pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Sun Feb 8 07:59:26 2026
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-02-08_090000.log
Parsed 915,949 log entries in 25s
Log start from 2026-02-08 09:00:00 to 2026-02-08 09:59:18

Global Stats

176 Number of unique normalized queries
122,532 Number of queries
1h1m31s Total query duration
2026-02-08 09:00:00 First query
2026-02-08 09:59:18 Last query
4,154 queries/s at 2026-02-08 09:00:50 Query peak

1h1m31s Total query duration
2s524ms Prepare/parse total duration
19s523ms Bind total duration
1h1m9s Execute total duration

0 Number of events
0 Number of unique normalized events
0 Max number of times the same event was reported
0 Number of cancellation

28 Total number of automatic vacuums
45 Total number of automatic analyzes

456 Number temporary file
142.17 MiB Max size of temporary file
6.37 MiB Average size of temporary file

1,768 Total number of sessions
12 sessions at 2026-02-08 09:51:36 Session peak
23d20h23m50s Total duration of sessions
19m25s Average duration of sessions
69 Average queries per session
2s87ms Average queries duration per session
19m23s Average idle time per session

1,765 Total number of connections
28 connections/s at 2026-02-08 09:33:48 Connection peak
3 Total number of databases

SQL Traffic

Key values

4,154 queries/s Query Peak
2026-02-08 09:00:50 Date

SELECT Traffic

Key values

2,043 queries/s Query Peak
2026-02-08 09:00:50 Date

INSERT/UPDATE/DELETE Traffic

Key values

139 queries/s Query Peak
2026-02-08 09:10:49 Date

Queries duration

Key values

1h1m31s 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

Day	Hour	Count	Min duration	Max duration	Avg duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Feb 08	09	122,532	0ms	31s69ms	29ms	2m55s	3m22s	3m29s

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Feb 08	09	40,497	26	0ms	0ms	0ms	0ms

Day	Hour	INSERT	UPDATE	DELETE	COPY FROM	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Feb 08	09	15,244	588	16	96	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Feb 08	09	10,055	43,749	4.35	17.03%

Day	Hour	Count	Average / Second
Feb 08	09	1,765	0.49/s

Day	Hour	Count	Average Duration	Average idle time
Feb 08	09	1,768	19m25s	19m23s

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Established Connections

Key values

28 connections Connection Peak
2026-02-08 09:33:48 Date

Connections per database

Key values

acaweb_fx Main Database
1,765 connections Total

Chart
Table

Database	User	Count
acaweb_fx		1,675
	postgres	1,332
	psql	343
socialmedia		90
	postgres	90

Connections per user

Key values

postgres Main User
1,765 connections Total

Chart
Table

User	Count
postgres	1,422
psql	343

Connections per host

Key values

192.168.4.142 Main host with 674 connections
1,765 Total connections

Chart
Table

Host	Count
127.0.0.1	107
182.165.1.54	2
192.168.0.114	2
192.168.0.216	116
192.168.0.74	23
192.168.0.84	2
192.168.1.131	2
192.168.1.145	14
192.168.1.15	11
192.168.1.20	34
192.168.1.201	1
192.168.1.238	2
192.168.1.239	56
192.168.1.90	6
192.168.2.126	18
192.168.3.199	39
192.168.4.142	674
192.168.4.33	90
192.168.4.98	330
[local]	236

Simultaneous sessions

Key values

12 sessions Session Peak
2026-02-08 09:51:36 Date

Histogram of session times

Key values

1,326 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	1,326	75.00%
500ms-1s	135	7.64%
1s-30s	239	13.52%
30s-1m	8	0.45%
1m-10m	4	0.23%
10m-30m	21	1.19%
30m-1h	1	0.06%
1h-8h	9	0.51%
> 8h	25	1.41%

Sessions per database

Key values

acaweb_fx Main Database
1,768 sessions Total

Chart
Table

Database	User	Count	Total Duration	Average Duration
acaweb_fx	1,678	23d20h22m10s	20m27s
socialmedia	90	1m39s	1s105ms

Sessions per user

Key values

postgres Main User
1,768 sessions Total

Chart
Table

User	Count	Total Duration	Average Duration
postgres	1	0ms	0ms

Sessions per host

Key values

192.168.4.142 Main Host
1,768 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
127.0.0.1	107	3s893ms	36ms
182.165.1.54	2	23h16m1s	11h38m
192.168.0.114	2	10m	5m
192.168.0.216	116	7m5s	3s666ms
192.168.0.74	25	5d1h17m29s	4h51m5s
192.168.0.84	2	23h59m33s	11h59m46s
192.168.1.131	2	23h59m31s	11h59m45s
192.168.1.145	15	5d5h16m5s	8h21m4s
192.168.1.15	11	3d22h31m14s	8h35m34s
192.168.1.20	35	5d15h34m13s	3h52m24s
192.168.1.238	2	23h59m29s	11h59m44s
192.168.1.239	56	318ms	5ms
192.168.1.90	6	76ms	12ms
192.168.2.126	18	5s462ms	303ms
192.168.3.199	39	31s759ms	814ms
192.168.4.142	674	7m21s	654ms
192.168.4.33	90	1m39s	1s105ms
192.168.4.98	330	13s440ms	40ms
[local]	236	3m10s	806ms

Sessions per application

Key values

unknown Main Host
1,768 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	1,768	23d20h23m50s	19m25s

Checkpoints Buffers

Key values

2,373 buffers Checkpoint Peak
2026-02-08 09:05:14 Date
209.959 seconds Highest write time
0.175 seconds Sync time

Checkpoints Wal files

Key values

2 files Wal files usage Peak
2026-02-08 09:05:14 Date

Checkpoints distance

Key values

44.80 Mo Distance Peak
2026-02-08 09:09:52 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Feb 08	09	17,256	1,747.81s	0.376s	1,748.43s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Feb 08	09	0	0	11	1,297	0.174s	0.002s

Day	Hour	Count	Avg time (sec)
Feb 08	09	0	0s

Day	Hour	Mean distance	Mean estimate
Feb 08	09	15,075.33 kB	21,611.75 kB

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Checkpoint causes

Key values

time (12) Main checkpoint cause
12 checkpoints Total

Chart
Table

Cause	Number of checkpoints
time	12
Total	12

Size of temporary files

Key values

100.45 MiB Temp Files size Peak
2026-02-08 09:17:19 Date

Number of temporary files

Key values

30 per second Temp Files Peak
2026-02-08 09:17:09 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Feb 08	09	456	2.84 GiB	6.37 MiB

↑ Back to the top of the Temporary Files Activity table

Queries generating the most temporary files (N)

