pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Thu Feb 19 04:59:37 2026
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-02-19_060000.log
Parsed 1,279,600 log entries in 35s
Log start from 2026-02-19 06:00:00 to 2026-02-19 06:59:35

Global Stats

1,028 Number of unique normalized queries
180,124 Number of queries
3h10m46s Total query duration
2026-02-19 06:00:00 First query
2026-02-19 06:59:35 Last query
5,448 queries/s at 2026-02-19 06:05:02 Query peak

3h10m46s Total query duration
2m19s Prepare/parse total duration
43s286ms Bind total duration
3h7m43s Execute total duration

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

37 Total number of automatic vacuums
51 Total number of automatic analyzes

955 Number temporary file
157.52 MiB Max size of temporary file
5.58 MiB Average size of temporary file

2,658 Total number of sessions
13 sessions at 2026-02-19 06:58:48 Session peak
3d21h57m10s Total duration of sessions
2m7s Average duration of sessions
67 Average queries per session
4s306ms Average queries duration per session
2m2s Average idle time per session

2,658 Total number of connections
28 connections/s at 2026-02-19 06:18:48 Connection peak
6 Total number of databases

SQL Traffic

Key values

5,448 queries/s Query Peak
2026-02-19 06:05:02 Date

SELECT Traffic

Key values

2,707 queries/s Query Peak
2026-02-19 06:05:02 Date

INSERT/UPDATE/DELETE Traffic

Key values

188 queries/s Query Peak
2026-02-19 06:30:51 Date

Queries duration

Key values

3h10m46s 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 19	06	180,124	0ms	14m30s	62ms	6m9s	7m5s	23m4s

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Feb 19	06	56,340	601	0ms	0ms	0ms	0ms

Day	Hour	INSERT	UPDATE	DELETE	COPY FROM	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Feb 19	06	22,225	1,928	13	78	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Feb 19	06	16,320	49,440	3.03	19.05%

Day	Hour	Count	Average / Second
Feb 19	06	2,658	0.74/s

Day	Hour	Count	Average Duration	Average idle time
Feb 19	06	2,658	2m7s	2m3s

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Established Connections

Key values

28 connections Connection Peak
2026-02-19 06:18:48 Date

Connections per database

Key values

acaweb_fx Main Database
2,658 connections Total

Chart
Table

Database	User	Count
acaweb_fx		2,581
	pg_dump	1
	postgres	2,264
	psql	316
acaweb_fx_integer		1
	pg_dump	1
postgres		3
	pg_dump	1
	psql	2
socialmedia		72
	pg_dump	1
	postgres	71
translations		1
	pg_dump	1

Connections per user

Key values

postgres Main User
2,658 connections Total

Chart
Table

User	Count
pg_dump	5
postgres	2,335
psql	318

Connections per host

Key values

192.168.4.142 Main host with 1278 connections
2,658 Total connections

Chart
Table

Host	Count
127.0.0.1	115
192.168.0.114	2
192.168.0.216	103
192.168.0.74	26
192.168.1.145	139
192.168.1.15	42
192.168.1.20	163
192.168.1.239	14
192.168.1.90	46
192.168.2.126	38
192.168.2.182	12
192.168.3.199	36
192.168.4.14	1
192.168.4.142	1,278
192.168.4.150	10
192.168.4.160	4
192.168.4.197	6
192.168.4.238	10
192.168.4.33	71
192.168.4.94	4
192.168.4.98	330
[local]	208

Simultaneous sessions

Key values

13 sessions Session Peak
2026-02-19 06:58:48 Date

Histogram of session times

Key values

2,193 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	2,193	82.51%
500ms-1s	161	6.06%
1s-30s	214	8.05%
30s-1m	5	0.19%
1m-10m	31	1.17%
10m-30m	29	1.09%
30m-1h	6	0.23%
1h-8h	17	0.64%
> 8h	2	0.08%

Sessions per database

Key values

acaweb_fx Main Database
2,658 sessions Total

Chart
Table

Database	User	Count	Total Duration
acaweb_fx	2,581	3d21h33m41s	2m10s
acaweb_fx_integer	1	20m6s	20m6s
postgres	3	222ms	74ms
socialmedia	72	3m22s	2s819ms
translations	1	161ms	161ms

