pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Sun Feb 8 16:59:20 2026
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-02-08_180000.log
Parsed 655,974 log entries in 19s
Log start from 2026-02-08 18:00:00 to 2026-02-08 18:59:18

Global Stats

169 Number of unique normalized queries
86,905 Number of queries
1h38m20s Total query duration
2026-02-08 18:00:00 First query
2026-02-08 18:59:18 Last query
3,190 queries/s at 2026-02-08 18:30:04 Query peak

1h38m20s Total query duration
2s811ms Prepare/parse total duration
27s629ms Bind total duration
1h37m49s 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

32 Total number of automatic vacuums
43 Total number of automatic analyzes

492 Number temporary file
142.22 MiB Max size of temporary file
6.23 MiB Average size of temporary file

1,808 Total number of sessions
13 sessions at 2026-02-08 18:58:48 Session peak
1d1h38m16s Total duration of sessions
51s49ms Average duration of sessions
48 Average queries per session
3s263ms Average queries duration per session
47s785ms Average idle time per session

1,808 Total number of connections
27 connections/s at 2026-02-08 18:48:48 Connection peak
3 Total number of databases

SQL Traffic

Key values

3,190 queries/s Query Peak
2026-02-08 18:30:04 Date

SELECT Traffic

Key values

1,592 queries/s Query Peak
2026-02-08 18:30:04 Date

INSERT/UPDATE/DELETE Traffic

Key values

128 queries/s Query Peak
2026-02-08 18:17:51 Date

Queries duration

Key values

1h38m20s 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	18	86,905	0ms	22s792ms	67ms	3m23s	3m37s	4m11s

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Feb 08	18	22,560	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	18	14,358	594	16	96	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Feb 08	18	9,262	26,042	2.81	22.52%

Day	Hour	Count	Average / Second
Feb 08	18	1,808	0.50/s

Day	Hour	Count	Average Duration	Average idle time
Feb 08	18	1,808	51s49ms	47s802ms

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Established Connections

Key values

27 connections Connection Peak
2026-02-08 18:48:48 Date

Connections per database

Key values

acaweb_fx Main Database
1,808 connections Total

Chart
Table

Database	User	Count
acaweb_fx		1,717
	postgres	1,376
	psql	341
socialmedia		91
	postgres	91

Connections per user

Key values

postgres Main User
1,808 connections Total

Chart
Table

User	Count
postgres	1,467
psql	341

Connections per host

Key values

192.168.4.142 Main host with 637 connections
1,808 Total connections

Chart
Table

Host	Count
127.0.0.1	105
192.168.0.114	7
192.168.0.216	117
192.168.0.74	78
192.168.1.145	21
192.168.1.15	19
192.168.1.20	42
192.168.1.239	56
192.168.1.90	6
192.168.2.126	18
192.168.2.182	12
192.168.3.199	38
192.168.4.142	637
192.168.4.33	86
192.168.4.98	330
[local]	236

Simultaneous sessions

Key values

13 sessions Session Peak
2026-02-08 18:58:48 Date

Histogram of session times

Key values

1,424 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	1,424	78.76%
500ms-1s	127	7.02%
1s-30s	204	11.28%
30s-1m	8	0.44%
1m-10m	16	0.88%
10m-30m	25	1.38%
30m-1h	2	0.11%
1h-8h	1	0.06%
> 8h	1	0.06%

Sessions per database

Key values

acaweb_fx Main Database
1,808 sessions Total

Chart
Table

Database	User	Count	Total Duration	Average Duration
acaweb_fx	1,717	1d1h9m46s	52s758ms
socialmedia	91	28m30s	18s799ms

Sessions per user

Key values

postgres Main User
1,808 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
1,808 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
127.0.0.1	105	3s470ms	33ms
192.168.0.114	7	35m	5m
192.168.0.216	117	7m36s	3s897ms
192.168.0.74	78	1h19m14s	1m
192.168.1.145	21	29m19s	1m23s
192.168.1.15	19	10h16m52s	32m28s
192.168.1.20	42	12h36m23s	18m
192.168.1.239	56	318ms	5ms
192.168.1.90	6	49ms	8ms
192.168.2.126	18	5s297ms	294ms
192.168.2.182	12	860ms	71ms
192.168.3.199	38	21s550ms	567ms
192.168.4.142	637	6m19s	595ms
192.168.4.33	86	3m30s	2s444ms
192.168.4.98	330	13s996ms	42ms
[local]	236	3m15s	827ms

Sessions per application

Key values

unknown Main Host
1,808 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	1,808	1d1h38m16s	51s49ms

Checkpoints Buffers

Key values

2,362 buffers Checkpoint Peak
2026-02-08 18:05:24 Date
209.904 seconds Highest write time
0.003 seconds Sync time

Checkpoints Wal files

Key values

2 files Wal files usage Peak
2026-02-08 18:39:53 Date

Checkpoints distance

Key values

46.60 Mo Distance Peak
2026-02-08 18:10:09 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Feb 08	18	16,859	1,733.933s	0.024s	1,734.196s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Feb 08	18	0	0	11	1,398	0.003s	0s

Day	Hour	Count	Avg time (sec)
Feb 08	18	0	0s

Day	Hour	Mean distance	Mean estimate
Feb 08	18	15,013.83 kB	21,150.25 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 18:02:22 Date