Rank	Count	Total size	Min size	Max size	Avg size	Query
1	38	173.12 MiB	4.52 MiB	4.58 MiB	4.56 MiB	select resultuid from relevance_fibonacci_results order by resultuid desc limit ?), fr as ( select a., rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp)))), results as ( select distinct on (symbolid) from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc; SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1), fr AS ( SELECT a., rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4, $5, $6, $7, $8, $9, $10)) AND ($11 = 0 OR s.exchange in ($12)) AND ($13 = 0 OR coalesce(bim.code, s.symbol) in ($14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226, $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: 2026-02-08 09:00:46 Duration: 0ms
2	16	619.88 MiB	38.74 MiB	38.74 MiB	38.74 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: 2026-02-08 09:01:12 Duration: 0ms
3	16	49.75 MiB	3.05 MiB	3.28 MiB	3.11 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: 2026-02-08 09:01:04 Duration: 0ms
4	16	1.11 GiB	71.12 MiB	71.12 MiB	71.12 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: 2026-02-08 09:01:15 Duration: 0ms
5	4	568.69 MiB	142.17 MiB	142.17 MiB	142.17 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2026-02-08 09:02:15 Duration: 0ms
6	4	347.46 MiB	86.86 MiB	86.87 MiB	86.86 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2026-02-08 09:02:05 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	142.17 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-08 09:17:15 ]
2	142.17 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-08 09:32:14 ]
3	142.17 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-08 09:47:14 ]
4	142.17 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-08 09:02:15 ]
5	86.87 MiB	select updateageforrelevantresults (); [ Date: 2026-02-08 09:02:05 ]
6	86.87 MiB	select updateageforrelevantresults (); [ Date: 2026-02-08 09:32:05 ]
7	86.86 MiB	select updateageforrelevantresults (); [ Date: 2026-02-08 09:47:04 ]
8	86.86 MiB	select updateageforrelevantresults (); [ Date: 2026-02-08 09:17:05 ]
9	71.12 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: 2026-02-08 09:01:15 ]
10	71.12 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: 2026-02-08 09:03:15 ]
11	71.12 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: 2026-02-08 09:05:15 ]
12	71.12 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: 2026-02-08 09:11:15 ]
13	71.12 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: 2026-02-08 09:16:15 ]
14	71.12 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: 2026-02-08 09:18:16 ]
15	71.12 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: 2026-02-08 09:20:15 ]
16	71.12 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: 2026-02-08 09:26:16 ]
17	71.12 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: 2026-02-08 09:31:15 ]
18	71.12 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: 2026-02-08 09:33:15 ]
19	71.12 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: 2026-02-08 09:35:16 ]
20	71.12 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: 2026-02-08 09:41:15 ]

Vacuums / Analyzes Distribution

Key values

0 sec Highest CPU-cost vacuum
Table
Database
Date
0 sec Highest CPU-cost analyze
Table
Database
Date

Analyzes per table

Key values

public.solr_relevance_old (16) Main table analyzed (database acaweb_fx)
45 analyzes Total

Chart
Table

Table	Number of analyzes
acaweb_fx.public.solr_relevance_old	16
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.solr_imports	1
acaweb_fx.public.relevance_keylevels_results	1
acaweb_fx.public.relevance_autochartist_results	1
acaweb_fx.public.latest_candle_datetime_per_receng	1
acaweb_fx.public.relevance_fibonacci_results	1
Total	45

Vacuums per table

Key values

public.solr_relevance_old (16) Main table vacuumed on database acaweb_fx
28 vacuums Total

Chart
Table

		Index	Buffer usage			Skipped		WAL usage
Table	Vacuums	scans	hits	misses	dirtied	pins	frozen	records	full page	bytes
acaweb_fx.public.solr_relevance_old	16	16	11,213	0	48	0	0	7,755	16	1,458,235
acaweb_fx.pg_catalog.pg_attribute	3	3	3,579	0	407	0	201	1,191	405	2,457,496
acaweb_fx.pg_catalog.pg_type	2	2	475	0	34	0	0	147	32	190,254
acaweb_fx.public.datafeeds_latestrun	2	0	246	0	3	0	0	26	3	22,860
acaweb_fx.pg_catalog.pg_class	2	2	1,114	0	88	0	0	252	89	497,285
acaweb_fx.pg_toast.pg_toast_2619	1	1	216	0	32	0	0	112	32	129,603
acaweb_fx.pg_catalog.pg_depend	1	1	585	0	73	0	59	165	69	336,199
acaweb_fx.public.latest_t15_candle_view	1	1	67	0	1	0	0	6	1	9,055
Total	28	26	17,495	662	686	0	260	9,654	647	5,100,987

Tuples removed per table

Key values

public.solr_relevance_old (49722) Main table with removed tuples on database acaweb_fx
56709 tuples Total removed

Chart
Table

		Index	Tuples			Pages
Table	Vacuums	scans	removed	remain	not yet removable	removed	remain
acaweb_fx.public.solr_relevance_old	16	16	49,722	85,335	0	0	2,697
acaweb_fx.pg_catalog.pg_attribute	3	3	5,690	32,386	0	26	770
acaweb_fx.pg_catalog.pg_type	2	2	732	2,892	0	8	78
acaweb_fx.pg_catalog.pg_class	2	2	172	3,298	0	0	300
acaweb_fx.pg_catalog.pg_depend	1	1	135	14,410	0	0	140
acaweb_fx.public.datafeeds_latestrun	2	0	122	28	0	0	32
acaweb_fx.pg_toast.pg_toast_2619	1	1	77	167	0	0	53
acaweb_fx.public.latest_t15_candle_view	1	1	59	14	0	0	1
Total	28	26	56,709	138,530	0	34	4,071

Pages removed per table

Key values

pg_catalog.pg_attribute (26) Main table with removed pages on database acaweb_fx
34 pages Total removed

Chart
Table

Table	Number of vacuums	Index scans	Tuples removed	Pages removed
acaweb_fx.pg_catalog.pg_attribute	3	3	5690	26
acaweb_fx.pg_catalog.pg_type	2	2	732	8
acaweb_fx.pg_toast.pg_toast_2619	1	1	77	0
acaweb_fx.public.datafeeds_latestrun	2	0	122	0
acaweb_fx.pg_catalog.pg_depend	1	1	135	0
acaweb_fx.public.latest_t15_candle_view	1	1	59	0
acaweb_fx.public.solr_relevance_old	16	16	49722	0
acaweb_fx.pg_catalog.pg_class	2	2	172	0
Total	28	26	56,709	34

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Feb 08	09	28	45

↑ Back to the top of the Autovacuum Activity table

Locks by types

Key values

unknown Main Lock Type
0 locks Total

Chart
Table

Type of locks

NO DATASET

Type	Object	Count	Total Duration	Average Duration (s)
NO DATASET

Most frequent waiting queries (N)

Rank	Count	Total time	Min time	Max time	Avg duration	Query
NO DATASET

Queries that waited the most

Rank	Wait time	Query
NO DATASET

Queries by type

Key values

40,497 Total read queries
18,554 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	40,497	33.05%
INSERT	15,244	12.44%
UPDATE	588	0.48%
DELETE	16	0.01%
COPY FROM	96	0.08%
COPY TO	26	0.02%
CTE	1,904	1.55%
DDL	16	0.01%
TCL	664	0.54%
CURSOR	0	0.00%
OTHERS	63,481	51.81%

Queries by database

Key values

unknown Main database
121,556 Requests
1h1m9s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	886	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	100	0ms
	ddl	16	0ms
	delete	16	0ms
	others	215	0ms
	select	64	0ms
	tcl	332	0ms
	update	37	0ms
socialmedia	Total	90	0ms
	select	90	0ms
unknown	Total	121,556	1h1m9s
	copy from	16	0ms
	cte	1,804	0ms
	insert	15,244	0ms
	others	1,999	0ms
	select	40,343	0ms
	tcl	332	0ms
	update	551	0ms