Sessions per user

Key values

postgres Main User
2,658 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
2,658 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
127.0.0.1	115	37m10s	19s396ms
192.168.0.114	2	10m4s	5m2s
192.168.0.216	103	1m22s	805ms
192.168.0.74	26	3h18m43s	7m38s
192.168.1.145	139	1d4h4m8s	12m6s
192.168.1.15	42	5h12m54s	7m27s
192.168.1.20	163	1d11h46m46s	13m10s
192.168.1.239	14	77ms	5ms
192.168.1.90	46	3m22s	4s407ms
192.168.2.126	38	5s711ms	150ms
192.168.2.182	12	930ms	77ms
192.168.3.199	36	1s441ms	40ms
192.168.4.14	1	209ms	209ms
192.168.4.142	1,278	7m33s	355ms
192.168.4.150	10	20h9m34s	2h57s
192.168.4.160	4	41ms	10ms
192.168.4.197	6	79ms	13ms
192.168.4.238	10	12s641ms	1s264ms
192.168.4.33	71	1m11s	1s12ms
192.168.4.94	4	28s111ms	7s27ms
192.168.4.98	330	24s425ms	74ms
[local]	208	23m2s	6s647ms

Sessions per application

Key values

unknown Main Host
2,658 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	2,658	3d21h57m10s	2m7s

Checkpoints Buffers

Key values

12,864 buffers Checkpoint Peak
2026-02-19 06:07:17 Date
210.007 seconds Highest write time
0.015 seconds Sync time

Checkpoints Wal files

Key values

5 files Wal files usage Peak
2026-02-19 06:07:17 Date

Checkpoints distance

Key values

150.46 Mo Distance Peak
2026-02-19 06:07:17 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Feb 19	06	35,047	1,745.028s	0.07s	1,745.416s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Feb 19	06	0	0	20	1,869	0.009s	0s

