pgBadger-
Global information
- Generated on Sun Feb 15 04:59:17 2026
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-02-15_060000.log
- Parsed 459,389 log entries in 16s
- Log start from 2026-02-15 06:00:00 to 2026-02-15 06:59:03
-
Overview
Global Stats
- 960 Number of unique normalized queries
- 83,508 Number of queries
- 2h56m9s Total query duration
- 2026-02-15 06:00:00 First query
- 2026-02-15 06:59:03 Last query
- 6,736 queries/s at 2026-02-15 06:05:02 Query peak
- 2h56m9s Total query duration
- 1s856ms Prepare/parse total duration
- 18s245ms Bind total duration
- 2h55m49s Execute total duration
- 14 Number of events
- 2 Number of unique normalized events
- 12 Max number of times the same event was reported
- 0 Number of cancellation
- 25 Total number of automatic vacuums
- 40 Total number of automatic analyzes
- 644 Number temporary file
- 139.87 MiB Max size of temporary file
- 4.61 MiB Average size of temporary file
- 1,524 Total number of sessions
- 12 sessions at 2026-02-15 06:54:00 Session peak
- 1d13h12m13s Total duration of sessions
- 1m27s Average duration of sessions
- 54 Average queries per session
- 6s935ms Average queries duration per session
- 1m20s Average idle time per session
- 1,524 Total number of connections
- 27 connections/s at 2026-02-15 06:03:48 Connection peak
- 6 Total number of databases
SQL Traffic
Key values
- 6,736 queries/s Query Peak
- 2026-02-15 06:05:02 Date
SELECT Traffic
Key values
- 3,366 queries/s Query Peak
- 2026-02-15 06:05:02 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 101 queries/s Query Peak
- 2026-02-15 06:38:49 Date
Queries duration
Key values
- 2h56m9s 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) Feb 15 06 83,508 0ms 14m14s 126ms 4m31s 5m59s 35m44s Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Feb 15 06 22,955 601 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Feb 15 06 12,312 496 13 78 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Feb 15 06 7,734 19,084 2.47 19.68% Day Hour Count Average / Second Feb 15 06 1,524 0.42/s Day Hour Count Average Duration Average idle time Feb 15 06 1,524 1m27s 1m20s -
Connections
Established Connections
Key values
- 27 connections Connection Peak
- 2026-02-15 06:03:48 Date
Connections per database
Key values
- acaweb_fx Main Database
- 1,524 connections Total
Connections per user
Key values
- postgres Main User
- 1,524 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 538 connections
- 1,524 Total connections
-
Sessions
Simultaneous sessions
Key values
- 12 sessions Session Peak
- 2026-02-15 06:54:00 Date
Histogram of session times
Key values
- 1,183 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 1,524 sessions Total
Sessions per user
Key values
- postgres Main User
- 1,524 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 1,524 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 110 35m58s 19s623ms 192.168.0.114 2 10m 5m 192.168.0.216 116 8m25s 4s360ms 192.168.0.74 16 1d1h53m27s 1h37m5s 192.168.1.145 2 299ms 149ms 192.168.1.20 21 9h53m36s 28m16s 192.168.1.239 56 314ms 5ms 192.168.1.90 6 67ms 11ms 192.168.2.126 18 5s195ms 288ms 192.168.3.199 39 31s788ms 815ms 192.168.4.142 538 7m37s 851ms 192.168.4.33 70 1m5s 929ms 192.168.4.98 330 20s798ms 63ms [local] 200 21m3s 6s315ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 2,397 buffers Checkpoint Peak
- 2026-02-15 06:06:39 Date
- 209.255 seconds Highest write time
- 0.643 seconds Sync time
Checkpoints Wal files
Key values
- 12 files Wal files usage Peak
- 2026-02-15 06:44:39 Date
Checkpoints distance
Key values
- 368.17 Mo Distance Peak
- 2026-02-15 06:44:39 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Feb 15 06 14,471 1,598.105s 0.695s 1,599.079s Day Hour Added Removed Recycled Synced files Longest sync Average sync Feb 15 06 0 0 21 1,368 0.398s 0.008s Day Hour Count Avg time (sec) Feb 15 06 0 0s Day Hour Mean distance Mean estimate Feb 15 06 28,913.67 kB 67,595.83 kB -
Temporary Files
Size of temporary files
Key values
- 105.23 MiB Temp Files size Peak
- 2026-02-15 06:02:18 Date
Number of temporary files
Key values
- 58 per second Temp Files Peak
- 2026-02-15 06:32:27 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Feb 15 06 644 2.90 GiB 4.61 MiB Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 60 272.30 MiB 4.50 MiB 4.60 MiB 4.54 MiB select resultuid from relevance_fibonacci_results order by resultuid desc limit ?), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp)))), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;-
SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4, $5, $6, $7, $8, $9, $10)) AND ($11 = 0 OR s.exchange in ($12)) AND ($13 = 0 OR coalesce(bim.code, s.symbol) in ($14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226, $227, $228, $229, $230, $231, $232, $233, $234, $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, $323)) AND ($324 = 0 OR fr.pattern in ($325)) AND ($326 = 0 OR fr.patternlengthbars <= $327) AND ($328 = 0 OR ($329 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($330 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $331 OR relevant = 1) AND ($332 = 0 OR age <= $333) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2026-02-15 06:00:46 Duration: 0ms
2 25 86.36 MiB 3.45 MiB 3.45 MiB 3.45 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: 2026-02-15 06:01:27 Duration: 0ms
3 24 74.39 MiB 3.10 MiB 3.10 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: 2026-02-15 06:02:08 Duration: 0ms
4 13 599.73 MiB 46.13 MiB 46.13 MiB 46.13 MiB update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2026-02-15 06:01:12 Duration: 0ms
5 13 1017.86 MiB 78.30 MiB 78.30 MiB 78.30 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2026-02-15 06:01:16 Duration: 0ms
6 4 559.47 MiB 139.86 MiB 139.87 MiB 139.87 MiB select updateresultsmaterializedview ();-
select updateresultsmaterializedview ();
Date: 2026-02-15 06:02:14 Duration: 0ms
7 4 357.20 MiB 89.30 MiB 89.30 MiB 89.30 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2026-02-15 06:02:05 Duration: 0ms
Queries generating the largest temporary files
Rank Size Query 1 139.87 MiB select updateresultsmaterializedview ();[ Date: 2026-02-15 06:47:31 ]
2 139.87 MiB select updateresultsmaterializedview ();[ Date: 2026-02-15 06:32:33 ]
3 139.87 MiB select updateresultsmaterializedview ();[ Date: 2026-02-15 06:17:37 ]
4 139.86 MiB select updateresultsmaterializedview ();[ Date: 2026-02-15 06:02:14 ]
5 89.30 MiB select updateageforrelevantresults ();[ Date: 2026-02-15 06:32:22 ]
6 89.30 MiB select updateageforrelevantresults ();[ Date: 2026-02-15 06:02:05 ]
7 89.30 MiB select updateageforrelevantresults ();[ Date: 2026-02-15 06:47:20 ]
8 89.30 MiB select updateageforrelevantresults ();[ Date: 2026-02-15 06:17:23 ]
9 78.30 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2026-02-15 06:01:16 ]
10 78.30 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2026-02-15 06:03:15 ]
11 78.30 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2026-02-15 06:19:32 ]
12 78.30 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2026-02-15 06:20:15 ]