Number of temporary files

Key values

30 per second Temp Files Peak
2026-02-08 18:02:12 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Feb 08	18	492	2.99 GiB	6.23 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	58	264.52 MiB	4.52 MiB	4.64 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 18:00:46 Duration: 0ms
2	36	115.35 MiB	3.05 MiB	3.28 MiB	3.20 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 18:01:06 Duration: 0ms
3	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 18:01:13 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 18:01:16 Duration: 0ms
5	4	568.86 MiB	142.21 MiB	142.22 MiB	142.21 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2026-02-08 18:02:18 Duration: 0ms
6	4	347.62 MiB	86.90 MiB	86.92 MiB	86.91 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2026-02-08 18:02:06 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	142.22 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-08 18:47:17 ]
2	142.21 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-08 18:32:16 ]
3	142.21 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-08 18:17:19 ]
4	142.21 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-08 18:02:18 ]
5	86.92 MiB	select updateageforrelevantresults (); [ Date: 2026-02-08 18:02:06 ]
6	86.91 MiB	select updateageforrelevantresults (); [ Date: 2026-02-08 18:47:06 ]
7	86.90 MiB	select updateageforrelevantresults (); [ Date: 2026-02-08 18:32:06 ]
8	86.90 MiB	select updateageforrelevantresults (); [ Date: 2026-02-08 18:17:07 ]
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 18:01:16 ]
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 18:03:15 ]
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 18:05:15 ]
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 18:11:15 ]
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 18:16:16 ]
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 18:18:15 ]
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 18:20:14 ]
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 18:26:16 ]
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 18:31:15 ]
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 18:33:15 ]
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 18:35:15 ]
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 18:41:15 ]

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)
43 analyzes Total

Chart
Table

Table	Number of analyzes
acaweb_fx.public.solr_relevance_old	16
acaweb_fx.pg_catalog.pg_attribute	7
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
socialmedia.public.processes	1
acaweb_fx.public.relevance_keylevels_results	1
acaweb_fx.public.relevance_autochartist_results	1
acaweb_fx.public.latest_candle_datetime_per_receng	1
Total	43

Vacuums per table

Key values

public.solr_relevance_old (16) Main table vacuumed on database acaweb_fx
32 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	11,214	0	72	0	0	7,577	1,789	7,651,601
acaweb_fx.public.datafeeds_latestrun	3	0	369	0	6	0	0	39	6	41,006
acaweb_fx.pg_catalog.pg_attribute	3	3	3,615	0	414	0	201	1,198	409	2,468,281
acaweb_fx.pg_catalog.pg_type	2	2	467	0	40	0	0	143	32	195,098
acaweb_fx.pg_catalog.pg_class	2	2	1,111	0	48	0	0	252	50	336,782
acaweb_fx.pg_toast.pg_toast_2619	1	1	209	0	36	0	0	110	34	134,018
acaweb_fx.pg_catalog.pg_index	1	1	91	0	11	0	0	28	10	75,024
acaweb_fx.pg_catalog.pg_statistic	1	1	1,063	0	160	0	594	366	153	592,871
acaweb_fx.public.solr_imports	1	1	67	0	2	0	0	6	4	14,459
acaweb_fx.public.latest_t15_candle_view	1	1	76	0	3	0	0	7	1	9,103
acaweb_fx.public.relevance_fibonacci_results	1	1	1,183	0	51	0	52	142	44	231,132
Total	32	29	19,465	1,789	843	0	847	9,868	2,532	11,749,375

Tuples removed per table

Key values

public.solr_relevance_old (45254) Main table with removed tuples on database acaweb_fx
52884 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	45,254	85,116	0	0	2,682
acaweb_fx.pg_catalog.pg_attribute	3	3	5,595	32,593	137	51	746
acaweb_fx.pg_catalog.pg_statistic	1	1	711	3,817	0	0	1,194
acaweb_fx.pg_catalog.pg_type	2	2	621	2,898	6	2	84
acaweb_fx.public.datafeeds_latestrun	3	0	179	42	0	0	48
acaweb_fx.pg_catalog.pg_class	2	2	176	3,308	10	0	300
acaweb_fx.public.relevance_fibonacci_results	1	1	145	1,355	0	0	102
acaweb_fx.pg_toast.pg_toast_2619	1	1	78	167	0	0	53
acaweb_fx.public.latest_t15_candle_view	1	1	57	14	0	0	1
acaweb_fx.public.solr_imports	1	1	51	1	0	0	2
acaweb_fx.pg_catalog.pg_index	1	1	17	813	0	0	22
Total	32	29	52,884	130,124	153	53	5,234

Pages removed per table

Key values

pg_catalog.pg_attribute (51) Main table with removed pages on database acaweb_fx
53 pages Total removed

Chart
Table

Table	Number of vacuums	Index scans	Tuples removed	Pages removed
acaweb_fx.pg_catalog.pg_attribute	3	3	5595	51
acaweb_fx.pg_catalog.pg_type	2	2	621	2
acaweb_fx.pg_toast.pg_toast_2619	1	1	78	0
acaweb_fx.pg_catalog.pg_index	1	1	17	0
acaweb_fx.public.datafeeds_latestrun	3	0	179	0
acaweb_fx.pg_catalog.pg_statistic	1	1	711	0
acaweb_fx.public.solr_imports	1	1	51	0
acaweb_fx.public.latest_t15_candle_view	1	1	57	0
acaweb_fx.public.solr_relevance_old	16	16	45254	0
acaweb_fx.pg_catalog.pg_class	2	2	176	0
acaweb_fx.public.relevance_fibonacci_results	1	1	145	0
Total	32	29	52,884	53