Queries by user

Key values

unknown Main user
121,556 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	976	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	100	0ms
	ddl	16	0ms
	delete	16	0ms
	others	215	0ms
	select	154	0ms
	tcl	332	0ms
	update	37	0ms
unknown	Total	121,556	1h1m9s
	copy from	16	0ms
	cte	1,804	0ms
	insert	15,244	0ms
	others	1,999	0ms
	select	40,343	0ms
	tcl	332	0ms
	update	551	0ms

Duration by user

Key values

1h1m9s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	976	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	100	0ms
	ddl	16	0ms
	delete	16	0ms
	others	215	0ms
	select	154	0ms
	tcl	332	0ms
	update	37	0ms
unknown	Total	121,556	1h1m9s
	copy from	16	0ms
	cte	1,804	0ms
	insert	15,244	0ms
	others	1,999	0ms
	select	40,343	0ms
	tcl	332	0ms
	update	551	0ms

Queries by host

Key values

unknown Main host
122,532 Requests
1h1m9s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	122,532	1h1m9s
	copy from	96	0ms
	copy to	26	0ms
	cte	1,904	0ms
	ddl	16	0ms
	delete	16	0ms
	insert	15,244	0ms
	others	2,214	0ms
	select	40,497	0ms
	tcl	664	0ms
	update	588	0ms

Queries by application

Key values

unknown Main application
122,189 Requests
1h1m9s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
psql	Total	343	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	100	0ms
	ddl	16	0ms
	delete	16	0ms
	others	4	0ms
	select	64	0ms
	update	37	0ms
unknown	Total	122,189	1h1m9s
	copy from	16	0ms
	cte	1,804	0ms
	insert	15,244	0ms
	others	2,210	0ms
	select	40,433	0ms
	tcl	664	0ms
	update	551	0ms

Number of cancelled queries

Key values

0 per second Cancelled query Peak
2026-02-08 09:45:09 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

47,817 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	47,817	78.05%
1-5ms	11,654	19.02%
5-10ms	238	0.39%
10-25ms	423	0.69%
25-50ms	165	0.27%
50-100ms	117	0.19%
100-500ms	265	0.43%
500-1000ms	43	0.07%
1000-10000ms	432	0.71%
> 10000ms	113	0.18%

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

38

Details

0ms

select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 08	09	38	0ms	0ms

2

0ms

124

Details

0ms

with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Feb 08	09	124	0ms	0ms

3

0ms

2

Details

0ms

with rar_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ) select bmr.symbolid, patternstarttime, patternendtime, timegranularity, ? as direction, case when bmr.old_resultuid = ? then bmr.old_resultuid else bmr.resultuid end as uid, s.exchange, s.symbol, s.longname, s.shortname, dtt.timezone, bmr.patternmovement, bmr.statisticalmovement, bmr.fromprice, bmr.toprice, bmr.percentile, bmr.patternlengthbars, case when rbr.age is not null then rbr.age when bmr.resultuid <= rm.resultuid then ? else ? end as age, case when rbr.relevant is not null then rbr.relevant when bmr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from bigmovement_results bmr inner join downloadersymbolsettings dss on bmr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on bmr.symbolid = s.symbolid inner join rar_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid left join currencypips cps on cps.symbol = s.symbol where (bmr.old_resultuid = ? or bmr.resultuid = ?) and dtt.dayofweek = ?;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Feb 08	09	2	0ms	0ms

4

0ms

2,404

Details

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 #4

Day	Hour	Count	Duration	Avg duration
Feb 08	09	2,404	0ms	0ms

5

0ms

142

Details

0ms

select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, timegranularity as interval, direction as direction, patternendtime as patternendtime, patternstartprice as psp, patternendprice as pep, target03 as t03, target16 as t16, patternlengthbars as length, p.patternname as patternname, dtt.timezone, cps.pip from fibonacci_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join fibonaccipatterns p on a.pattern = p.patternname left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Feb 08	09	142	0ms	0ms

6

0ms

110

Details

0ms

update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Feb 08	09	110	0ms	0ms

7

0ms

1

Details

0ms

insert into resultmedia (processresultsid, type, name, filename) values (?, ?, ?, ?) returning id;

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Feb 08	09	1	0ms	0ms

8

0ms

18

Details

0ms

select cast(count(*) / cast(setting as numeric) * ? as int) from pg_stat_activity, pg_settings where name = ? group by setting;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Feb 08	09	18	0ms	0ms

9

0ms

238

Details

0ms

select v.datname, c.relname, v.phase, v.heap_blks_total, v.heap_blks_scanned, v.heap_blks_vacuumed, v.index_vacuum_count, v.max_dead_tuples, v.num_dead_tuples from pg_stat_progress_vacuum as v join pg_class c on c.oid = v.relid;

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Feb 08	09	238	0ms	0ms

10

0ms

203

Details

0ms

select distinct s.statsid as statsid, sy.exchange as name from stats s inner join broker b on s.brokerid = b.brokerid inner join brokerconfig bc on b.brokerid = bc.brokerid inner join stats_symbols ss on s.statsid = ss.statsid inner join downloadersymbolsettings dss on ss.symbolid = dss.symbolid inner join symbols sy on dss.symbolid = sy.symbolid where dss.enabled = ? and s.brokerid is not null and b.brokerid = ? and s.groupingtype ilike ? and s.description ilike ? || b.name || ? and s.description ilike ? || sy.exchange || ? and s.description not ilike ? || ? || ? union all select distinct s.statsid as statsid, basegroupname as name from stats s inner join broker b on s.brokerid = b.brokerid inner join brokerconfig bc on b.brokerid = bc.brokerid inner join stats_symbols ss on s.statsid = ss.statsid inner join downloadersymbolsettings dss on ss.symbolid = dss.symbolid inner join symbolgroup sg on dss.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bg.brokerid = b.brokerid where dss.enabled = ? and s.brokerid is not null and b.brokerid = ? and s.groupingtype not ilike ? and s.description ilike ? || b.name || ? and s.description ilike ? || g.basegroupname || ? and s.description not ilike ? || ? || ?;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Feb 08	09	203	0ms	0ms

11

0ms

462

Details

0ms

select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) and name in (...) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) and name in (...) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 08	09	462	0ms	0ms

12

0ms

7

Details

0ms

select * from ( select pricedatetime, open, high, low, close, volume, bsf from t60 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Feb 08	09	7	0ms	0ms

13

0ms

332

Details

0ms

commit;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Feb 08	09	332	0ms	0ms

14

0ms

188

Details

0ms

with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 08	09	188	0ms	0ms

15

0ms

3

Details

0ms

select psd.symbolid, psd.hourlysymbolid as intervalsymbolid, s.symbol, dtt.timezone, dtt.absolutetimezoneoffset, psh.hour as index, psh.ave, psh.stddev, ((psh.ave - psh.stddev) / ?.?) as low, ((psh.ave + psh.stddev) / ?.?) as high, ee.timezone as exchangetimezone, ee.mon_t1start as exchangestart, ee.mon_t1end as exchangeend from powerstats_symboldata psd inner join powerstats_hourly psh on psd.hourlysymbolid = psh.symbolid inner join symbols s on psh.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join mat_ps_hourly_symbolid_max_enddate e on psh.enddate = e.enddate and psh.symbolid = e.symbolid inner join exchanges ee on ee.exchange = s.exchange where psd.symbolid = ? and dtt.dayofweek = ? order by hour asc;