13 78.30 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2026-02-15 06:26:16 ]
14 78.30 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2026-02-15 06:31:18 ]
15 78.30 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2026-02-15 06:33:17 ]
16 78.30 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2026-02-15 06:35:15 ]
17 78.30 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2026-02-15 06:41:17 ]
18 78.30 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2026-02-15 06:46:17 ]
19 78.30 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2026-02-15 06:48:15 ]
20 78.30 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2026-02-15 06:50:15 ]
-
Vacuums
Vacuums / Analyzes Distribution
Key values
- 0 sec Highest CPU-cost vacuum
Table
Database - Date
- 0 sec Highest CPU-cost analyze
Table
Database - Date
Analyzes per table
Key values
- public.solr_relevance_old (13) Main table analyzed (database acaweb_fx)
- 40 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 13 acaweb_fx.pg_catalog.pg_attribute 8 acaweb_fx.pg_catalog.pg_type 4 acaweb_fx.pg_catalog.pg_class 4 acaweb_fx.public.datafeeds_latestrun 3 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.pg_catalog.pg_depend 2 acaweb_fx.pg_catalog.pg_index 1 acaweb_fx.public.relevance_keylevels_results 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.relevance_fibonacci_results 1 Total 40 Vacuums per table
Key values
- public.solr_relevance_old (13) Main table vacuumed on database acaweb_fx
- 25 vacuums Total
Index Buffer usage Skipped WAL usage Table Vacuums scans hits misses dirtied pins frozen records full page bytes acaweb_fx.public.solr_relevance_old 13 13 10,991 0 45 0 0 8,420 13 1,465,902 acaweb_fx.pg_catalog.pg_attribute 3 3 2,963 0 362 0 201 1,210 360 2,049,286 acaweb_fx.pg_catalog.pg_type 2 2 329 0 40 0 0 141 31 161,006 acaweb_fx.public.datafeeds_latestrun 2 0 240 0 5 0 0 27 4 29,107 acaweb_fx.pg_catalog.pg_class 2 2 887 0 128 0 0 257 111 533,606 acaweb_fx.pg_catalog.pg_statistic 1 1 879 0 170 0 628 451 161 662,212 acaweb_fx.public.solr_imports 1 1 69 0 2 0 0 6 2 14,157 acaweb_fx.public.latest_t15_candle_view 1 1 67 0 1 0 0 6 1 9,055 Total 25 23 16,425 1,675 753 0 829 10,518 683 4,924,331 Tuples removed per table
Key values
- public.solr_relevance_old (75021) Main table with removed tuples on database acaweb_fx
- 82808 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 13 13 75,021 84,760 0 0 2,720 acaweb_fx.pg_catalog.pg_attribute 3 3 5,814 33,507 1,320 22 800 acaweb_fx.pg_catalog.pg_statistic 1 1 740 3,955 0 0 1,194 acaweb_fx.pg_catalog.pg_type 2 2 623 2,892 0 0 88 acaweb_fx.pg_catalog.pg_class 2 2 378 3,472 174 0 300 acaweb_fx.public.datafeeds_latestrun 2 0 122 28 0 0 32 acaweb_fx.public.latest_t15_candle_view 1 1 59 14 0 0 1 acaweb_fx.public.solr_imports 1 1 51 1 0 0 2 Total 25 23 82,808 128,629 1,494 22 5,137 Pages removed per table
Key values
- pg_catalog.pg_attribute (22) Main table with removed pages on database acaweb_fx
- 22 pages Total removed
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_catalog.pg_attribute 3 3 5814 22 acaweb_fx.pg_catalog.pg_type 2 2 623 0 acaweb_fx.public.datafeeds_latestrun 2 0 122 0 acaweb_fx.pg_catalog.pg_statistic 1 1 740 0 acaweb_fx.public.solr_imports 1 1 51 0 acaweb_fx.public.latest_t15_candle_view 1 1 59 0 acaweb_fx.pg_catalog.pg_class 2 2 378 0 acaweb_fx.public.solr_relevance_old 13 13 75021 0 Total 25 23 82,808 22 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Feb 15 06 25 40 - 0 sec Highest CPU-cost vacuum
-
Locks
Locks by types
Key values
- AccessShareLock Main Lock Type
- 11 locks Total
Most frequent waiting queries (N)
Rank Count Total time Min time Max time Avg duration Query 1 9 17m43s 1s53ms 2m25s 1m58s select datetimeupdate from latest_candle_datetime_per_receng where recognitionengine ilike ?;-
SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'HOTFOREX - 1';
Date: 2026-02-15 06:19:27
2 1 14m13s 14m13s 14m13s 14m13s truncate table solr_relevance_old;-
TRUNCATE TABLE solr_relevance_old;
Date: 2026-02-15 06:19:25
3 1 2m24s 2m24s 2m24s 2m24s refresh materialized view latest_candle_datetime_per_receng;-
refresh materialized view latest_candle_datetime_per_receng;
Date: 2026-02-15 06:19:25
Queries that waited the most
Rank Wait time Query 1 14m13s TRUNCATE TABLE solr_relevance_old;[ Date: 2026-02-15 06:19:25 ]
2 2m25s SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'IQFEED_FX - 1';[ Date: 2026-02-15 06:19:27 ]
3 2m24s refresh materialized view latest_candle_datetime_per_receng;[ Date: 2026-02-15 06:19:25 ]
4 2m20s SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'Alpari - 1';[ Date: 2026-02-15 06:19:27 ]
5 2m18s SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'FPMARKETS - 1';[ Date: 2026-02-15 06:19:27 ]
6 2m15s SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'HOTFOREX - 1';[ Date: 2026-02-15 06:19:27 ]
7 2m12s SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'AXIORY - 1';[ Date: 2026-02-15 06:19:27 ]
8 2m6s SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'ATFX - 1';[ Date: 2026-02-15 06:19:27 ]
9 2m1s SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'PEPPERSTONE - 1';[ Date: 2026-02-15 06:19:27 ]
10 2m SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'MILLENNIUMPF - 1';[ Date: 2026-02-15 06:19:27 ]
11 1s53ms SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'HOTFOREX - 1';[ Date: 2026-02-15 06:47:03 ]
-
Queries
Queries by type
Key values
- 22,955 Total read queries
- 16,342 Total write queries
Queries by database
Key values
- unknown Main database
- 82,585 Requests
- 2h55m49s (unknown)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 847 0ms copy from 65 0ms copy to 26 0ms cte 82 0ms ddl 13 0ms delete 13 0ms others 215 0ms select 65 0ms tcl 332 0ms update 36 0ms acaweb_fx_integer Total 1 0ms select 1 0ms postgres Total 3 0ms select 3 0ms socialmedia Total 71 0ms select 71 0ms translations Total 1 0ms select 1 0ms unknown Total 82,585 2h55m49s copy from 13 0ms copy to 575 0ms cte 2,078 0ms insert 12,312 0ms others 2,242 0ms select 22,814 0ms tcl 337 0ms update 460 0ms Queries by user
Key values
- unknown Main user
- 82,585 Requests
User Request type Count Duration postgres Total 923 0ms copy from 65 0ms copy to 26 0ms cte 82 0ms ddl 13 0ms delete 13 0ms others 215 0ms select 141 0ms tcl 332 0ms update 36 0ms unknown Total 82,585 2h55m49s copy from 13 0ms copy to 575 0ms cte 2,078 0ms insert 12,312 0ms others 2,242 0ms select 22,814 0ms tcl 337 0ms update 460 0ms Duration by user
Key values
- 2h55m49s (unknown) Main time consuming user
User Request type Count Duration postgres Total 923 0ms copy from 65 0ms copy to 26 0ms cte 82 0ms ddl 13 0ms delete 13 0ms others 215 0ms select 141 0ms tcl 332 0ms update 36 0ms unknown Total 82,585 2h55m49s copy from 13 0ms copy to 575 0ms cte 2,078 0ms insert 12,312 0ms others 2,242 0ms select 22,814 0ms tcl 337 0ms update 460 0ms Queries by host
Key values
- unknown Main host
- 83,508 Requests
- 2h55m49s (unknown)
- Main time consuming host
Queries by application
Key values
- unknown Main application