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Feb 08	18	32	43

↑ 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

22,560 Total read queries
18,568 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	22,560	25.96%
INSERT	14,358	16.52%
UPDATE	594	0.68%
DELETE	16	0.02%
COPY FROM	96	0.11%
COPY TO	26	0.03%
CTE	2,754	3.17%
DDL	16	0.02%
TCL	708	0.81%
CURSOR	0	0.00%
OTHERS	45,777	52.67%

Queries by database

Key values

unknown Main database
85,918 Requests
1h37m49s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	896	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	100	0ms
	ddl	16	0ms
	delete	16	0ms
	others	227	0ms
	select	64	0ms
	tcl	332	0ms
	update	35	0ms
socialmedia	Total	91	0ms
	select	86	0ms
	tcl	5	0ms
unknown	Total	85,918	1h37m49s
	copy from	16	0ms
	cte	2,654	0ms
	insert	14,358	0ms
	others	2,097	0ms
	select	22,410	0ms
	tcl	371	0ms
	update	559	0ms

Queries by user

Key values

unknown Main user
85,918 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	987	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	100	0ms
	ddl	16	0ms
	delete	16	0ms
	others	227	0ms
	select	150	0ms
	tcl	337	0ms
	update	35	0ms
unknown	Total	85,918	1h37m49s
	copy from	16	0ms
	cte	2,654	0ms
	insert	14,358	0ms
	others	2,097	0ms
	select	22,410	0ms
	tcl	371	0ms
	update	559	0ms

Duration by user

Key values

1h37m49s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	987	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	100	0ms
	ddl	16	0ms
	delete	16	0ms
	others	227	0ms
	select	150	0ms
	tcl	337	0ms
	update	35	0ms
unknown	Total	85,918	1h37m49s
	copy from	16	0ms
	cte	2,654	0ms
	insert	14,358	0ms
	others	2,097	0ms
	select	22,410	0ms
	tcl	371	0ms
	update	559	0ms

Queries by host

Key values

unknown Main host
86,905 Requests
1h37m49s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	86,905	1h37m49s
	copy from	96	0ms
	copy to	26	0ms
	cte	2,754	0ms
	ddl	16	0ms
	delete	16	0ms
	insert	14,358	0ms
	others	2,324	0ms
	select	22,560	0ms
	tcl	708	0ms
	update	594	0ms

Queries by application

Key values

unknown Main application
86,564 Requests
1h37m49s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
psql	Total	341	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	35	0ms
unknown	Total	86,564	1h37m49s
	copy from	16	0ms
	cte	2,654	0ms
	insert	14,358	0ms
	others	2,320	0ms
	select	22,496	0ms
	tcl	708	0ms
	update	559	0ms

Number of cancelled queries

Key values

0 per second Cancelled query Peak
2026-02-08 18:03:54 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

28,188 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	28,188	64.87%
1-5ms	13,016	29.95%
5-10ms	199	0.46%
10-25ms	353	0.81%
25-50ms	165	0.38%
50-100ms	222	0.51%
100-500ms	337	0.78%
500-1000ms	87	0.20%
1000-10000ms	725	1.67%
> 10000ms	161	0.37%

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

30

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	18	30	0ms	0ms

2

0ms

204

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	18	204	0ms	0ms

3

0ms

5

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	18	5	0ms	0ms

4

0ms

2,229

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	18	2,229	0ms	0ms

5

0ms

61

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	18	61	0ms	0ms

6

0ms

113

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	18	113	0ms	0ms

7

0ms

5

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	18	5	0ms	0ms

8

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 #8

Day	Hour	Count	Duration	Avg duration
Feb 08	18	238	0ms	0ms

9

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 #9

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

10

0ms

11

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 #10

Day	Hour	Count	Duration	Avg duration
Feb 08	18	11	0ms	0ms

11

0ms

354

Details

0ms

commit;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 08	18	354	0ms	0ms

12

0ms

324

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 #12

Day	Hour	Count	Duration	Avg duration
Feb 08	18	324	0ms	0ms

13

0ms

10

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 #13

Day	Hour	Count	Duration	Avg duration
Feb 08	18	10	0ms	0ms

14

0ms

238

Details

0ms

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

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 08	18	238	0ms	0ms

15

0ms

2

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 #15

Day	Hour	Count	Duration	Avg duration
Feb 08	18	2	0ms	0ms

16

0ms

13

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 #16

Day	Hour	Count	Duration	Avg duration
Feb 08	18	13	0ms	0ms

17

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 #17

Day	Hour	Count	Duration	Avg duration
Feb 08	18	6	0ms	0ms

18

0ms

2

Details

0ms

select name, value from systemsettings limit ? offset ?;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 08	18	2	0ms	0ms

19

0ms

25

Details

0ms

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

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 08	18	25	0ms	0ms

20

0ms

238

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 08	18	238	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