Day	Hour	Count	Avg time (sec)
Feb 19	06	0	0s

Day	Hour	Mean distance	Mean estimate
Feb 19	06	28,968.09 kB	58,420.55 kB

↑ Back to the top of the Checkpoint Activity table

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

183.98 MiB Temp Files size Peak
2026-02-19 06:10:07 Date

Number of temporary files

Key values

62 per second Temp Files Peak
2026-02-19 06:17:18 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Feb 19	06	955	5.21 GiB	5.58 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	45	153.09 MiB	3.22 MiB	3.57 MiB	3.40 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: 2026-02-19 06:02:29 Duration: 0ms
2	44	177.83 MiB	3.93 MiB	4.15 MiB	4.04 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: 2026-02-19 06:01:58 Duration: 0ms
3	30	1.65 GiB	3.83 MiB	157.52 MiB	56.32 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = ? ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?; with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; Date: 2026-02-19 06:00:07 Duration: 0ms
4	24	87.36 MiB	3.63 MiB	3.65 MiB	3.64 MiB	jr.resultuid as resultuid, jr.direction as direction, jr.patternendtime as identified, jr.patternlengthbars as length, jr.patternstarttime as patternstarttime, case when jr.trendchangeid = ? then ? else ? end as trendchange, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, jp.patternname as pattern_name, dtt.timezone as timezone, ? as age, cps.pip, g.basegroupname from japsticks_results jr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = jr.symbolid inner join relevance_japsticks_results rar on rar.resultuid = jr.resultuid inner join symbols s on jr.symbolid = s.symbolid and s.nonliquid = ? inner join japsticks_patterns jp on jr.patternid = jp.id inner join downloadersymbolsettings dss on jr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where jr.gmttimefound > now() - interval ? and s.deleted = ? and (jr.simulation = ? or jr.simulation is null) and (rar.relevant = ?) --and (semicolon_age = ? or rar.age <= semicolon_age) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or jp.patternname in (...)) and (? = ? or jr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results order by symbolid, resultuid ) select * from results order by identified desc, length desc ; jr.resultuid AS resultuid, jr.direction AS direction, jr.patternendtime AS identified, jr.patternlengthbars AS length, jr.patternstarttime AS patternstarttime, case when jr.trendchangeid = 1 then 'Continuation' else 'Reversal' end AS trendchange, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, jp.patternname AS pattern_name, dtt.timezone AS timezone, 0 AS age, cps.pip, g.basegroupname FROM japsticks_results jr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = jr.symbolid INNER JOIN relevance_japsticks_results rar ON rar.resultuid = jr.resultuid INNER JOIN symbols s ON jr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN japsticks_patterns jp ON jr.patternid = jp.id INNER JOIN downloadersymbolsettings dss ON jr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE jr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (jr.simulation = 0 OR jr.simulation IS NULL) AND (rar.relevant = 1) --AND (semicolon_age = 0 OR rar.age <= semicolon_age) AND ($2 = 0 OR s.timegranularity in ($3)) AND ($4 = 0 OR s.exchange in ($5)) AND ($6 = 0 OR coalesce(bim.code, s.symbol) in ($7)) AND ($8 = 0 OR jp.patternname in ($9)) AND ($10 = 0 OR jr.patternlengthbars <= $11)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-02-19 06:02:48 Duration: 0ms
5	13	599.93 MiB	46.15 MiB	46.15 MiB	46.15 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: 2026-02-19 06:01:12 Duration: 0ms
6	13	1018.37 MiB	78.34 MiB	78.34 MiB	78.34 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: 2026-02-19 06:01:15 Duration: 0ms
7	8	1.10 GiB	140.22 MiB	140.26 MiB	140.23 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2026-02-19 06:02:18 Duration: 0ms
8	4	356.50 MiB	89.09 MiB	89.18 MiB	89.13 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2026-02-19 06:02:05 Duration: 0ms
9	1	3.93 MiB	3.93 MiB	3.93 MiB	3.93 MiB	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 = ?; 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 = $1 AND dss.downloadfrequency = $2 AND dss.symbolid = t.symbolid AND s.symbolid = dss.symbolid AND dss.enabled = 1 AND s.deleted = 0 AND dss.downloadersymbol IN ($3) AND t.pricedatetime > now() - INTERVAL '2 days') AS ranked_candles_table WHERE rn = 1; Date: 2026-02-19 06:12:21 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	157.52 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-19 06:20:13 ]
2	157.52 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-19 06:30:12 ]
3	140.26 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-19 06:32:29 ]
4	140.25 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-19 06:47:32 ]
5	140.24 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-19 06:50:34 ]
6	140.24 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-19 06:17:29 ]
7	140.24 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-19 06:35:39 ]
8	140.22 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-19 06:20:36 ]
9	140.22 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-19 06:02:18 ]
10	140.22 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-19 06:05:32 ]
11	130.48 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-19 06:00:05 ]
12	124.30 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-19 06:50:08 ]
13	89.98 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-19 06:10:04 ]
14	89.69 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-19 06:20:09 ]
15	89.18 MiB	select updateageforrelevantresults (); [ Date: 2026-02-19 06:02:05 ]
16	89.14 MiB	select updateageforrelevantresults (); [ Date: 2026-02-19 06:32:10 ]
17	89.09 MiB	select updateageforrelevantresults (); [ Date: 2026-02-19 06:17:09 ]
18	89.09 MiB	select updateageforrelevantresults (); [ Date: 2026-02-19 06:47:14 ]
19	85.20 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-19 06:40:25 ]
20	83.76 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-19 06:40:25 ]

Vacuums / Analyzes Distribution

Key values

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

Analyzes per table

Key values

public.solr_relevance_old (13) Main table analyzed (database acaweb_fx)
51 analyzes Total

Chart
Table

Table	Number of analyzes
acaweb_fx.public.solr_relevance_old	13
acaweb_fx.pg_catalog.pg_attribute	8
acaweb_fx.pg_catalog.pg_class	4
acaweb_fx.pg_catalog.pg_type	4
acaweb_fx.public.datafeeds_latestrun	3
acaweb_fx.public.relevance_keylevels_results	3
acaweb_fx.public.relevance_autochartist_results	3
acaweb_fx.pg_catalog.pg_index	2
acaweb_fx.public.latest_t15_candle_view	2
acaweb_fx.pg_catalog.pg_depend	2
acaweb_fx.public.relevance_fibonacci_results	2
acaweb_fx.public.autochartist_symbolupdates	1
acaweb_fx.public.latest_candle_datetime_per_receng	1
acaweb_fx.public.relevance_consecutivecandles_results	1
acaweb_fx.public.symbollatestupdatetime	1
acaweb_fx.public.t15	1
Total	51