- 83,198 Requests
- 2h55m49s (unknown)
- Main time consuming application
Application Request type Count Duration pg_dump Total 5 0ms select 5 0ms psql Total 305 0ms copy from 65 0ms copy to 26 0ms cte 82 0ms ddl 13 0ms delete 13 0ms others 4 0ms select 66 0ms update 36 0ms unknown Total 83,198 2h55m49s copy from 13 0ms copy to 575 0ms cte 2,078 0ms insert 12,312 0ms others 2,453 0ms select 22,884 0ms tcl 669 0ms update 460 0ms Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2026-02-15 06:34:09 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 30,420 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 1 0ms 0ms 0ms lock table public.stats_hrs_summary_by_groups in access share mode;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Feb 15 06 1 0ms 0ms 2 0ms 2 0ms 0ms 0ms copy public.powerstats_trumpet (symbolid, dayofweek, fromtime, enddate, stddev_15, ave_15, stddev_30, ave_30, stddev_60, ave_60, stddev_240, ave_240, stddev_1440, ave_1440) to stdout;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 3 0ms 2 0ms 0ms 0ms select last_value, is_called from public.stats_by_groups_statsid_seq;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 4 0ms 2 0ms 0ms 0ms lock table public.timezones_korean in access share mode;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 5 0ms 12 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 #5
Day Hour Count Duration Avg duration Feb 15 06 12 0ms 0ms 6 0ms 2 0ms 0ms 0ms copy public.t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived, pricesadjusted, relevanceprocessed, recengprocessedadjusted, historical) to stdout;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 7 0ms 1 0ms 0ms 0ms copy public.processresults (id, processid, resultdate, shorttext, longtext, title, test) to stdout;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Feb 15 06 1 0ms 0ms 8 0ms 2,462 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 Feb 15 06 2,462 0ms 0ms 9 0ms 2 0ms 0ms 0ms select last_value, is_called from public.keylevels_results_resultuid_seq19;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 10 0ms 2 0ms 0ms 0ms copy archive.whatshot (whid, brokerid, whdatetime, jobcompletiontime) to stdout;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 11 0ms 5 0ms 0ms 0ms set synchronize_seqscans to off;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Feb 15 06 5 0ms 0ms 12 0ms 1 0ms 0ms 0ms select last_value, is_called from public."ProcessLocaleParameters_id_seq";Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Feb 15 06 1 0ms 0ms 13 0ms 975 0ms 0ms 0ms select oid, tableoid, pol.polname, pol.polcmd, pol.polpermissive, case when pol.polroles = ? then null else pg_catalog.array_to_string(array ( select pg_catalog.quote_ident(rolname) from pg_catalog.pg_roles where oid = any (pol.polroles)), ?) end as polroles, pg_catalog.pg_get_expr(pol.polqual, pol.polrelid) as polqual, pg_catalog.pg_get_expr(pol.polwithcheck, pol.polrelid) as polwithcheck from pg_catalog.pg_policy pol where polrelid = ?;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Feb 15 06 975 0ms 0ms 14 0ms 2 0ms 0ms 0ms lock table public.timezones_turkish in access share mode;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 15 0ms 2 0ms 0ms 0ms copy public.timezones_greek (timezoneid, timezone) to stdout;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 16 0ms 2 0ms 0ms 0ms lock table public.futures_symbols in access share mode;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 17 0ms 2 0ms 0ms 0ms copy archive.autochartist_results (resultid, bandwidth, pattern, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, qtytp, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, symbolid, resultuid, relevancestartdistance, simulation, writtendatetime, old_resultuid) to stdout;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 18 0ms 2 0ms 0ms 0ms copy public.satelliteauthentication (id, satelliteserverid, brokerid, authenticationstatus, maketradeurl, notifications, validusername, validpassword, enabled) to stdout;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 19 0ms 2 0ms 0ms 0ms lock table archive.patternresultsage in access share mode;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 20 0ms 1 0ms 0ms 0ms copy public.processes (id, locale, region, schedule, enabled, live, lastmodified, lastrun, contenttypeid, brokerid, uuid) to stdout;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Feb 15 06 1 0ms 0ms Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 3,824 0ms 0ms 0ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Feb 15 06 3,824 0ms 0ms 2 3,798 0ms 0ms 0ms 0ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Feb 15 06 3,798 0ms 0ms 3 2,799 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 #3
Day Hour Count Duration Avg duration Feb 15 06 2,799 0ms 0ms 4 2,470 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 #4
Day Hour Count Duration Avg duration Feb 15 06 2,470 0ms 0ms 5 2,462 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 #5
Day Hour Count Duration Avg duration Feb 15 06 2,462 0ms 0ms 6 1,714 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 #6
Day Hour Count Duration Avg duration Feb 15 06 1,714 0ms 0ms 7 1,663 0ms 0ms 0ms 0ms select pg_catalog.format_type(?::pg_catalog.oid, null);Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Feb 15 06 1,663 0ms 0ms 8 1,639 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 #8
Day Hour Count Duration Avg duration Feb 15 06 1,639 0ms 0ms 9 975 0ms 0ms 0ms 0ms select oid, tableoid, pol.polname, pol.polcmd, pol.polpermissive, case when pol.polroles = ? then null else pg_catalog.array_to_string(array ( select pg_catalog.quote_ident(rolname) from pg_catalog.pg_roles where oid = any (pol.polroles)), ?) end as polroles, pg_catalog.pg_get_expr(pol.polqual, pol.polrelid) as polqual, pg_catalog.pg_get_expr(pol.polwithcheck, pol.polrelid) as polwithcheck from pg_catalog.pg_policy pol where polrelid = ?;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Feb 15 06 975 0ms 0ms 10 943 0ms 0ms 0ms 0ms select datetimeupdate from latest_candle_datetime_per_receng where recognitionengine ilike ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Feb 15 06 943 0ms 0ms -
SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'HOTFOREX - 1';
Date: 2026-02-15 06:19:27 Duration: 0ms