6,856

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 08	18	6,856	0ms	0ms

2

6,544

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	18	6,544	0ms	0ms

3

3,478

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 #3

Day	Hour	Count	Duration	Avg duration
Feb 08	18	3,478	0ms	0ms

4

2,911

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 #4

Day	Hour	Count	Duration	Avg duration
Feb 08	18	2,911	0ms	0ms

5

2,543

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 #5

Day	Hour	Count	Duration	Avg duration
Feb 08	18	2,543	0ms	0ms

6

2,229

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 #6

Day	Hour	Count	Duration	Avg duration
Feb 08	18	2,229	0ms	0ms

7

2,219

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 #7

Day	Hour	Count	Duration	Avg duration
Feb 08	18	2,219	0ms	0ms

8

982

Details

0ms

select datetimeupdate from latest_candle_datetime_per_receng where recognitionengine ilike ?;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Feb 08	18	982	0ms	0ms

9

809

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Feb 08	18	809	0ms	0ms

10

797

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Feb 08	18	797	0ms	0ms

11

460

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 #11

Day	Hour	Count	Duration	Avg duration
Feb 08	18	460	0ms	0ms

12

354

Details

0ms

commit;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Feb 08	18	354	0ms	0ms

13

354

Details

0ms

begin;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Feb 08	18	354	0ms	0ms

14

332

Details

0ms

update datafeeds_latestrun set latestrxtime = subquery.latestrxtime, latestdbwritetime = subquery.latestdbwritetime from ( select latestrxtime, latestdbwritetime from latest_t15_candle_view where classname ilike ?) as subquery where datafeeds_latestrun.feedname ilike ?;

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 08	18	332	0ms	0ms

15

324

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 #15

Day	Hour	Count	Duration	Avg duration
Feb 08	18	324	0ms	0ms

16

324

Details

0ms

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

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 08	18	324	0ms	0ms

17

276

Details

0ms

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

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Feb 08	18	276	0ms	0ms

18

251

Details

0ms

with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ) select a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, s.exchange, s.symbol, s.longname, s.shortname, breakout, dtt.timezone, patternstartprice, patternendprice, qtytp, newlevels.profit, newlevels.stop, newlevels.filtered, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern inner join rar_max rm on ? = ? left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid left join lateral calc_cp_signal (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 08	18	251	0ms	0ms

19

247

Details

0ms

set statement_timeout = ?;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 08	18	247	0ms	0ms

20

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 #20

Day	Hour	Count	Duration	Avg duration
Feb 08	18	238	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

30

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	18	30	0ms	0ms

2

0ms

204

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	18	204	0ms	0ms

3

0ms

5

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	18	5	0ms	0ms

4

0ms

2,229

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	18	2,229	0ms	0ms

5

0ms

61

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	18	61	0ms	0ms

6

0ms

113

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	18	113	0ms	0ms

7

0ms

5

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	18	5	0ms	0ms

8

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 #8

Day	Hour	Count	Duration	Avg duration
Feb 08	18	238	0ms	0ms

9

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 #9

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

10

0ms

11

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 #10

Day	Hour	Count	Duration	Avg duration
Feb 08	18	11	0ms	0ms

11

0ms

354

Details

0ms

commit;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 08	18	354	0ms	0ms

12

0ms

324

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 #12

Day	Hour	Count	Duration	Avg duration
Feb 08	18	324	0ms	0ms

13

0ms

10

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 #13

Day	Hour	Count	Duration	Avg duration
Feb 08	18	10	0ms	0ms

14

0ms

238

Details

0ms

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

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 08	18	238	0ms	0ms

15

0ms

2

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 #15

Day	Hour	Count	Duration	Avg duration
Feb 08	18	2	0ms	0ms

16

0ms

13

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 #16

Day	Hour	Count	Duration	Avg duration
Feb 08	18	13	0ms	0ms

17

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 #17

Day	Hour	Count	Duration	Avg duration
Feb 08	18	6	0ms	0ms

18

0ms

2

Details

0ms

select name, value from systemsettings limit ? offset ?;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 08	18	2	0ms	0ms

19

0ms

25

Details

0ms

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

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 08	18	25	0ms	0ms

20

0ms

238

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 08	18	238	0ms	0ms

Time consuming prepare


Date: 2026-02-08 18:01:35
Duration: 18ms
Database: postgres
Date: 2026-02-08 18:02:08
Duration: 2ms
Database: postgres
Date: 2026-02-08 18:10:34
Duration: 0ms
Database: postgres
Date: 2026-02-08 18:11:02
Duration: 0ms
Database: postgres
Date: 2026-02-08 18:30:05
Duration: 2ms
Database: postgres
Date: 2026-02-08 18:15:44
Duration: 1ms
Database: postgres
Date: 2026-02-08 18:34:21
Duration: 0ms
Database: postgres
Date: 2026-02-08 18:47:05
Duration: 0ms
Database: postgres
Date: 2026-02-08 18:31:09
Duration: 3ms
Database: postgres
Date: 2026-02-08 18:21:09
Duration: 2ms
Database: postgres
Date: 2026-02-08 18:40:04
Duration: 2ms
Database: postgres
Date: 2026-02-08 18:02:05
Duration: 0ms
Database: postgres
Date: 2026-02-08 18:01:36
Duration: 0ms
Database: postgres
Date: 2026-02-08 18:48:00
Duration: 2ms
Database: postgres
Date: 2026-02-08 18:00:53
Duration: 0ms
Database: postgres
Date: 2026-02-08 18:37:20
Duration: 1ms
Database: postgres
Date: 2026-02-08 18:35:16
Duration: 0ms
Database: postgres
Date: 2026-02-08 18:06:44
Duration: 1ms
Database: postgres
Date: 2026-02-08 18:07:35
Duration: 0ms
Database: postgres
Date: 2026-02-08 18:06:44
Duration: 0ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

