37:19 Duration: 1ms Database: postgres parameters: $1 = '607911236774208301'
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Events
Log levels
Key values
- 251,605 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 238 ERROR entries
- 0 WARNING entries
Most Frequent Errors/Events
Key values
- 237 Max number of times the same event was reported
- 238 Total events found
Rank Times reported Error 1 237 ERROR: canceling statement due to statement timeout
Times Reported Most Frequent Error / Event #1
Day Hour Count Mar 28 09 237 - ERROR: canceling statement due to statement timeout
Statement: /* service='datadog-agent' */ select count(*) from (select *, row_number() over (partition by whid order by id desc) r from whatshot_probability where "type" = 'cp' union select *, row_number() over (partition by whid order by id desc) r from whatshot_probability where "type" = 'ekl' union select *, row_number() over (partition by whid order by id desc) r from whatshot_probability where type = 'kl') as k where r > 3;
Date: 2026-03-28 09:00:14
2 1 LOG: process ... still waiting for AccessShareLock on relation ... of database ... after ... ms
Times Reported Most Frequent Error / Event #2
Day Hour Count Mar 28 09 1 - LOG: process 29944 still waiting for AccessShareLock on relation 5894441 of database 5881926 after 1000.038 ms at character 28
Detail: Process holding the lock: 29967. Wait queue: 29944.
Statement: SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'Alpari - 1'Date: 2026-03-28 09:17:02