11 785 0ms 0ms 0ms 0ms select a.attnum, a.attname, a.atttypmod, a.attstattarget, a.attstorage, t.typstorage, a.attnotnull, a.atthasdef, a.attisdropped, a.attlen, a.attalign, a.attislocal, pg_catalog.format_type(t.oid, a.atttypmod) as atttypname, a.attgenerated, case when a.atthasmissing and not a.attisdropped then a.attmissingval else null end as attmissingval, a.attidentity, pg_catalog.array_to_string(array ( select pg_catalog.quote_ident(option_name) || ? || pg_catalog.quote_literal(option_value) from pg_catalog.pg_options_to_table(attfdwoptions) order by option_name), e ?) as attfdwoptions, case when a.attcollation <> t.typcollation then a.attcollation else ? end as attcollation, array_to_string(a.attoptions, ?) as attoptions from pg_catalog.pg_attribute a left join pg_catalog.pg_type t on a.atttypid = t.oid where a.attrelid = ?::pg_catalog.oid and a.attnum > ?::pg_catalog.int2 order by a.attnum;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Feb 15 06 785 0ms 0ms 12 677 0ms 0ms 0ms 0ms select at.attname, ( select pg_catalog.array_agg(acl order by row_n) from ( select acl, row_n from pg_catalog.unnest(coalesce(at.attacl, pg_catalog.acldefault(?, c.relowner))) with ordinality as perm (acl, row_n) where not exists ( select ? from pg_catalog.unnest(coalesce(pip.initprivs, pg_catalog.acldefault(?, c.relowner))) as init (init_acl) where acl = init_acl)) as foo) as attacl, ( select pg_catalog.array_agg(acl order by row_n) from ( select acl, row_n from pg_catalog.unnest(coalesce(pip.initprivs, pg_catalog.acldefault(?, c.relowner))) with ordinality as initp (acl, row_n) where not exists ( select ? from pg_catalog.unnest(coalesce(at.attacl, pg_catalog.acldefault(?, c.relowner))) as permp (orig_acl) where acl = orig_acl)) as foo) as rattacl, null as initattacl, null as initrattacl from pg_catalog.pg_attribute at join pg_catalog.pg_class c on (at.attrelid = c.oid) left join pg_catalog.pg_init_privs pip on (at.attrelid = pip.objoid and pip.classoid = ?::pg_catalog.regclass and at.attnum = pip.objsubid) where at.attrelid = ?::pg_catalog.oid and not at.attisdropped and (( select pg_catalog.array_agg(acl order by row_n) from ( select acl, row_n from pg_catalog.unnest(coalesce(at.attacl, pg_catalog.acldefault(?, c.relowner))) with ordinality as perm (acl, row_n) where not exists ( select ? from pg_catalog.unnest(coalesce(pip.initprivs, pg_catalog.acldefault(?, c.relowner))) as init (init_acl) where acl = init_acl)) as foo) is not null or ( select pg_catalog.array_agg(acl order by row_n) from ( select acl, row_n from pg_catalog.unnest(coalesce(pip.initprivs, pg_catalog.acldefault(?, c.relowner))) with ordinality as initp (acl, row_n) where not exists ( select ? from pg_catalog.unnest(coalesce(at.attacl, pg_catalog.acldefault(?, c.relowner))) as permp (orig_acl) where acl = orig_acl)) as foo) is not null or null is not null or null is not null) order by at.attnum;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Feb 15 06 677 0ms 0ms 13 652 0ms 0ms 0ms 0ms select proretset, prosrc, probin, pg_catalog.pg_get_function_arguments(oid) as funcargs, pg_catalog.pg_get_function_identity_arguments(oid) as funciargs, pg_catalog.pg_get_function_result(oid) as funcresult, array_to_string(protrftypes, ?) as protrftypes, prokind, provolatile, proisstrict, prosecdef, proleakproof, proconfig, procost, prorows, prosupport, proparallel, ( select lanname from pg_catalog.pg_language where oid = prolang) as lanname from pg_catalog.pg_proc where oid = ?::pg_catalog.oid;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Feb 15 06 652 0ms 0ms 14 589 0ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Feb 15 06 589 0ms 0ms 15 577 0ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Feb 15 06 577 0ms 0ms 16 575 0ms 0ms 0ms 0ms select pr.tableoid, pr.oid, p.pubname from pg_publication_rel pr, pg_publication p where pr.prrelid = ? and p.oid = pr.prpubid;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Feb 15 06 575 0ms 0ms 17 494 0ms 0ms 0ms 0ms select t.tableoid, t.oid, t.relname as indexname, inh.inhparent as parentidx, pg_catalog.pg_get_indexdef(i.indexrelid) as indexdef, i.indnkeyatts as indnkeyatts, i.indnatts as indnatts, i.indkey, i.indisclustered, i.indisreplident, c.contype, c.conname, c.condeferrable, c.condeferred, c.tableoid as contableoid, c.oid as conoid, pg_catalog.pg_get_constraintdef(c.oid, false) as condef, ( select spcname from pg_catalog.pg_tablespace s where s.oid = t.reltablespace) as tablespace, t.reloptions as indreloptions, ( select pg_catalog.array_agg(attnum order by attnum) from pg_catalog.pg_attribute where attrelid = i.indexrelid and attstattarget >= ?) as indstatcols, ( select pg_catalog.array_agg(attstattarget order by attnum) from pg_catalog.pg_attribute where attrelid = i.indexrelid and attstattarget >= ?) as indstatvals from pg_catalog.pg_index i join pg_catalog.pg_class t on (t.oid = i.indexrelid) join pg_catalog.pg_class t2 on (t2.oid = i.indrelid) left join pg_catalog.pg_constraint c on (i.indrelid = c.conrelid and i.indexrelid = c.conindid and c.contype in (...)) left join pg_catalog.pg_inherits inh on (inh.inhrelid = indexrelid) where i.indrelid = ?::pg_catalog.oid and (i.indisvalid or t2.relkind = ?) and i.indisready order by indexname;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Feb 15 06 494 0ms 0ms 18 373 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 #18
Day Hour Count Duration Avg duration Feb 15 06 373 0ms 0ms 19 337 0ms 0ms 0ms 0ms begin;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Feb 15 06 337 0ms 0ms 20 332 0ms 0ms 0ms 0ms commit;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Feb 15 06 332 0ms 0ms Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 0ms 0ms 0ms 1 0ms lock table public.stats_hrs_summary_by_groups in access share mode;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Feb 15 06 1 0ms 0ms 2 0ms 0ms 0ms 2 0ms copy public.powerstats_trumpet (symbolid, dayofweek, fromtime, enddate, stddev_15, ave_15, stddev_30, ave_30, stddev_60, ave_60, stddev_240, ave_240, stddev_1440, ave_1440) to stdout;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 3 0ms 0ms 0ms 2 0ms select last_value, is_called from public.stats_by_groups_statsid_seq;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 4 0ms 0ms 0ms 2 0ms lock table public.timezones_korean in access share mode;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 5 0ms 0ms 0ms 12 0ms select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Feb 15 06 12 0ms 0ms 6 0ms 0ms 0ms 2 0ms copy public.t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived, pricesadjusted, relevanceprocessed, recengprocessedadjusted, historical) to stdout;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 7 0ms 0ms 0ms 1 0ms copy public.processresults (id, processid, resultdate, shorttext, longtext, title, test) to stdout;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Feb 15 06 1 0ms 0ms 8 0ms 0ms 0ms 2,462 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 Feb 15 06 2,462 0ms 0ms 9 0ms 0ms 0ms 2 0ms select last_value, is_called from public.keylevels_results_resultuid_seq19;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 10 0ms 0ms 0ms 2 0ms copy archive.whatshot (whid, brokerid, whdatetime, jobcompletiontime) to stdout;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 11 0ms 0ms 0ms 5 0ms set synchronize_seqscans to off;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Feb 15 06 5 0ms 0ms 12 0ms 0ms 0ms 1 0ms select last_value, is_called from public."ProcessLocaleParameters_id_seq";Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Feb 15 06 1 0ms 0ms 13 0ms 0ms 0ms 975 0ms select oid, tableoid, pol.polname, pol.polcmd, pol.polpermissive, case when pol.polroles = ? then null else pg_catalog.array_to_string(array ( select pg_catalog.quote_ident(rolname) from pg_catalog.pg_roles where