21s833ms

1,821

Details

0ms

58ms

11ms

WITH rar_max as ( ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Feb 08	18	1,821	21s833ms	11ms

WITH rar_max as ( ;

Date: 2026-02-08 18:36:53 Duration: 58ms 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 18:17:08 Duration: 38ms Database: postgres parameters: $1 = '667', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '84', $13 = 'AUDCAD', $14 = 'AUDCHF', $15 = 'AUDJPY', $16 = 'AUDNZD', $17 = 'AUDSGD', $18 = 'CADCHF', $19 = 'CADJPY', $20 = 'CHFJPY', $21 = 'EURAUD', $22 = 'EURCAD', $23 = 'EURCHF', $24 = 'EURCZK', $25 = 'EURGBP', $26 = 'EURHUF', $27 = 'EURJPY', $28 = 'EURNOK', $29 = 'EURNZD', $30 = 'EURPLN', $31 = 'EURSEK', $32 = 'EURSGD', $33 = 'EURTRY', $34 = 'EURZAR', $35 = 'GBPAUD', $36 = 'GBPCAD', $37 = 'GBPCHF', $38 = 'GBPJPY', $39 = 'GBPNZD', $40 = 'GBPPLN', $41 = 'GBPSEK', $42 = 'GBPSGD', $43 = 'NZDCAD', $44 = 'NZDCHF', $45 = 'NZDJPY', $46 = 'NZDSGD', $47 = 'USDCNH', $48 = 'USDCZK', $49 = 'USDHUF', $50 = 'USDNOK', $51 = 'USDPLN', $52 = 'USDSEK', $53 = 'USDSGD', $54 = 'USDTRY', $55 = 'USDZAR', $56 = 'WTI', $57 = 'XBRUSD', $58 = 'XTIUSD', $59 = 'BTCUSD', $60 = 'XAGAUD', $61 = 'XAGUSD', $62 = 'XAUAUD', $63 = 'XAUUSD', $64 = 'XPTUSD', $65 = 'XPDUSD', $66 = 'AUDUSD', $67 = 'EURUSD', $68 = 'GBPUSD', $69 = 'NZDUSD', $70 = 'USDCAD', $71 = 'USDCHF', $72 = 'USDHKD', $73 = 'USDJPY', $74 = 'AUS200', $75 = 'CHINA300', $76 = 'CHINA50', $77 = 'DJ30', $78 = 'ESP35t', $79 = 'EUR50', $80 = 'EURO50', $81 = 'FRA40', $82 = 'GDAXI', $83 = 'GDAXIm', $84 = 'HK50', $85 = 'ITA40', $86 = 'J225', $87 = 'JP225', $88 = 'NAS100', $89 = 'SING30', $90 = 'SPA35', $91 = 'STOXX50', $92 = 'SUI20', $93 = 'UK100', $94 = 'US100', $95 = 'US30', $96 = 'US500', $97 = '500', $98 = '500', $99 = 't', $100 = '10', $101 = '10'
WITH rar_max as ( ;

Date: 2026-02-08 18:53:35 Duration: 34ms Database: postgres parameters: $1 = 't', $2 = '667', $3 = '0', $4 = '0', $5 = '0', $6 = '', $7 = '0', $8 = '', $9 = '0', $10 = '', $11 = '0', $12 = '0', $13 = '0', $14 = '0', $15 = '0', $16 = 't', $17 = '0', $18 = '0'

2

2s406ms

7,377

Details

0ms

7ms

0ms

SELECT ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	18	7,377	2s406ms	0ms

SELECT ;

Date: 2026-02-08 18:30:05 Duration: 7ms Database: postgres parameters: $1 = '500991628203869200'
SELECT ;

Date: 2026-02-08 18:20:52 Duration: 7ms Database: postgres parameters: $1 = '689', $2 = '689', $3 = '515840245920901300'
SELECT ;

Date: 2026-02-08 18:30:05 Duration: 6ms Database: postgres parameters: $1 = '500991627551098200'

3

1s487ms

566

Details

0ms

7ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	18	566	1s487ms	2ms

SELECT symbolid, ;

Date: 2026-02-08 18:17:08 Duration: 7ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '15', $3 = 'SPX500', $4 = 'US30'
SELECT symbolid, ;

Date: 2026-02-08 18:46:03 Duration: 4ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'NZDUSD', $4 = 'USOil', $5 = 'SHBUSD', $6 = 'ETHJPY', $7 = 'MATUSD', $8 = 'BTCUSD', $9 = 'ETHUSD', $10 = 'UKOil', $11 = 'DOGUSD', $12 = 'USDJPY', $13 = 'EURUSD', $14 = 'LTCJPY', $15 = 'JP225', $16 = 'USDZAR', $17 = 'US30', $18 = 'GBPUSD', $19 = 'DOTBTC', $20 = 'EURGBP', $21 = 'EURJPY', $22 = 'BTCXAU', $23 = 'LTCUSD', $24 = 'BTCZAR', $25 = 'EURHUF', $26 = 'USDCHF', $27 = 'SOLUSD', $28 = 'GTi12', $29 = 'GBPJPY', $30 = 'USDCZK', $31 = 'EURAUD', $32 = 'USDCAD', $33 = 'BTCUSO'
SELECT symbolid, ;