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Feb 08	09	3	0ms	0ms

16

0ms

1

Details

0ms

select (cast(substring(tz.gmoffset from ? for ?) as float) * ? + cast(substring(tz.gmoffset from ? for ?) as float)) / ? as offset from timezones tz where tz.timezone = ?;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 08	09	1	0ms	0ms

17

0ms

238

Details

0ms

select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Feb 08	09	238	0ms	0ms

18

0ms

11

Details

0ms

select * from ( select pricedatetime, open, high, low, close, volume, bsf from t30 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 08	09	11	0ms	0ms

19

0ms

6

Details

0ms

select pid, datname, client_addr from pg_stat_activity where query ilike ? and pid <> pg_backend_pid() and state = ? and datname = ?;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 08	09	6	0ms	0ms

20

0ms

30

Details

0ms

update executions set isrunning = false, has_results = false, response = ? where id = ?;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 08	09	30	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

15,926

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 08	09	15,926	0ms	0ms

2

6,552

Details

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 08	09	6,552	0ms	0ms

3

5,082

Details

0ms

select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Feb 08	09	5,082	0ms	0ms

4

2,813

Details

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 #4

Day	Hour	Count	Duration	Avg duration
Feb 08	09	2,813	0ms	0ms

5

2,772

Details

0ms

select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Feb 08	09	2,772	0ms	0ms

6

2,436

Details

0ms

insert into t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Feb 08	09	2,436	0ms	0ms

7

2,404

Details

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 #7

Day	Hour	Count	Duration	Avg duration
Feb 08	09	2,404	0ms	0ms

8

1,884

Details

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 #8

Day	Hour	Count	Duration	Avg duration
Feb 08	09	1,884	0ms	0ms

9

1,796

Details

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 #9

Day	Hour	Count	Duration	Avg duration
Feb 08	09	1,796	0ms	0ms

10

974

Details

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 08	09	974	0ms	0ms

11

777

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 08	09	777	0ms	0ms

12

765

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Feb 08	09	765	0ms	0ms

13

688

Details

0ms

select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars as length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternstartprice, resy1, supporty1, dtt.timezone, cps.pip, newlevels.profit from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern left join currencypips cps on cps.symbol = s.symbol left join lateral calc_cp_signal (a.resultuid) newlevels on true where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Feb 08	09	688	0ms	0ms

14

495

Details

0ms

select symbolid, pricedatetime, classname, downloadfrequency, downloadersymbol, open, high, low, close, volume, bsf, sastdatetimereceived from ( select pricedatetime, dss.classname, dss.downloadfrequency, dss.symbolid, dss.downloadersymbol, t.open, t.high, t.low, t.close, t.volume, t.bsf, t.sastdatetimereceived, row_number() over (partition by t.symbolid order by t.pricedatetime desc) as rn from t15 t, downloadersymbolsettings dss, symbols s where dss.classname = ? and dss.downloadfrequency = ? and dss.symbolid = t.symbolid and s.symbolid = dss.symbolid and dss.enabled = ? and s.deleted = ? and dss.downloadersymbol in (...) and t.pricedatetime > now() - interval ?) as ranked_candles_table where rn = ?;

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 08	09	495	0ms	0ms

15

462

Details

0ms

select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) and name in (...) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) and name in (...) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Feb 08	09	462	0ms	0ms

16

462

Details

0ms

select distinct category from ( select * from stats_hrsapproaches_summary where statsid = ?) as data;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 08	09	462	0ms	0ms

17

462

Details

0ms

select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = ? and category = lower(?) and name in (...) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Feb 08	09	462	0ms	0ms

18

462

Details

0ms

select absolutetimezoneoffset from symbols s inner join brokersymbollist bsl on s.symbolid = bsl.symbolid inner join downloadersymbolsettings dss on bsl.symbolid = dss.symbolid inner join datafeedstimetable df on dss.classname = df.classname where brokerid = ? and lower(exchange) = lower(?) group by absolutetimezoneoffset;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 08	09	462	0ms	0ms

19

462

Details

0ms

select distinct category from ( select * from stats_summary where statsid = ? union select * from stats_hrs_summary where statsid = ?) as data;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 08	09	462	0ms	0ms

20

462

Details

0ms

select name from ( select * from ( select * from stats_summary ss where statsid = ? union select * from stats_hrs_summary where statsid = ?) as data where lower(category) = ? order by correct desc limit ?) a;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 08	09	462	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

38

Details

0ms

select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 08	09	38	0ms	0ms

2

0ms

124

Details

0ms

with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Feb 08	09	124	0ms	0ms

3

0ms

2

Details

0ms

with rar_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ) select bmr.symbolid, patternstarttime, patternendtime, timegranularity, ? as direction, case when bmr.old_resultuid = ? then bmr.old_resultuid else bmr.resultuid end as uid, s.exchange, s.symbol, s.longname, s.shortname, dtt.timezone, bmr.patternmovement, bmr.statisticalmovement, bmr.fromprice, bmr.toprice, bmr.percentile, bmr.patternlengthbars, case when rbr.age is not null then rbr.age when bmr.resultuid <= rm.resultuid then ? else ? end as age, case when rbr.relevant is not null then rbr.relevant when bmr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from bigmovement_results bmr inner join downloadersymbolsettings dss on bmr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on bmr.symbolid = s.symbolid inner join rar_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid left join currencypips cps on cps.symbol = s.symbol where (bmr.old_resultuid = ? or bmr.resultuid = ?) and dtt.dayofweek = ?;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Feb 08	09	2	0ms	0ms

4

0ms

2,404

Details

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 #4

Day	Hour	Count	Duration	Avg duration
Feb 08	09	2,404	0ms	0ms

5

0ms

142

Details

0ms

select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, timegranularity as interval, direction as direction, patternendtime as patternendtime, patternstartprice as psp, patternendprice as pep, target03 as t03, target16 as t16, patternlengthbars as length, p.patternname as patternname, dtt.timezone, cps.pip from fibonacci_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join fibonaccipatterns p on a.pattern = p.patternname left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Feb 08	09	142	0ms	0ms

6

0ms

110

Details

0ms

update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Feb 08	09	110	0ms	0ms

7

0ms

1

Details

0ms

insert into resultmedia (processresultsid, type, name, filename) values (?, ?, ?, ?) returning id;

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Feb 08	09	1	0ms	0ms

8

0ms

18

Details

0ms

select cast(count(*) / cast(setting as numeric) * ? as int) from pg_stat_activity, pg_settings where name = ? group by setting;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Feb 08	09	18	0ms	0ms

9

0ms

238

Details

0ms

select v.datname, c.relname, v.phase, v.heap_blks_total, v.heap_blks_scanned, v.heap_blks_vacuumed, v.index_vacuum_count, v.max_dead_tuples, v.num_dead_tuples from pg_stat_progress_vacuum as v join pg_class c on c.oid = v.relid;