oid = any (pol.polroles)), ?) end as polroles, pg_catalog.pg_get_expr(pol.polqual, pol.polrelid) as polqual, pg_catalog.pg_get_expr(pol.polwithcheck, pol.polrelid) as polwithcheck from pg_catalog.pg_policy pol where polrelid = ?;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Feb 15 06 975 0ms 0ms 14 0ms 0ms 0ms 2 0ms lock table public.timezones_turkish in access share mode;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 15 0ms 0ms 0ms 2 0ms copy public.timezones_greek (timezoneid, timezone) to stdout;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 16 0ms 0ms 0ms 2 0ms lock table public.futures_symbols in access share mode;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 17 0ms 0ms 0ms 2 0ms copy archive.autochartist_results (resultid, bandwidth, pattern, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, qtytp, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, symbolid, resultuid, relevancestartdistance, simulation, writtendatetime, old_resultuid) to stdout;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 18 0ms 0ms 0ms 2 0ms copy public.satelliteauthentication (id, satelliteserverid, brokerid, authenticationstatus, maketradeurl, notifications, validusername, validpassword, enabled) to stdout;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 19 0ms 0ms 0ms 2 0ms lock table archive.patternresultsage in access share mode;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Feb 15 06 2 0ms 0ms 20 0ms 0ms 0ms 1 0ms copy public.processes (id, locale, region, schedule, enabled, live, lastmodified, lastrun, contenttypeid, brokerid, uuid) to stdout;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Feb 15 06 1 0ms 0ms Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 781ms 471 0ms 21ms 1ms SELECT symbolid, ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Feb 15 06 471 781ms 1ms -
SELECT symbolid, ;
Date: 2026-02-15 06:15:56 Duration: 21ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-02-15 06:06:00 Duration: 7ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-02-15 06:10:25 Duration: 5ms Database: postgres
2 248ms 2,365 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 #2
Day Hour Count Duration Avg duration 06 2,365 248ms 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: 2026-02-15 06:11:50 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: 2026-02-15 06:11:38 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: 2026-02-15 06:10:29 Duration: 0ms Database: postgres
3 200ms 2,437 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 06 2,437 200ms 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: 2026-02-15 06:11:38 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: 2026-02-15 06:11:50 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: 2026-02-15 06:11:52 Duration: 0ms Database: postgres
4 132ms 118 0ms 3ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 06 118 132ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-15 06:16:43 Duration: 3ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-15 06:45:53 Duration: 1ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-15 06:46:01 Duration: 1ms Database: postgres
5 117ms 167 0ms 3ms 0ms WITH rar_max as ( ;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 06 167 117ms 0ms -
WITH rar_max as ( ;
Date: 2026-02-15 06:06:01 Duration: 3ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-02-15 06:50:39 Duration: 3ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-02-15 06:44:56 Duration: 2ms Database: postgres
6 89ms 430 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 #6
Day Hour Count Duration Avg duration 06 430 89ms 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: 2026-02-15 06:16:03 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: 2026-02-15 06:32:03 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: 2026-02-15 06:40:51 Duration: 0ms Database: postgres
7 86ms 589 0ms 0ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 06 589 86ms 0ms -
SET extra_float_digits = 3;
Date: 2026-02-15 06:10:53 Duration: 0ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-02-15 06:40:04 Duration: 0ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-02-15 06:17:23 Duration: 0ms Database: postgres
8 79ms 233 0ms 2ms 0ms SELECT ;Times Reported Time consuming prepare #8
Day Hour Count Duration Avg duration 06 233 79ms 0ms -
SELECT ;
Date: 2026-02-15 06:45:02 Duration: 2ms Database: postgres
-
SELECT ;
Date: 2026-02-15 06:45:03 Duration: 2ms Database: postgres
-
SELECT ;
Date: 2026-02-15 06:15:04 Duration: 2ms Database: postgres
9 50ms 18 2ms 4ms 2ms select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 06 18 50ms 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: 2026-02-15 06:10:02 Duration: 4ms 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: 2026-02-15 06:40:02 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: 2026-02-15 06:20:02 Duration: 3ms Database: postgres
10 15ms 140 0ms 0ms 0ms INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 06 140 15ms 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: 2026-02-15 06:15:19 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: 2026-02-15 06:17:19 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: 2026-02-15 06:47:26 Duration: 0ms Database: postgres
11 15ms 6 2ms 3ms 2ms select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 06 6 15ms 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: 2026-02-15 06:40:04 Duration: 3ms 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: 2026-02-15 06:10:04 Duration: 3ms 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: 2026-02-15 06:50:05 Duration: 2ms Database: postgres
12 13ms 108 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 #12
Day Hour Count Duration Avg duration 06 108 13ms 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: 2026-02-15 06:31:53 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: 2026-02-15 06:16:53 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: 2026-02-15 06:46:52 Duration: 0ms Database: postgres
13 7ms 577 0ms 0ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 06 577 7ms 0ms -
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-02-15 06:00:50 Duration: 0ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-02-15 06:46:01 Duration: 0ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-02-15 06:32:18 Duration: 0ms Database: postgres
14 6ms 3 0ms 4ms 2ms WITH last_candle AS ( ;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 06 3 6ms 2ms -
WITH last_candle AS ( ;
Date: 2026-02-15 06:52:01 Duration: 4ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-02-15 06:48:01 Duration: 2ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-02-15 06:56:01 Duration: 0ms Database: postgres
15 5ms 2 1ms 3ms 2ms select * from datafeed_symbols where classname ilike 'ICMARKETS-AU-MT5' limit 5000;Times Reported Time consuming prepare #15
Day Hour Count Duration Avg duration 06 2 5ms 2ms -
select * from datafeed_symbols where classname ilike 'ICMARKETS-AU-MT5' limit 5000;
Date: 2026-02-15 06:37:50 Duration: 3ms Database: postgres
-