Date: 2026-02-08 18:01:32 Duration: 3ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'GBPUSD.ID', $4 = 'GBPJPY', $5 = 'GBPJPY.FX', $6 = 'GBPNZD.FX', $7 = 'GBPUSD.FX', $8 = 'GBPJPY.ID', $9 = 'GBPUSD'

4

401ms

60

Details

4ms

11ms

6ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	18	60	401ms	6ms

WITH last_candle AS ( ;

Date: 2026-02-08 18:36:00 Duration: 11ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-02-08 18:08:00 Duration: 10ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-02-08 18:28:02 Duration: 10ms Database: postgres parameters: $1 = '667', $2 = '667'

5

337ms

19

Details

0ms

54ms

17ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	18	19	337ms	17ms

with wh_patitioned as ( ;

Date: 2026-02-08 18:50:52 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 18:25:00 Duration: 30ms 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 18:25:02 Duration: 30ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'

6

199ms

121

Details

1ms

2ms

1ms

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

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	18	121	199ms	1ms

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

Date: 2026-02-08 18:01:29 Duration: 2ms Database: postgres parameters: $1 = 'FPMARKETS'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-02-08 18:16:43 Duration: 2ms Database: postgres parameters: $1 = 'AXIORY'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-02-08 18:01:19 Duration: 2ms Database: postgres parameters: $1 = 'ICMARKETS'

7

179ms

24

Details

0ms

12ms

7ms

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

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	18	24	179ms	7ms

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

Date: 2026-02-08 18:22:40 Duration: 12ms 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 18:33:57 Duration: 12ms 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 18:07:35 Duration: 12ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

8

176ms

2,229

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 #8

Day	Hour	Count	Duration	Avg duration
	18	2,229	176ms	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 18:10:34 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 21:00:00', $2 = '199.82', $3 = '200.08', $4 = '199.81', $5 = '199.97', $6 = '1064', $7 = '515840247929791300', $8 = '0', $9 = '2026-02-08 18:10:34.528', $10 = '2026-02-08 18:10:34.46', $11 = '199.82', $12 = '200.08', $13 = '199.81', $14 = '199.97', $15 = '1064', $16 = '0', $17 = '2026-02-08 18:10:34.528', $18 = '2026-02-08 18:10:34.46'
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 18:11:04 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 22:00:00', $2 = '24982.1', $3 = '25118.35', $4 = '24980.97', $5 = '25039.78', $6 = '27110', $7 = '515840248039327300', $8 = '0', $9 = '2026-02-08 18:11:04.87', $10 = '2026-02-08 18:11:04.769', $11 = '24982.1', $12 = '25118.35', $13 = '24980.97', $14 = '25039.78', $15 = '27110', $16 = '0', $17 = '2026-02-08 18:11:04.87', $18 = '2026-02-08 18:11:04.769'
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 18:11:45 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 20:00:00', $2 = '8767.4', $3 = '8777.9', $4 = '8765.2', $5 = '8774.95', $6 = '4787', $7 = '515840248015562300', $8 = '0', $9 = '2026-02-08 18:11:45.237', $10 = '2026-02-08 18:11:45.088', $11 = '8767.4', $12 = '8777.9', $13 = '8765.2', $14 = '8774.95', $15 = '4787', $16 = '0', $17 = '2026-02-08 18:11:45.237', $18 = '2026-02-08 18:11:45.088'

9

173ms

6,753

Details

0ms

3ms

0ms

select 1;

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	18	6,753	173ms	0ms

select 1;

Date: 2026-02-08 18:20:46 Duration: 3ms Database: postgres
select 1;

Date: 2026-02-08 18:35:17 Duration: 2ms Database: postgres
select 1;

Date: 2026-02-08 18:50:44 Duration: 2ms Database: postgres

10

154ms

2,219

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 #10

Day	Hour	Count	Duration	Avg duration
	18	2,219	154ms	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 18:11:02 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 18:11:02.796', $10 = '2026-02-08 18:11:02.728', $11 = '26935.7', $12 = '26975.5', $13 = '26930.7', $14 = '26963.8', $15 = '7047', $16 = '0', $17 = '2026-02-08 18:11:02.796', $18 = '2026-02-08 18:11:02.728'
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 18:11:04 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 23:00:00', $2 = '25040.4', $3 = '25050.78', $4 = '24999.65', $5 = '25006.15', $6 = '8557', $7 = '515840248039147300', $8 = '0', $9 = '2026-02-08 18:11:04.858', $10 = '2026-02-08 18:11:04.762', $11 = '25040.4', $12 = '25050.78', $13 = '24999.65', $14 = '25006.15', $15 = '8557', $16 = '0', $17 = '2026-02-08 18:11:04.858', $18 = '2026-02-08 18:11:04.762'
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 18:41:44 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 18:41:44.85', $10 = '2026-02-08 18:41:44.769', $11 = '8774.9', $12 = '8779.45', $13 = '8771.85', $14 = '8775', $15 = '2091', $16 = '0', $17 = '2026-02-08 18:41:44.85', $18 = '2026-02-08 18:41:44.769'