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Feb 08	09	238	0ms	0ms

10

0ms

203

Details

0ms

select distinct s.statsid as statsid, sy.exchange as name from stats s inner join broker b on s.brokerid = b.brokerid inner join brokerconfig bc on b.brokerid = bc.brokerid inner join stats_symbols ss on s.statsid = ss.statsid inner join downloadersymbolsettings dss on ss.symbolid = dss.symbolid inner join symbols sy on dss.symbolid = sy.symbolid where dss.enabled = ? and s.brokerid is not null and b.brokerid = ? and s.groupingtype ilike ? and s.description ilike ? || b.name || ? and s.description ilike ? || sy.exchange || ? and s.description not ilike ? || ? || ? union all select distinct s.statsid as statsid, basegroupname as name from stats s inner join broker b on s.brokerid = b.brokerid inner join brokerconfig bc on b.brokerid = bc.brokerid inner join stats_symbols ss on s.statsid = ss.statsid inner join downloadersymbolsettings dss on ss.symbolid = dss.symbolid inner join symbolgroup sg on dss.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bg.brokerid = b.brokerid where dss.enabled = ? and s.brokerid is not null and b.brokerid = ? and s.groupingtype not ilike ? and s.description ilike ? || b.name || ? and s.description ilike ? || g.basegroupname || ? and s.description not ilike ? || ? || ?;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Feb 08	09	203	0ms	0ms

11

0ms

462

Details

0ms

select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) and name in (...) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) and name in (...) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 08	09	462	0ms	0ms

12

0ms

7

Details

0ms

select * from ( select pricedatetime, open, high, low, close, volume, bsf from t60 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Feb 08	09	7	0ms	0ms

13

0ms

332

Details

0ms

commit;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Feb 08	09	332	0ms	0ms

14

0ms

188

Details

0ms

with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 08	09	188	0ms	0ms

15

0ms

3

Details

0ms

select psd.symbolid, psd.hourlysymbolid as intervalsymbolid, s.symbol, dtt.timezone, dtt.absolutetimezoneoffset, psh.hour as index, psh.ave, psh.stddev, ((psh.ave - psh.stddev) / ?.?) as low, ((psh.ave + psh.stddev) / ?.?) as high, ee.timezone as exchangetimezone, ee.mon_t1start as exchangestart, ee.mon_t1end as exchangeend from powerstats_symboldata psd inner join powerstats_hourly psh on psd.hourlysymbolid = psh.symbolid inner join symbols s on psh.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join mat_ps_hourly_symbolid_max_enddate e on psh.enddate = e.enddate and psh.symbolid = e.symbolid inner join exchanges ee on ee.exchange = s.exchange where psd.symbolid = ? and dtt.dayofweek = ? order by hour asc;

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Feb 08	09	3	0ms	0ms

16

0ms

1

Details

0ms

select (cast(substring(tz.gmoffset from ? for ?) as float) * ? + cast(substring(tz.gmoffset from ? for ?) as float)) / ? as offset from timezones tz where tz.timezone = ?;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 08	09	1	0ms	0ms

17

0ms

238

Details

0ms

select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Feb 08	09	238	0ms	0ms

18

0ms

11

Details

0ms

select * from ( select pricedatetime, open, high, low, close, volume, bsf from t30 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 08	09	11	0ms	0ms

19

0ms

6

Details

0ms

select pid, datname, client_addr from pg_stat_activity where query ilike ? and pid <> pg_backend_pid() and state = ? and datname = ?;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 08	09	6	0ms	0ms

20

0ms

30

Details

0ms

update executions set isrunning = false, has_results = false, response = ? where id = ?;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 08	09	30	0ms	0ms

Time consuming prepare


Date: 2026-02-08 09:10:44
Duration: 2ms
Database: postgres
Date: 2026-02-08 09:40:42
Duration: 10ms
Database: postgres
Date: 2026-02-08 09:11:02
Duration: 0ms
Database: postgres
Date: 2026-02-08 09:40:44
Duration: 0ms
Database: postgres
Date: 2026-02-08 09:46:04
Duration: 1ms
Database: postgres
Date: 2026-02-08 09:45:33
Duration: 1ms
Database: postgres
Date: 2026-02-08 09:10:43
Duration: 2ms
Database: postgres
Date: 2026-02-08 09:10:43
Duration: 0ms
Database: postgres
Date: 2026-02-08 09:02:28
Duration: 0ms
Database: postgres
Date: 2026-02-08 09:11:01
Duration: 3ms
Database: postgres
Date: 2026-02-08 09:10:41
Duration: 6ms
Database: postgres
Date: 2026-02-08 09:10:40
Duration: 2ms
Database: postgres
Date: 2026-02-08 09:10:42
Duration: 5ms
Database: postgres
Date: 2026-02-08 09:00:04
Duration: 2ms
Database: postgres
Date: 2026-02-08 09:50:41
Duration: 0ms
Database: postgres
Date: 2026-02-08 09:10:40
Duration: 0ms
Database: postgres
Date: 2026-02-08 09:45:57
Duration: 0ms
Database: postgres
Date: 2026-02-08 09:45:31
Duration: 0ms
Database: postgres
Date: 2026-02-08 09:10:44
Duration: 0ms
Database: postgres
Date: 2026-02-08 09:10:47
Duration: 2ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

11s764ms

1,004

Details

0ms

56ms

11ms

WITH rar_max as ( ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Feb 08	09	1,004	11s764ms	11ms

WITH rar_max as ( ;

Date: 2026-02-08 09:45:52 Duration: 56ms 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: 2026-02-08 09:45:41 Duration: 38ms Database: postgres parameters: $1 = 't', $2 = '558', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '80', $14 = 'AUDSGD', $15 = 'CHFSGD', $16 = 'EURDKK', $17 = 'EURHKD', $18 = 'EURNOK', $19 = 'EURPLN', $20 = 'EURSEK', $21 = 'EURSGD', $22 = 'EURTRY', $23 = 'EURZAR', $24 = 'GBPDKK', $25 = 'GBPNOK', $26 = 'GBPSEK', $27 = 'GBPSGD', $28 = 'NOKJPY', $29 = 'NOKSEK', $30 = 'SEKJPY', $31 = 'SGDJPY', $32 = 'USDCNH', $33 = 'USDCZK', $34 = 'USDDKK', $35 = 'USDHKD', $36 = 'USDHUF', $37 = 'USDMXN', $38 = 'USDNOK', $39 = 'USDPLN', $40 = 'USDRUB', $41 = 'USDSEK', $42 = 'USDTHB', $43 = 'USDTRY', $44 = 'USDZAR', $45 = 'AUDUSD', $46 = 'EURUSD', $47 = 'GBPUSD', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDJPY', $51 = 'AUDCAD', $52 = 'AUDCHF', $53 = 'AUDJPY', $54 = 'AUDNZD', $55 = 'CADCHF', $56 = 'CADJPY', $57 = 'CHFJPY', $58 = 'EURAUD', $59 = 'EURCAD', $60 = 'EURCHF', $61 = 'EURGBP', $62 = 'EURJPY', $63 = 'EURNZD', $64 = 'GBPAUD', $65 = 'GBPCAD', $66 = 'GBPCHF', $67 = 'GBPJPY', $68 = 'GBPNZD', $69 = 'NZDCAD', $70 = 'NZDCHF', $71 = 'NZDJPY', $72 = 'NZDUSD', $73 = 'USDSGD', $74 = 'AUS200', $75 = 'DE30', $76 = 'ES35', $77 = 'F40', $78 = 'HK50', $79 = 'IT40', $80 = 'JP225', $81 = 'STOXX50', $82 = 'UK100', $83 = 'US2000', $84 = 'US30', $85 = 'US500', $86 = 'CHINA50', $87 = 'USTEC', $88 = 'XAGEUR', $89 = 'XAGUSD', $90 = 'XAUUSD', $91 = 'XAUEUR', $92 = 'XPDUSD', $93 = 'XPTUSD', $94 = '0', $95 = '', $96 = '0', $97 = '0', $98 = '0', $99 = '0', $100 = '0', $101 = 't', $102 = '10', $103 = '10'
WITH rar_max as ( ;