select * from datafeed_symbols where classname ilike 'ICMARKETS-AU-MT5' limit 5000;
Date: 2026-02-15 06:07:47 Duration: 1ms Database: postgres
16 2ms 6 0ms 0ms 0ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 06 6 2ms 0ms -
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-02-15 06:08:07 Duration: 0ms Database: postgres
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-02-15 06:19:47 Duration: 0ms Database: postgres
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-02-15 06:17:02 Duration: 0ms Database: postgres
17 2ms 55 0ms 0ms 0ms select 1;Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 06 55 2ms 0ms -
select 1;
Date: 2026-02-15 06:52:01 Duration: 0ms Database: postgres
-
select 1;
Date: 2026-02-15 06:45:02 Duration: 0ms Database: postgres
-
select 1;
Date: 2026-02-15 06:45:16 Duration: 0ms Database: postgres
18 0ms 4 0ms 0ms 0ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 06 4 0ms 0ms -
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-02-15 06:23:18 Duration: 0ms Database: postgres
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-02-15 06:44:55 Duration: 0ms Database: postgres
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-02-15 06:44:55 Duration: 0ms Database: postgres
19 0ms 3 0ms 0ms 0ms SELECT DISTINCT ;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 06 3 0ms 0ms -
SELECT DISTINCT ;
Date: 2026-02-15 06:44:56 Duration: 0ms Database: postgres
-
SELECT DISTINCT ;
Date: 2026-02-15 06:43:37 Duration: 0ms Database: postgres
-
SELECT DISTINCT ;
Date: 2026-02-15 06:44:56 Duration: 0ms Database: postgres
20 0ms 2 0ms 0ms 0ms SELECT groupid, ;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 06 2 0ms 0ms -
SELECT groupid, ;
Date: 2026-02-15 06:44:55 Duration: 0ms Database: postgres
-
SELECT groupid, ;
Date: 2026-02-15 06:45:00 Duration: 0ms Database: postgres
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 13s550ms 1,267 0ms 60ms 10ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Feb 15 06 1,267 13s550ms 10ms -
WITH rar_max as ( ;
Date: 2026-02-15 06:22:01 Duration: 60ms Database: postgres parameters: $1 = 't', $2 = '621', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '1', $14 = 'EURUSD', $15 = '0', $16 = '', $17 = '0', $18 = '0', $19 = '0', $20 = '0', $21 = '0', $22 = 't', $23 = '10', $24 = '10'
-
WITH rar_max as ( ;
Date: 2026-02-15 06:45:49 Duration: 54ms Database: postgres parameters: $1 = 't', $2 = '621', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '1', $14 = 'EURUSD', $15 = '0', $16 = '', $17 = '0', $18 = '0', $19 = '0', $20 = '0', $21 = '0', $22 = 't', $23 = '10', $24 = '10'
-
WITH rar_max as ( ;
Date: 2026-02-15 06:06:42 Duration: 52ms 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'
2 1s330ms 3,878 0ms 19ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 06 3,878 1s330ms 0ms -
SELECT ;
Date: 2026-02-15 06:45:02 Duration: 19ms Database: postgres parameters: $1 = '500991628203869200'
-
SELECT ;
Date: 2026-02-15 06:45:02 Duration: 16ms Database: postgres parameters: $1 = '500991628203869200'
-
SELECT ;
Date: 2026-02-15 06:21:00 Duration: 6ms Database: postgres parameters: $1 = '607681495050804301', $2 = '607681495050804301', $3 = '607681495050804301'
3 1s286ms 471 1ms 18ms 2ms SELECT symbolid, ;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 06 471 1s286ms 2ms -
SELECT symbolid, ;
Date: 2026-02-15 06:10:25 Duration: 18ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '60', $3 = '#ADBE', $4 = '#BA', $5 = '#APPL', $6 = '#AMZN'
-
SELECT symbolid, ;
Date: 2026-02-15 06:10:51 Duration: 16ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '15', $3 = 'NAS100'
-
SELECT symbolid, ;
Date: 2026-02-15 06:17:11 Duration: 8ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'EURCAD.FX', $4 = 'EURCHF.FX', $5 = 'EURGBP', $6 = 'EURAUD.ID', $7 = 'EURCAD', $8 = 'EURCAD.ID', $9 = 'EURCHF.ID', $10 = 'EURCHF', $11 = 'EURAUD.FX'
4 437ms 45 4ms 39ms 9ms WITH last_candle AS ( ;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 06 45 437ms 9ms -
WITH last_candle AS ( ;
Date: 2026-02-15 06:36:00 Duration: 39ms Database: postgres parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2026-02-15 06:32:00 Duration: 25ms Database: postgres parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2026-02-15 06:12:00 Duration: 21ms Database: postgres parameters: $1 = '558', $2 = '558'
5 369ms 12 0ms 61ms 30ms with wh_patitioned as ( ;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 06 12 369ms 30ms -
with wh_patitioned as ( ;
Date: 2026-02-15 06:40:02 Duration: 61ms 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: 2026-02-15 06:10:02 Duration: 57ms 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: 2026-02-15 06:25:02 Duration: 43ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
6 233ms 25 0ms 19ms 9ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 06 25 233ms 9ms -
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-02-15 06:17:02 Duration: 19ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-02-15 06:35:29 Duration: 16ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-02-15 06:23:18 Duration: 12ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
7 205ms 118 1ms 2ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 06 118 205ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-15 06:07:20 Duration: 2ms Database: postgres parameters: $1 = 'PEPPERSTONEMT5'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-15 06:45:53 Duration: 2ms Database: postgres parameters: $1 = 'GLOBALGTMT5'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-15 06:16:43 Duration: 2ms Database: postgres parameters: $1 = 'AXIORY'
8 199ms 2,462 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 #8
Day Hour Count Duration Avg duration 06 2,462 199ms 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: 2026-02-15 06:11:50 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 17:00:00', $2 = '26484.7', $3 = '26558.5', $4 = '26447.5', $5 = '26526.3', $6 = '22942', $7 = '515840247933961300', $8 = '0', $9 = '2026-02-15 06:11:50.172', $10 = '2026-02-15 06:11:50.076', $11 = '26484.7', $12 = '26558.5', $13 = '26447.5', $14 = '26526.3', $15 = '22942', $16 = '0', $17 = '2026-02-15 06:11:50.172', $18 = '2026-02-15 06:11:50.076'
-
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: 2026-02-15 06:10:29 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 21:00:00', $2 = '110.51', $3 = '110.85', $4 = '110.02', $5 = '110.13', $6 = '4173', $7 = '515840247879403300', $8 = '0', $9 = '2026-02-15 06:10:29.535', $10 = '2026-02-15 06:10:29.432', $11 = '110.51', $12 = '110.85', $13 = '110.02', $14 = '110.13', $15 = '4173', $16 = '0', $17 = '2026-02-15 06:10:29.535', $18 = '2026-02-15 06:10:29.432'
-
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: 2026-02-15 06:10:37 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 20:00:00', $2 = '8960.4', $3 = '8968.9', $4 = '8954.9', $5 = '8962.4', $6 = '8875', $7 = '515840248015562300', $8 = '0', $9 = '2026-02-15 06:10:37.621', $10 = '2026-02-15 06:10:37.534', $11 = '8960.4', $12 = '8968.9', $13 = '8954.9', $14 = '8962.4', $15 = '8875', $16 = '0', $17 = '2026-02-15 06:10:37.621', $18 = '2026-02-15 06:10:37.534'