11

115ms

2,543

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 #11

Day	Hour	Count	Duration	Avg duration
	18	2,543	115ms	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 18:47:05 Duration: 0ms Database: postgres parameters: $1 = '2026-02-07 00:45:00', $2 = '4960.7', $3 = '4969.185', $4 = '4958.055', $5 = '4966.94', $6 = '1531', $7 = '515840249390867300', $8 = '0', $9 = '2026-02-08 18:47:05.662', $10 = '2026-02-08 18:47:05.516', $11 = '4960.7', $12 = '4969.185', $13 = '4958.055', $14 = '4966.94', $15 = '1531', $16 = '0', $17 = '2026-02-08 18:47:05.662', $18 = '2026-02-08 18:47:05.516'
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 18:01:16 Duration: 0ms Database: postgres parameters: $1 = '2026-02-07 00:45:00', $2 = '157.1985', $3 = '157.2695', $4 = '157.1865', $5 = '157.225', $6 = '649', $7 = '515840249375237300', $8 = '0', $9 = '2026-02-08 18:01:16.293', $10 = '2026-02-08 18:01:15.987', $11 = '157.1985', $12 = '157.2695', $13 = '157.1865', $14 = '157.225', $15 = '649', $16 = '0', $17 = '2026-02-08 18:01:16.293', $18 = '2026-02-08 18:01:15.987'
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 18:46:40 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 22:30:00', $2 = '8785.07', $3 = '8798.07', $4 = '8784.07', $5 = '8798.07', $6 = '102', $7 = '515840238058964300', $8 = '0', $9 = '2026-02-08 18:46:40.449', $10 = '2026-02-08 18:46:40.411', $11 = '8785.07', $12 = '8798.07', $13 = '8784.07', $14 = '8798.07', $15 = '102', $16 = '0', $17 = '2026-02-08 18:46:40.449', $18 = '2026-02-08 18:46:40.411'

12

40ms

9

Details

3ms

6ms

4ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #12

Day	Hour	Count	Duration	Avg duration
	18	9	40ms	4ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-08 18:21:05 Duration: 6ms Database: postgres parameters: $1 = '627', $2 = '627'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-08 18:07:22 Duration: 6ms Database: postgres parameters: $1 = '667', $2 = '667'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-08 18:31:01 Duration: 5ms Database: postgres parameters: $1 = '627', $2 = '627'

13

19ms

87

Details

0ms

4ms

0ms

/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;

Times Reported Time consuming bind #13

Day	Hour	Count	Duration	Avg duration
	18	87	19ms	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 18:31:15 Duration: 4ms Database: postgres parameters: $1 = '607634366045656301'
/*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 18:21:03 Duration: 4ms Database: postgres parameters: $1 = '607634606625757301'
/*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 18:22:20 Duration: 3ms Database: postgres parameters: $1 = '607634662039583301'

14

12ms

18

Details

0ms

select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;

Times Reported Time consuming bind #14

Day	Hour	Count	Duration	Avg duration
	18	18	12ms	0ms

select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;

Date: 2026-02-08 18:21:02 Duration: 0ms Database: postgres
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;

Date: 2026-02-08 18:21:01 Duration: 0ms Database: postgres
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;

Date: 2026-02-08 18:51:01 Duration: 0ms Database: postgres

15

8ms

23

Details

0ms

2ms

0ms

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

Times Reported Time consuming bind #15

Day	Hour	Count	Duration	Avg duration
	18	23	8ms	0ms

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

Date: 2026-02-08 18:57:18 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 18:33:49 Duration: 1ms Database: postgres parameters: $1 = '607634661176504303'
/*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 18:32:35 Duration: 1ms Database: postgres parameters: $1 = '607634251500653303'

16

7ms

51

Details

0ms

INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Times Reported Time consuming bind #16

Day	Hour	Count	Duration	Avg duration
	18	51	7ms	0ms

INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-08 18:01:36 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 16:00:00', $2 = '55515', $3 = '56290', $4 = '55455', $5 = '56265', $6 = '5788', $7 = '515840230561612300', $8 = '0', $9 = '2026-02-08 18:01:36.889', $10 = '2026-02-08 18:01:36.889', $11 = '55515', $12 = '56290', $13 = '55455', $14 = '56265', $15 = '5788', $16 = '0', $17 = '2026-02-08 18:01:36.889', $18 = '2026-02-08 18:01:36.889'
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-08 18:16:55 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 16:00:00', $2 = '55515', $3 = '56290', $4 = '55455', $5 = '56265', $6 = '5788', $7 = '515840230561612300', $8 = '0', $9 = '2026-02-08 18:16:55.866', $10 = '2026-02-08 18:16:55.866', $11 = '55515', $12 = '56290', $13 = '55455', $14 = '56265', $15 = '5788', $16 = '0', $17 = '2026-02-08 18:16:55.866', $18 = '2026-02-08 18:16:55.866'
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-08 18:32:26 Duration: 0ms Database: postgres parameters: $1 = '2026-02-06 16:00:00', $2 = '55515', $3 = '56290', $4 = '55455', $5 = '56265', $6 = '5788', $7 = '515840230561612300', $8 = '0', $9 = '2026-02-08 18:32:26.486', $10 = '2026-02-08 18:32:26.485', $11 = '55515', $12 = '56290', $13 = '55455', $14 = '56265', $15 = '5788', $16 = '0', $17 = '2026-02-08 18:32:26.486', $18 = '2026-02-08 18:32:26.485'