Vacuums per table

Key values

public.solr_relevance_old (13) Main table vacuumed on database acaweb_fx
37 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	13	13	9,842	0	50	0	0	7,068	819	4,089,168
acaweb_fx.pg_catalog.pg_attribute	6	4	4,207	0	482	0	402	1,377	397	2,357,397
acaweb_fx.public.datafeeds_latestrun	3	0	359	0	6	0	0	33	5	37,297
acaweb_fx.pg_catalog.pg_type	2	2	314	0	59	0	0	162	35	186,618
acaweb_fx.public.relevance_keylevels_results	2	2	7,012	0	533	4	198	1,814	530	1,781,750
acaweb_fx.pg_catalog.pg_class	2	2	927	0	101	0	0	287	93	452,774
acaweb_fx.public.relevance_autochartist_results	2	2	6,522	0	330	2	501	1,271	314	996,678
acaweb_fx.public.relevance_fibonacci_results	2	2	2,279	0	69	0	101	320	135	453,468
acaweb_fx.pg_catalog.pg_index	1	1	97	0	15	0	0	31	12	84,567
acaweb_fx.pg_toast.pg_toast_2619	1	1	130	0	25	0	0	93	23	75,540
acaweb_fx.public.autochartist_symbolupdates	1	1	22,657	0	492	3	38,542	5,383	433	527,079
acaweb_fx.pg_catalog.pg_statistic	1	1	958	0	220	0	582	563	239	869,858
acaweb_fx.public.latest_t15_candle_view	1	1	66	0	1	0	0	6	1	9,031
Total	37	32	55,370	48,002	2,383	9	40,326	18,408	3,036	11,921,225

Tuples removed per table

Key values

public.solr_relevance_old (56587) Main table with removed tuples on database acaweb_fx
75286 tuples Total removed

Chart
Table

		Index	Tuples			Pages
Table	Vacuums	scans	removed	remain	not yet removable	removed	remain
acaweb_fx.public.solr_relevance_old	13	13	56,587	73,785	3,613	0	2,410
acaweb_fx.pg_catalog.pg_attribute	6	4	7,540	70,321	6,845	29	1,589
acaweb_fx.public.autochartist_symbolupdates	1	1	5,454	48,417	68	0	40,691
acaweb_fx.public.relevance_keylevels_results	2	2	2,147	23,996	0	0	558
acaweb_fx.public.relevance_autochartist_results	2	2	1,140	16,284	0	0	760
acaweb_fx.pg_catalog.pg_statistic	1	1	768	3,735	0	0	1,194
acaweb_fx.pg_catalog.pg_type	2	2	753	2,932	36	2	88
acaweb_fx.pg_catalog.pg_class	2	2	463	3,354	54	0	300
acaweb_fx.public.relevance_fibonacci_results	2	2	146	2,852	22	0	204
acaweb_fx.public.datafeeds_latestrun	3	0	136	70	28	0	48
acaweb_fx.pg_toast.pg_toast_2619	1	1	82	174	8	0	52
acaweb_fx.public.latest_t15_candle_view	1	1	55	14	0	0	1
acaweb_fx.pg_catalog.pg_index	1	1	15	813	0	1	22
Total	37	32	75,286	246,747	10,674	32	47,917

Pages removed per table

Key values

pg_catalog.pg_attribute (29) Main table with removed pages on database acaweb_fx
32 pages Total removed

Chart
Table

Table	Number of vacuums	Index scans	Tuples removed	Pages removed
acaweb_fx.pg_catalog.pg_attribute	6	4	7540	29
acaweb_fx.pg_catalog.pg_type	2	2	753	2
acaweb_fx.pg_catalog.pg_index	1	1	15	1
acaweb_fx.pg_toast.pg_toast_2619	1	1	82	0
acaweb_fx.public.datafeeds_latestrun	3	0	136	0
acaweb_fx.public.autochartist_symbolupdates	1	1	5454	0
acaweb_fx.pg_catalog.pg_statistic	1	1	768	0
acaweb_fx.public.latest_t15_candle_view	1	1	55	0
acaweb_fx.public.relevance_keylevels_results	2	2	2147	0
acaweb_fx.pg_catalog.pg_class	2	2	463	0
acaweb_fx.public.solr_relevance_old	13	13	56587	0
acaweb_fx.public.relevance_autochartist_results	2	2	1140	0
acaweb_fx.public.relevance_fibonacci_results	2	2	146	0
Total	37	32	75,286	32