9 173ms 2,470 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 #9
Day Hour Count Duration Avg duration 06 2,470 173ms 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: 2026-02-15 06:07:18 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 22:30:00', $2 = '110.13', $3 = '110.7', $4 = '110.03', $5 = '110.645', $6 = '1344', $7 = '515840249427609300', $8 = '0', $9 = '2026-02-15 06:07:18.346', $10 = '2026-02-15 06:07:18.339', $11 = '110.13', $12 = '110.7', $13 = '110.03', $14 = '110.645', $15 = '1344', $16 = '0', $17 = '2026-02-15 06:07:18.346', $18 = '2026-02-15 06:07:18.339'
-
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: 2026-02-15 06:11:52 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 23:00:00', $2 = '24701.65', $3 = '24715.15', $4 = '24689.28', $5 = '24699.9', $6 = '9006', $7 = '515840248039147300', $8 = '0', $9 = '2026-02-15 06:11:52.193', $10 = '2026-02-15 06:11:52.113', $11 = '24701.65', $12 = '24715.15', $13 = '24689.28', $14 = '24699.9', $15 = '9006', $16 = '0', $17 = '2026-02-15 06:11:52.193', $18 = '2026-02-15 06:11:52.113'
-
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: 2026-02-15 06:11:38 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 21:00:00', $2 = '8962.55', $3 = '8964.95', $4 = '8953.4', $5 = '8956.5', $6 = '3960', $7 = '515840248015340300', $8 = '0', $9 = '2026-02-15 06:11:38.107', $10 = '2026-02-15 06:11:38.003', $11 = '8962.55', $12 = '8964.95', $13 = '8953.4', $14 = '8956.5', $15 = '3960', $16 = '0', $17 = '2026-02-15 06:11:38.107', $18 = '2026-02-15 06:11:38.003'
10 148ms 3,725 0ms 9ms 0ms select 1;Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 06 3,725 148ms 0ms -
select 1;
Date: 2026-02-15 06:06:10 Duration: 9ms Database: postgres
-
select 1;
Date: 2026-02-15 06:06:56 Duration: 6ms Database: postgres
-
select 1;
Date: 2026-02-15 06:10:48 Duration: 4ms Database: postgres
11 120ms 2,799 0ms 0ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #11
Day Hour Count Duration Avg duration 06 2,799 120ms 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: 2026-02-15 06:47:04 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 23:30:00', $2 = '7.46953', $3 = '7.46956', $4 = '7.46907', $5 = '7.46907', $6 = '49', $7 = '515840243190162300', $8 = '0', $9 = '2026-02-15 06:47:04.251', $10 = '2026-02-15 06:47:04.148', $11 = '7.46953', $12 = '7.46956', $13 = '7.46907', $14 = '7.46907', $15 = '49', $16 = '0', $17 = '2026-02-15 06:47:04.251', $18 = '2026-02-15 06:47:04.148'
-
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: 2026-02-15 06:16:03 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 23:30:00', $2 = '7.46953', $3 = '7.46956', $4 = '7.46907', $5 = '7.46907', $6 = '49', $7 = '515840243190162300', $8 = '0', $9 = '2026-02-15 06:16:03.049', $10 = '2026-02-15 06:16:02.981', $11 = '7.46953', $12 = '7.46956', $13 = '7.46907', $14 = '7.46907', $15 = '49', $16 = '0', $17 = '2026-02-15 06:16:03.049', $18 = '2026-02-15 06:16:02.981'
-
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: 2026-02-15 06:17:09 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 21:15:00', $2 = '8962.4', $3 = '8963.4', $4 = '8952.9', $5 = '8953.4', $6 = '185', $7 = '515840245910095300', $8 = '0', $9 = '2026-02-15 06:17:09.039', $10 = '2026-02-15 06:17:08.907', $11 = '8962.4', $12 = '8963.4', $13 = '8952.9', $14 = '8953.4', $15 = '185', $16 = '0', $17 = '2026-02-15 06:17:09.039', $18 = '2026-02-15 06:17:08.907'
12 38ms 65 0ms 7ms 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 #12
Day Hour Count Duration Avg duration 06 65 38ms 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: 2026-02-15 06:32:41 Duration: 7ms Database: postgres parameters: $1 = '607674180305476301'
-
/*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: 2026-02-15 06:14:36 Duration: 5ms Database: postgres parameters: $1 = '607674183011591301'
-
/*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: 2026-02-15 06:25:29 Duration: 4ms Database: postgres parameters: $1 = '607674179211631301'
13 19ms 87 0ms 0ms 0ms SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T15 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 06 87 19ms 0ms -
SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T15 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2026-02-15 06:55:17 Duration: 0ms Database: postgres parameters: $1 = '500991627555899200'
-
SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T15 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2026-02-15 06:20:34 Duration: 0ms Database: postgres parameters: $1 = '515840243238020300'
-
SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T15 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2026-02-15 06:25:29 Duration: 0ms Database: postgres parameters: $1 = '515840243870885300'
14 17ms 20 0ms 10ms 0ms /*server.FibonacciResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, Exchange AS e, longname as lo, shortname as sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, 1 - errormargin as rq, 1 - noise as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz 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 where resultuid = $1 and dtt.dayofweek = 3;Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 06 20 17ms 0ms -
/*server.FibonacciResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, Exchange AS e, longname as lo, shortname as sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, 1 - errormargin as rq, 1 - noise as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz 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 where resultuid = $1 and dtt.dayofweek = 3;
Date: 2026-02-15 06:20:34 Duration: 10ms Database: postgres parameters: $1 = '607674297870928302'
-
/*server.FibonacciResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, Exchange AS e, longname as lo, shortname as sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, 1 - errormargin as rq, 1 - noise as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz 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 where resultuid = $1 and dtt.dayofweek = 3;
Date: 2026-02-15 06:37:55 Duration: 2ms Database: postgres parameters: $1 = '607674127982294302'
-
/*server.FibonacciResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, Exchange AS e, longname as lo, shortname as sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, 1 - errormargin as rq, 1 - noise as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz 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 where resultuid = $1 and dtt.dayofweek = 3;
Date: 2026-02-15 06:06:03 Duration: 2ms Database: postgres parameters: $1 = '607680140470018302'
15 16ms 31 0ms 4ms 0ms /*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 06 31 16ms 0ms -
/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;
Date: 2026-02-15 06:34:09 Duration: 4ms Database: postgres parameters: $1 = '607673657094439303'
-
/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;
Date: 2026-02-15 06:05:37 Duration: 2ms Database: postgres parameters: $1 = '607673419017571303'
-