17

6ms

2

Details

3ms

select * from datafeed_symbols where classname ilike 'ICMARKETS-AU-MT5' limit 5000;

Times Reported Time consuming bind #17

Day	Hour	Count	Duration	Avg duration
	18	2	6ms	3ms

select * from datafeed_symbols where classname ilike 'ICMARKETS-AU-MT5' limit 5000;

Date: 2026-02-08 18:07:19 Duration: 3ms Database: postgres
select * from datafeed_symbols where classname ilike 'ICMARKETS-AU-MT5' limit 5000;

Date: 2026-02-08 18:37:20 Duration: 3ms Database: postgres

18

5ms

104

Details

0ms

SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	18	104	5ms	0ms

SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;

Date: 2026-02-08 18:31:16 Duration: 0ms Database: postgres parameters: $1 = '500991628280939200'
SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;

Date: 2026-02-08 18:22:20 Duration: 0ms Database: postgres parameters: $1 = '515840238055737300'
SELECT df.absolutetimezoneoffset FROM datafeedstimetable df INNER JOIN downloadersymbolsettings dss ON df.classname = dss.classname WHERE dss.symbolid = $1 GROUP BY df.absolutetimezoneoffset LIMIT 1;

Date: 2026-02-08 18:21:03 Duration: 0ms Database: postgres parameters: $1 = '515840243280258300'

19

4ms

7

Details

0ms

2ms

0ms

/*server.FibonacciResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, Exchange AS e, longname as lo, shortname as sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, 1 - errormargin as rq, 1 - noise as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM Fibonacci_Results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN fibonaccipatterns p on a.pattern = p.patternname where resultuid = $1 and dtt.dayofweek = 3;

Times Reported Time consuming bind #19

Day	Hour	Count	Duration	Avg duration
	18	7	4ms	0ms

/*server.FibonacciResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, Exchange AS e, longname as lo, shortname as sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, 1 - errormargin as rq, 1 - noise as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM Fibonacci_Results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN fibonaccipatterns p on a.pattern = p.patternname where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-02-08 18:11:49 Duration: 2ms Database: postgres parameters: $1 = '607635390740045302'
/*server.FibonacciResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, Exchange AS e, longname as lo, shortname as sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, 1 - errormargin as rq, 1 - noise as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM Fibonacci_Results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN fibonaccipatterns p on a.pattern = p.patternname where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-02-08 18:38:22 Duration: 1ms Database: postgres parameters: $1 = '607635390347302302'
/*server.FibonacciResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, Exchange AS e, longname as lo, shortname as sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, 1 - errormargin as rq, 1 - noise as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM Fibonacci_Results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN fibonaccipatterns p on a.pattern = p.patternname where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-02-08 18:05:49 Duration: 0ms Database: postgres parameters: $1 = '607635390347302302'

20

4ms

8

Details

0ms

SELECT DISTINCT ;

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	18	8	4ms	0ms

SELECT DISTINCT ;

Date: 2026-02-08 18:01:35 Duration: 0ms Database: postgres parameters: $1 = '558', $2 = '558'
SELECT DISTINCT ;

Date: 2026-02-08 18:07:32 Duration: 0ms Database: postgres parameters: $1 = '558', $2 = '558'
SELECT DISTINCT ;

Date: 2026-02-08 18:01:35 Duration: 0ms Database: postgres parameters: $1 = '558', $2 = '558'

Log levels

Key values

164,266 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	364	0.22%
DETAIL	35,270	21.47%
LOG	128,236	78.07%
STATEMENT	396	0.24%

Events distribution

Key values

0 PANIC entries
0 FATAL entries
0 ERROR entries
0 WARNING entries

Errors per 5 minutes

NO DATASET

Most Frequent Errors/Events

Key values

0 Max number of times the same event was reported
0 Total events found

Rank	Times reported	Error
NO DATASET

Global information

Overview

Global Stats

SQL Traffic

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SELECT Traffic

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INSERT/UPDATE/DELETE Traffic

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Queries duration

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Prepared queries ratio

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General Activity

Connections

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Connections per database

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Connections per user

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Connections per host

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Sessions

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Histogram of session times

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Sessions per database

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Sessions per user

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Sessions per application

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Checkpoints / Restartpoints

Checkpoints Buffers

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Checkpoints distance

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Checkpoints Activity

Checkpoint causes

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Temporary Files

Size of temporary files

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Number of temporary files

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Temporary Files Activity

Queries generating the most temporary files (N)

Queries generating the largest temporary files

Vacuums

Vacuums / Analyzes Distribution

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Analyzes per table

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Vacuums per table

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Tuples removed per table

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Pages removed per table

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Autovacuum Activity

Locks

Locks by types

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Type of locks

Most frequent waiting queries (N)

Queries that waited the most

Queries

Queries by type

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Queries by database

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Queries by user

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Duration by user