Date: 2026-02-08 09:45:42 Duration: 38ms Database: postgres parameters: $1 = 't', $2 = '558', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '80', $14 = 'AUDSGD', $15 = 'CHFSGD', $16 = 'EURDKK', $17 = 'EURHKD', $18 = 'EURNOK', $19 = 'EURPLN', $20 = 'EURSEK', $21 = 'EURSGD', $22 = 'EURTRY', $23 = 'EURZAR', $24 = 'GBPDKK', $25 = 'GBPNOK', $26 = 'GBPSEK', $27 = 'GBPSGD', $28 = 'NOKJPY', $29 = 'NOKSEK', $30 = 'SEKJPY', $31 = 'SGDJPY', $32 = 'USDCNH', $33 = 'USDCZK', $34 = 'USDDKK', $35 = 'USDHKD', $36 = 'USDHUF', $37 = 'USDMXN', $38 = 'USDNOK', $39 = 'USDPLN', $40 = 'USDRUB', $41 = 'USDSEK', $42 = 'USDTHB', $43 = 'USDTRY', $44 = 'USDZAR', $45 = 'AUDUSD', $46 = 'EURUSD', $47 = 'GBPUSD', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDJPY', $51 = 'AUDCAD', $52 = 'AUDCHF', $53 = 'AUDJPY', $54 = 'AUDNZD', $55 = 'CADCHF', $56 = 'CADJPY', $57 = 'CHFJPY', $58 = 'EURAUD', $59 = 'EURCAD', $60 = 'EURCHF', $61 = 'EURGBP', $62 = 'EURJPY', $63 = 'EURNZD', $64 = 'GBPAUD', $65 = 'GBPCAD', $66 = 'GBPCHF', $67 = 'GBPJPY', $68 = 'GBPNZD', $69 = 'NZDCAD', $70 = 'NZDCHF', $71 = 'NZDJPY', $72 = 'NZDUSD', $73 = 'USDSGD', $74 = 'AUS200', $75 = 'DE30', $76 = 'ES35', $77 = 'F40', $78 = 'HK50', $79 = 'IT40', $80 = 'JP225', $81 = 'STOXX50', $82 = 'UK100', $83 = 'US2000', $84 = 'US30', $85 = 'US500', $86 = 'CHINA50', $87 = 'USTEC', $88 = 'XAGEUR', $89 = 'XAGUSD', $90 = 'XAUUSD', $91 = 'XAUEUR', $92 = 'XPDUSD', $93 = 'XPTUSD', $94 = '0', $95 = '', $96 = '0', $97 = '0', $98 = '0', $99 = '0', $100 = '0', $101 = 't', $102 = '10', $103 = '10'

2

1s657ms

5,219

Details

0ms

7ms

0ms

SELECT ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	09	5,219	1s657ms	0ms

SELECT ;

Date: 2026-02-08 09:10:43 Duration: 7ms Database: postgres parameters: $1 = '515840243190162300'
SELECT ;

Date: 2026-02-08 09:05:04 Duration: 7ms Database: postgres parameters: $1 = '667', $2 = '667', $3 = '500991628256412200'
SELECT ;

Date: 2026-02-08 09:10:43 Duration: 5ms Database: postgres parameters: $1 = '515840243190162300'

3

1s472ms

612

Details

0ms

4ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	09	612	1s472ms	2ms

SELECT symbolid, ;

Date: 2026-02-08 09:10:44 Duration: 4ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '30', $3 = 'AUS_200'
SELECT symbolid, ;

Date: 2026-02-08 09:47:02 Duration: 3ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'EURGBP', $4 = 'GBPJPY', $5 = 'EURJPY', $6 = 'EURHUF', $7 = 'EURUSD', $8 = 'EURAUD', $9 = 'ETHUSD', $10 = 'GBPUSD'
SELECT symbolid, ;

Date: 2026-02-08 09:10:44 Duration: 3ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '15', $3 = 'AUS_200'

4

1s345ms

203

Details

0ms

32ms

6ms

select distinct s.statsid as statsid, sy.exchange as name;

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	09	203	1s345ms	6ms

select distinct s.statsid as statsid, sy.exchange as name;

Date: 2026-02-08 09:00:45 Duration: 32ms Database: postgres parameters: $1 = '1436', $2 = '1436'
select distinct s.statsid as statsid, sy.exchange as name;

Date: 2026-02-08 09:00:45 Duration: 26ms Database: postgres parameters: $1 = '1436', $2 = '1436'
select distinct s.statsid as statsid, sy.exchange as name;

Date: 2026-02-08 09:10:45 Duration: 24ms Database: postgres parameters: $1 = '621', $2 = '621'

5

769ms

8,778

Details

0ms

16ms

0ms

select category, ;

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	09	8,778	769ms	0ms

select category, ;

Date: 2026-02-08 09:10:42 Duration: 16ms Database: postgres parameters: $1 = '515852059313898307', $2 = 'symbol', $3 = 'BTCUSD', $4 = 'AUDJPY', $5 = 'USDMXN', $6 = 'GBPJPY', $7 = 'USDTHB', $8 = 'USDZAR', $9 = 'USDJPY', $10 = 'EURZAR', $11 = 'NZDJPY', $12 = 'USDHUF', $13 = 'CHFJPY', $14 = 'CADJPY', $15 = 'SGDJPY', $16 = 'EURJPY', $17 = 'EURTRY', $18 = 'EURHKD', $19 = 'SEKJPY', $20 = 'GBPSEK', $21 = 'USDSEK', $22 = 'USDDKK', $23 = 'EURSEK', $24 = 'NOKJPY', $25 = 'USDNOK', $26 = 'USDPLN', $27 = 'GBPDKK', $28 = 'USDCZK', $29 = 'EURNOK', $30 = 'GBPNOK', $31 = 'BTCUSD', $32 = 'GBPAUD', $33 = 'GBPNZD', $34 = 'EURPLN', $35 = 'EURAUD', $36 = 'USDCNH', $37 = 'USDTRY', $38 = 'EURNZD', $39 = 'GBPCAD', $40 = 'EURGBP', $41 = 'SEKJPY', $42 = 'USDCAD', $43 = 'GBPNOK', $44 = 'USDHUF', $45 = 'USDZAR', $46 = 'GBPCAD', $47 = 'GBPUSD', $48 = 'EURNOK', $49 = 'GBPSGD', $50 = 'CHFSGD', $51 = 'EURCAD', $52 = 'NOKJPY', $53 = '515852059313898307', $54 = 'symbol', $55 = 'BTCUSD', $56 = 'AUDJPY', $57 = 'USDMXN', $58 = 'GBPJPY', $59 = 'USDTHB', $60 = 'USDZAR', $61 = 'USDJPY', $62 = 'EURZAR', $63 = 'NZDJPY', $64 = 'USDHUF', $65 = 'CHFJPY', $66 = 'CADJPY', $67 = 'SGDJPY', $68 = 'EURJPY', $69 = 'EURTRY', $70 = 'EURHKD', $71 = 'SEKJPY', $72 = 'GBPSEK', $73 = 'USDSEK', $74 = 'USDDKK', $75 = 'EURSEK', $76 = 'NOKJPY', $77 = 'USDNOK', $78 = 'USDPLN', $79 = 'GBPDKK', $80 = 'USDCZK', $81 = 'EURNOK', $82 = 'GBPNOK', $83 = 'BTCUSD', $84 = 'GBPAUD', $85 = 'GBPNZD', $86 = 'EURPLN', $87 = 'EURAUD', $88 = 'USDCNH', $89 = 'USDTRY', $90 = 'EURNZD', $91 = 'GBPCAD', $92 = 'EURGBP', $93 = 'SEKJPY', $94 = 'USDCAD', $95 = 'GBPNOK', $96 = 'USDHUF', $97 = 'USDZAR', $98 = 'GBPCAD', $99 = 'GBPUSD', $100 = 'EURNOK', $101 = 'GBPSGD', $102 = 'CHFSGD', $103 = 'EURCAD', $104 = 'NOKJPY'
select category, ;