/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;
Date: 2026-02-15 06:22:43 Duration: 2ms Database: postgres parameters: $1 = '607674179945046303'
16 15ms 4 3ms 5ms 3ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 06 4 15ms 3ms -
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-02-15 06:23:18 Duration: 5ms Database: postgres parameters: $1 = '667', $2 = '667'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-02-15 06:51:03 Duration: 3ms Database: postgres parameters: $1 = '627', $2 = '627'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-02-15 06:44:55 Duration: 3ms Database: postgres parameters: $1 = '667', $2 = '667'
17 14ms 140 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 06 140 14ms 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: 2026-02-15 06:47:26 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 16:00:00', $2 = '57420', $3 = '57685', $4 = '57025', $5 = '57615', $6 = '6368', $7 = '515840230561612300', $8 = '0', $9 = '2026-02-15 06:47:26.982', $10 = '2026-02-15 06:47:26.981', $11 = '57420', $12 = '57685', $13 = '57025', $14 = '57615', $15 = '6368', $16 = '0', $17 = '2026-02-15 06:47:26.982', $18 = '2026-02-15 06:47:26.981'
-
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: 2026-02-15 06:17:19 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 16:00:00', $2 = '57420', $3 = '57685', $4 = '57025', $5 = '57615', $6 = '6368', $7 = '515840230561612300', $8 = '0', $9 = '2026-02-15 06:17:19.785', $10 = '2026-02-15 06:17:19.784', $11 = '57420', $12 = '57685', $13 = '57025', $14 = '57615', $15 = '6368', $16 = '0', $17 = '2026-02-15 06:17:19.785', $18 = '2026-02-15 06:17:19.784'
-
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: 2026-02-15 06:06:02 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 16:00:00', $2 = '57420', $3 = '57685', $4 = '57025', $5 = '57615', $6 = '6368', $7 = '515840230561612300', $8 = '0', $9 = '2026-02-15 06:06:02.386', $10 = '2026-02-15 06:06:02.386', $11 = '57420', $12 = '57685', $13 = '57025', $14 = '57615', $15 = '6368', $16 = '0', $17 = '2026-02-15 06:06:02.386', $18 = '2026-02-15 06:06:02.386'
18 13ms 18 0ms 0ms 0ms 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 bind #18
Day Hour Count Duration Avg duration 06 18 13ms 0ms -
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-02-15 06:11:01 Duration: 0ms Database: postgres
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select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-02-15 06:31:09 Duration: 0ms Database: postgres
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select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-02-15 06:11:01 Duration: 0ms Database: postgres
19 13ms 108 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 #19
Day Hour Count Duration Avg duration 06 108 13ms 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: 2026-02-15 06:15:50 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 00:00:00', $2 = '256.964', $3 = '269.783', $4 = '256.9295', $5 = '269.0435', $6 = '98967', $7 = '515840249404368300', $8 = '0', $9 = '2026-02-15 06:15:50.809', $10 = '2026-02-15 06:15:50.809', $11 = '256.964', $12 = '269.783', $13 = '256.9295', $14 = '269.0435', $15 = '98967', $16 = '0', $17 = '2026-02-15 06:15:50.809', $18 = '2026-02-15 06:15:50.809'
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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: 2026-02-15 06:46:54 Duration: 0ms Database: postgres parameters: $1 = '2026-02-14 00:00:00', $2 = '84.76705', $3 = '88.4503', $4 = '84.1759', $5 = '88.15435', $6 = '94524', $7 = '515840249476835300', $8 = '0', $9 = '2026-02-15 06:46:54.724', $10 = '2026-02-15 06:46:54.723', $11 = '84.76705', $12 = '88.4503', $13 = '84.1759', $14 = '88.15435', $15 = '94524', $16 = '0', $17 = '2026-02-15 06:46:54.724', $18 = '2026-02-15 06:46:54.723'
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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: 2026-02-15 06:16:51 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 00:00:00', $2 = '256.964', $3 = '269.783', $4 = '256.9295', $5 = '269.0435', $6 = '98967', $7 = '515840249404368300', $8 = '0', $9 = '2026-02-15 06:16:51.099', $10 = '2026-02-15 06:16:51.099', $11 = '256.964', $12 = '269.783', $13 = '256.9295', $14 = '269.0435', $15 = '98967', $16 = '0', $17 = '2026-02-15 06:16:51.099', $18 = '2026-02-15 06:16:51.099'
20 9ms 109 0ms 1ms 0ms SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 06 109 9ms 0ms -
SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2026-02-15 06:20:34 Duration: 1ms Database: postgres parameters: $1 = '515840243238020300'
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2026-02-15 06:55:17 Duration: 1ms Database: postgres parameters: $1 = '500991627555899200'
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SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;
Date: 2026-02-15 06:25:29 Duration: 0ms Database: postgres parameters: $1 = '515840243870885300'
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Events
Log levels
Key values
- 145,085 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 14 ERROR entries
- 0 WARNING entries
Most Frequent Errors/Events
Key values
- 12 Max number of times the same event was reported
- 14 Total events found
Rank Times reported Error 1 12 LOG: process ... still waiting for AccessShareLock on relation ... of database ... after ... ms
Times Reported Most Frequent Error / Event #1
Day Hour Count Feb 15 06 12 - LOG: process 19022 still waiting for AccessShareLock on relation 5894441 of database 5881926 after 1000.055 ms at character 28
- LOG: process 18036 still waiting for AccessShareLock on relation 5894441 of database 5881926 after 1000.054 ms at character 28
- LOG: process 19216 still waiting for AccessShareLock on relation 5894441 of database 5881926 after 1000.058 ms at character 28
Detail: Process holding the lock: 28884. Wait queue: 32125, 19022.
Statement: SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'IQFEED_FX - 1'Date: 2026-02-15 06:17:02
Detail: Process holding the lock: 28884. Wait queue: 32125, 19022, 18036.
Statement: SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'Alpari - 1'Date: 2026-02-15 06:17:07
Detail: Process holding the lock: 28884. Wait queue: 32125, 19022, 18036, 19216.
Statement: SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'FPMARKETS - 1'Date: 2026-02-15 06:17:09
2 2 LOG: process ... still waiting for AccessExclusiveLock on relation ... of database ... after ... ms
Times Reported Most Frequent Error / Event #2
Day Hour Count Feb 15 06 2 - LOG: process 28904 still waiting for AccessExclusiveLock on relation 5883477 of database 5881926 after 1000.047 ms
- LOG: process 32125 still waiting for AccessExclusiveLock on relation 5894441 of database 5881926 after 1000.051 ms
Detail: Process holding the lock: 28884. Wait queue: 28904.
Statement: TRUNCATE TABLE solr_relevance_old;Date: 2026-02-15 06:05:12
Detail: Process holding the lock: 28884. Wait queue: 32125, 19022.
Statement: refresh materialized view latest_candle_datetime_per_recengDate: 2026-02-15 06:17:02