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Feb 19	06	37	51

↑ Back to the top of the Autovacuum Activity table

Locks by types

Key values

AccessShareLock Main Lock Type
6 locks Total

Chart
Table

Type	Object	Count	Total Duration	Average Duration (s)
AccessExclusiveLock		2	17m11s	8m35s
	relation	2	17m11s	8m35s
AccessShareLock		4	6m58s	1m44s
	relation	4	6m58s	1m44s
	Total	6	24m10s	4m1s

Most frequent waiting queries (N)

Rank	Count	Total time	Min time	Max time	Avg duration	Query
1	1	14m30s	14m30s	14m30s	14m30s	truncate table solr_relevance_old; TRUNCATE TABLE solr_relevance_old; Date: 2026-02-19 06:19:42
2	2	4m45s	2m14s	2m31s	2m22s	select datetimeupdate from latest_candle_datetime_per_receng where recognitionengine ilike ?; SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'IQFEED_FX - 1'; Date: 2026-02-19 06:19:43
3	1	2m40s	2m40s	2m40s	2m40s	refresh materialized view latest_candle_datetime_per_receng; refresh materialized view latest_candle_datetime_per_receng; Date: 2026-02-19 06:19:42
4	2	2m13s	28s913ms	1m44s	1m6s	select recognitionengine, to_char(datetimeupdate, ?) from latest_candle_datetime_per_receng; select recognitionengine, to_char(datetimeupdate, 'yyyy-mm-dd HH24:MI') from latest_candle_datetime_per_receng; Date: 2026-02-19 06:19:43

Queries that waited the most

Rank	Wait time	Query
1	14m30s	TRUNCATE TABLE solr_relevance_old; [ Date: 2026-02-19 06:19:42 ]
2	2m40s	refresh materialized view latest_candle_datetime_per_receng; [ Date: 2026-02-19 06:19:42 ]
3	2m31s	SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'PEPPERSTONE - 1'; [ Date: 2026-02-19 06:19:43 ]
4	2m14s	SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'IQFEED_FX - 1'; [ Date: 2026-02-19 06:19:43 ]
5	1m44s	select recognitionengine, to_char(datetimeupdate, 'yyyy-mm-dd HH24:MI') from latest_candle_datetime_per_receng; [ Date: 2026-02-19 06:19:43 ]
6	28s913ms	select recognitionengine, to_char(datetimeupdate, 'yyyy-mm-dd HH24:MI') from latest_candle_datetime_per_receng; [ Date: 2026-02-19 06:19:43 ]

Queries by type

Key values

56,340 Total read queries
29,322 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	56,340	31.28%
INSERT	22,225	12.34%
UPDATE	1,928	1.07%
DELETE	13	0.01%
COPY FROM	78	0.04%
COPY TO	601	0.33%
CTE	3,781	2.10%
DDL	13	0.01%
TCL	683	0.38%
CURSOR	0	0.00%
OTHERS	94,462	52.44%

Queries by database

Key values

unknown Main database
179,233 Requests
3h7m43s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	814	0ms
	copy from	65	0ms
	copy to	26	0ms
	cte	85	0ms
	ddl	13	0ms
	delete	13	0ms
	others	169	0ms
	select	73	0ms
	tcl	332	0ms
	update	38	0ms
acaweb_fx_integer	Total	1	0ms
	select	1	0ms
postgres	Total	3	0ms
	select	3	0ms
socialmedia	Total	72	0ms
	select	72	0ms
translations	Total	1	0ms
	select	1	0ms
unknown	Total	179,233	3h7m43s
	copy from	13	0ms
	copy to	575	0ms
	cte	3,696	0ms
	insert	22,225	0ms
	others	4,466	0ms
	select	56,190	0ms
	tcl	351	0ms
	update	1,890	0ms

Queries by user

Key values

unknown Main user
179,233 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	891	0ms
	copy from	65	0ms
	copy to	26	0ms
	cte	85	0ms
	ddl	13	0ms
	delete	13	0ms
	others	169	0ms
	select	150	0ms
	tcl	332	0ms
	update	38	0ms
unknown	Total	179,233	3h7m43s
	copy from	13	0ms
	copy to	575	0ms
	cte	3,696	0ms
	insert	22,225	0ms
	others	4,466	0ms
	select	56,190	0ms
	tcl	351	0ms
	update	1,890	0ms