Date: 2026-02-08 09:10:42 Duration: 14ms Database: postgres parameters: $1 = '601729875347685307', $2 = 'symbol', $3 = 'Danone', $4 = 'Adidas', $5 = 'Daimler', $6 = 'Bayer', $7 = 'LVMH', $8 = 'Volksw', $9 = 'Lufthansa', $10 = 'Lufthansa', $11 = 'Danone', $12 = 'Volksw', $13 = 'Adidas', $14 = 'Bayer', $15 = 'LVMH', $16 = 'Daimler', $17 = '601729875347685307', $18 = 'symbol', $19 = 'Danone', $20 = 'Adidas', $21 = 'Daimler', $22 = 'Bayer', $23 = 'LVMH', $24 = 'Volksw', $25 = 'Lufthansa', $26 = 'Lufthansa', $27 = 'Danone', $28 = 'Volksw', $29 = 'Adidas', $30 = 'Bayer', $31 = 'LVMH', $32 = 'Daimler'
select category, ;

Date: 2026-02-08 09:10:43 Duration: 13ms Database: postgres parameters: $1 = '601729875363291307', $2 = 'symbol', $3 = 'Danone', $4 = 'Adidas', $5 = 'Daimler', $6 = 'Bayer', $7 = 'LVMH', $8 = 'Volksw', $9 = 'Lufthansa', $10 = 'Lufthansa', $11 = 'Danone', $12 = 'Volksw', $13 = 'Adidas', $14 = 'Bayer', $15 = 'LVMH', $16 = 'Daimler', $17 = '601729875363291307', $18 = 'symbol', $19 = 'Danone', $20 = 'Adidas', $21 = 'Daimler', $22 = 'Bayer', $23 = 'LVMH', $24 = 'Volksw', $25 = 'Lufthansa', $26 = 'Lufthansa', $27 = 'Danone', $28 = 'Volksw', $29 = 'Adidas', $30 = 'Bayer', $31 = 'LVMH', $32 = 'Daimler'

6

534ms

19

Details

0ms

55ms

28ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	09	19	534ms	28ms

with wh_patitioned as ( ;

Date: 2026-02-08 09:10:41 Duration: 55ms 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: 2026-02-08 09:40:36 Duration: 54ms 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: 2026-02-08 09:10:02 Duration: 36ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'

7

344ms

462

Details

0ms

1ms

0ms

SELECT absolutetimezoneoffset;

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	09	462	344ms	0ms

SELECT absolutetimezoneoffset;

Date: 2026-02-08 09:10:41 Duration: 1ms Database: postgres parameters: $1 = '538', $2 = 'Commodities'
SELECT absolutetimezoneoffset;

Date: 2026-02-08 09:51:30 Duration: 1ms Database: postgres parameters: $1 = '538', $2 = 'Shares EU'
SELECT absolutetimezoneoffset;

Date: 2026-02-08 09:10:42 Duration: 1ms Database: postgres parameters: $1 = '538', $2 = 'Shares EU'

8

335ms

44

Details

4ms

16ms

7ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	09	44	335ms	7ms

WITH last_candle AS ( ;

Date: 2026-02-08 09:36:00 Duration: 16ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-02-08 09:36:00 Duration: 15ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-02-08 09:10:42 Duration: 15ms Database: postgres parameters: $1 = '558', $2 = '558'

9

238ms

15,823

Details

0ms

7ms

0ms

select 1;

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	09	15,823	238ms	0ms

select 1;

Date: 2026-02-08 09:50:51 Duration: 7ms Database: postgres
select 1;

Date: 2026-02-08 09:50:51 Duration: 6ms Database: postgres
select 1;

Date: 2026-02-08 09:51:09 Duration: 4ms Database: postgres

10

227ms

139

Details

1ms

2ms

1ms

SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Times Reported Time consuming bind #10

Day	Hour	Count	Duration	Avg duration
	09	139	227ms	1ms

SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-02-08 09:16:04 Duration: 2ms Database: postgres parameters: $1 = 'MILLENNIUMPF'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-02-08 09:45:43 Duration: 2ms Database: postgres parameters: $1 = 'AXIORY'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-02-08 09:46:04 Duration: 2ms Database: postgres parameters: $1 = 'PEPPERSTONEMT5'

11

181ms

2,404

Details

0ms

INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Times Reported Time consuming bind #11

Day	Hour	Count	Duration	Avg duration
	09	2,404	181ms	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: 2026-02-08 09:11:02 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 17:00:00', $2 = '26888.1', $3 = '26966.3', $4 = '26867.3', $5 = '26935.3', $6 = '20485', $7 = '515840247933961300', $8 = '0', $9 = '2026-02-08 09:11:02.352', $10 = '2026-02-08 09:11:02.271', $11 = '26888.1', $12 = '26966.3', $13 = '26867.3', $14 = '26935.3', $15 = '20485', $16 = '0', $17 = '2026-02-08 09:11:02.352', $18 = '2026-02-08 09:11:02.271'
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: 2026-02-08 09:10:08 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 22:00:00', $2 = '6913.45', $3 = '6941.4', $4 = '6912.55', $5 = '6924.53', $6 = '24223', $7 = '515840248032396300', $8 = '0', $9 = '2026-02-08 09:10:08.038', $10 = '2026-02-08 09:10:07.976', $11 = '6913.45', $12 = '6941.4', $13 = '6912.55', $14 = '6924.53', $15 = '24223', $16 = '0', $17 = '2026-02-08 09:10:08.038', $18 = '2026-02-08 09:10:07.976'
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: 2026-02-08 09:35:36 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 22:00:00', $2 = '0.775405', $3 = '0.77548', $4 = '0.775155', $5 = '0.77536', $6 = '1225', $7 = '515840230587639300', $8 = '0', $9 = '2026-02-08 09:35:36.178', $10 = '2026-02-08 09:35:36.177', $11 = '0.775405', $12 = '0.77548', $13 = '0.775155', $14 = '0.77536', $15 = '1225', $16 = '0', $17 = '2026-02-08 09:35:36.178', $18 = '2026-02-08 09:35:36.177'

12

158ms

2,436

Details

0ms

INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Times Reported Time consuming bind #12

Day	Hour	Count	Duration	Avg duration
	09	2,436	158ms	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: 2026-02-08 09:01:24 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 22:30:00', $2 = '2.262255', $3 = '2.26286', $4 = '2.2621', $5 = '2.26278', $6 = '2388', $7 = '515840230500992300', $8 = '0', $9 = '2026-02-08 09:01:24.979', $10 = '2026-02-08 09:01:24.97', $11 = '2.262255', $12 = '2.26286', $13 = '2.2621', $14 = '2.26278', $15 = '2388', $16 = '0', $17 = '2026-02-08 09:01:24.979', $18 = '2026-02-08 09:01:24.97'
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: 2026-02-08 09:40:44 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 21:00:00', $2 = '8774.9', $3 = '8779.45', $4 = '8771.85', $5 = '8775', $6 = '2091', $7 = '515840248015340300', $8 = '0', $9 = '2026-02-08 09:40:44.313', $10 = '2026-02-08 09:40:44.216', $11 = '8774.9', $12 = '8779.45', $13 = '8771.85', $14 = '8775', $15 = '2091', $16 = '0', $17 = '2026-02-08 09:40:44.313', $18 = '2026-02-08 09:40:44.216'
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: 2026-02-08 09:32:01 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 18:00:00', $2 = '26935.7', $3 = '26975.5', $4 = '26930.7', $5 = '26963.8', $6 = '7047', $7 = '515840247933633300', $8 = '0', $9 = '2026-02-08 09:32:01.47', $10 = '2026-02-08 09:32:01.404', $11 = '26935.7', $12 = '26975.5', $13 = '26930.7', $14 = '26963.8', $15 = '7047', $16 = '0', $17 = '2026-02-08 09:32:01.471', $18 = '2026-02-08 09:32:01.404'

13

118ms

2,813

Details

0ms

INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Times Reported Time consuming bind #13

Day	Hour	Count	Duration	Avg duration
	09	2,813	118ms	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: 2026-02-08 09:56:05 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 23:15:00', $2 = '25025.78', $3 = '25031.28', $4 = '24999.65', $5 = '25006.15', $6 = '3571', $7 = '515840248038958300', $8 = '0', $9 = '2026-02-08 09:56:05.186', $10 = '2026-02-08 09:56:05.064', $11 = '25025.78', $12 = '25031.28', $13 = '24999.65', $14 = '25006.15', $15 = '3571', $16 = '0', $17 = '2026-02-08 09:56:05.186', $18 = '2026-02-08 09:56:05.064'
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: 2026-02-08 09:02:28 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 21:30:00', $2 = '8776.85', $3 = '8784.85', $4 = '8775.85', $5 = '8782.85', $6 = '55', $7 = '500991628265645200', $8 = '0', $9 = '2026-02-08 09:02:28.116', $10 = '2026-02-08 09:02:28.025', $11 = '8776.85', $12 = '8784.85', $13 = '8775.85', $14 = '8782.85', $15 = '55', $16 = '0', $17 = '2026-02-08 09:02:28.116', $18 = '2026-02-08 09:02:28.025'
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: 2026-02-08 09:45:54 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 23:45:00', $2 = '278.09', $3 = '279.01', $4 = '278.075', $5 = '278.195', $6 = '501', $7 = '515840216708269300', $8 = '0', $9 = '2026-02-08 09:45:54.205', $10 = '2026-02-08 09:45:53.894', $11 = '278.09', $12 = '279.01', $13 = '278.075', $14 = '278.195', $15 = '501', $16 = '0', $17 = '2026-02-08 09:45:54.205', $18 = '2026-02-08 09:45:53.894'

14

51ms

462

Details

0ms

4ms

0ms

SELECT name;

Times Reported Time consuming bind #14

Day	Hour	Count	Duration	Avg duration
	09	462	51ms	0ms

SELECT name;

Date: 2026-02-08 09:00:45 Duration: 4ms Database: postgres parameters: $1 = '515852059317765307', $2 = '515852059317765307'
SELECT name;

Date: 2026-02-08 09:45:32 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307', $2 = '515852059317765307'
SELECT name;

Date: 2026-02-08 09:10:38 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307', $2 = '515852059317765307'

15

51ms

924

Details

0ms

1ms

0ms

select distinct category;

Times Reported Time consuming bind #15

Day	Hour	Count	Duration	Avg duration
	09	924	51ms	0ms

select distinct category;

Date: 2026-02-08 09:00:45 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307'
select distinct category;

Date: 2026-02-08 09:00:45 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307'
select distinct category;

Date: 2026-02-08 09:10:43 Duration: 0ms Database: postgres parameters: $1 = '515852059313898307', $2 = '515852059313898307'

16

48ms

8

Details

3ms

9ms

6ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #16

Day	Hour	Count	Duration	Avg duration
	09	8	48ms	6ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-08 09:10:48 Duration: 9ms Database: postgres parameters: $1 = '958', $2 = '958'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-08 09:10:47 Duration: 9ms Database: postgres parameters: $1 = '958', $2 = '958'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-08 09:01:22 Duration: 9ms Database: postgres parameters: $1 = '627', $2 = '627'

17

38ms

86

Details

0ms

5ms

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 #17

Day	Hour	Count	Duration	Avg duration
	09	86	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: 2026-02-08 09:05:43 Duration: 5ms Database: postgres parameters: $1 = '607634606692355301'
/*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: 2026-02-08 09:20:45 Duration: 4ms Database: postgres parameters: $1 = '607631894848621301'
/*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: 2026-02-08 09:50:42 Duration: 4ms Database: postgres parameters: $1 = '607634602751513301'

18

29ms

203

Details

0ms

3ms

0ms

select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	09	203	29ms	0ms

select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;

Date: 2026-02-08 09:00:45 Duration: 3ms Database: postgres parameters: $1 = '1436'
select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;

Date: 2026-02-08 09:00:45 Duration: 3ms Database: postgres parameters: $1 = '1436'
select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;

Date: 2026-02-08 09:10:38 Duration: 1ms Database: postgres parameters: $1 = '1436'

19

24ms

7

Details

0ms

13ms

3ms

WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;

Times Reported Time consuming bind #19

Day	Hour	Count	Duration	Avg duration
	09	7	24ms	3ms

WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;

Date: 2026-02-08 09:05:18 Duration: 13ms 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: 2026-02-08 09:03:46 Duration: 10ms 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: 2026-02-08 09:10:04 Duration: 0ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

20

22ms

21

Details

0ms

4ms

1ms

/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	09	21	22ms	1ms

/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-02-08 09:56:03 Duration: 4ms Database: postgres parameters: $1 = '607634601646748303'
/*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: 2026-02-08 09:56:27 Duration: 2ms Database: postgres parameters: $1 = '607634660783070303'
/*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: 2026-02-08 09:56:19 Duration: 1ms Database: postgres parameters: $1 = '607635261231261303'

Log levels

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235,683 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	368	0.16%
DETAIL	52,716	22.37%
LOG	182,199	77.31%
STATEMENT	400	0.17%

Events distribution

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0 FATAL entries
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NO DATASET

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0 Total events found

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NO DATASET

Global information

Overview

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