Duration by user

Key values

3h7m43s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	891	0ms
	copy from	65	0ms
	copy to	26	0ms
	cte	85	0ms
	ddl	13	0ms
	delete	13	0ms
	others	169	0ms
	select	150	0ms
	tcl	332	0ms
	update	38	0ms
unknown	Total	179,233	3h7m43s
	copy from	13	0ms
	copy to	575	0ms
	cte	3,696	0ms
	insert	22,225	0ms
	others	4,466	0ms
	select	56,190	0ms
	tcl	351	0ms
	update	1,890	0ms

Queries by host

Key values

unknown Main host
180,124 Requests
3h7m43s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	180,124	3h7m43s
	copy from	78	0ms
	copy to	601	0ms
	cte	3,781	0ms
	ddl	13	0ms
	delete	13	0ms
	insert	22,225	0ms
	others	4,635	0ms
	select	56,340	0ms
	tcl	683	0ms
	update	1,928	0ms

Queries by application

Key values

unknown Main application
179,801 Requests
3h7m43s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
pg_dump	Total	5	0ms
	select	5	0ms
psql	Total	318	0ms
	copy from	65	0ms
	copy to	26	0ms
	cte	85	0ms
	ddl	13	0ms
	delete	13	0ms
	others	4	0ms
	select	74	0ms
	update	38	0ms
unknown	Total	179,801	3h7m43s
	copy from	13	0ms
	copy to	575	0ms
	cte	3,696	0ms
	insert	22,225	0ms
	others	4,631	0ms
	select	56,261	0ms
	tcl	683	0ms
	update	1,890	0ms

Number of cancelled queries

Key values

1 per second Cancelled query Peak
2026-02-19 06:13:11 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

54,380 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	54,380	60.54%
1-5ms	28,306	31.51%
5-10ms	2,601	2.90%
10-25ms	2,185	2.43%
25-50ms	394	0.44%
50-100ms	305	0.34%
100-500ms	451	0.50%
500-1000ms	116	0.13%
1000-10000ms	829	0.92%
> 10000ms	260	0.29%

Slowest individual queries

Rank	Duration	Query
NO DATASET

Time consuming queries

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

0ms

1

Details

0ms

lock table public.stats_hrs_summary_by_groups in access share mode;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1	0ms	0ms

2

0ms

2

Details

0ms

lock table public.timezones_korean in access share mode;

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

3

0ms

13

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 #3

Day	Hour	Count	Duration	Avg duration
Feb 19	06	13	0ms	0ms

4

0ms

2

Details

0ms

copy public.t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived, pricesadjusted, relevanceprocessed, recengprocessedadjusted, historical) to stdout;

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

5

0ms

1

Details

0ms

copy public.processresults (id, processid, resultdate, shorttext, longtext, title, test) to stdout;

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1	0ms	0ms

6

0ms

2,132

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 19	06	2,132	0ms	0ms

7

0ms

976

Details

0ms

select oid, tableoid, pol.polname, pol.polcmd, pol.polpermissive, case when pol.polroles = ? then null else pg_catalog.array_to_string(array ( select pg_catalog.quote_ident(rolname) from pg_catalog.pg_roles where oid = any (pol.polroles)), ?) end as polroles, pg_catalog.pg_get_expr(pol.polqual, pol.polrelid) as polqual, pg_catalog.pg_get_expr(pol.polwithcheck, pol.polrelid) as polwithcheck from pg_catalog.pg_policy pol where polrelid = ?;

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Feb 19	06	976	0ms	0ms

8

0ms

2

Details

0ms

copy public.timezones_greek (timezoneid, timezone) to stdout;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

9

0ms

2

Details

0ms

lock table public.futures_symbols in access share mode;

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

10

0ms

2

Details

0ms

copy archive.autochartist_results (resultid, bandwidth, pattern, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, qtytp, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, symbolid, resultuid, relevancestartdistance, simulation, writtendatetime, old_resultuid) to stdout;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

11

0ms

2

Details

0ms

copy public.satelliteauthentication (id, satelliteserverid, brokerid, authenticationstatus, maketradeurl, notifications, validusername, validpassword, enabled) to stdout;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

12

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 #12

Day	Hour	Count	Duration	Avg duration
Feb 19	06	18	0ms	0ms

13

0ms

5

Details

0ms

select s.tableoid, s.oid, s.subname, ( select rolname from pg_catalog.pg_roles where oid = s.subowner) as rolname, s.subconninfo, s.subslotname, s.subsynccommit, s.subpublications from pg_subscription s where s.subdbid = ( select oid from pg_database where datname = current_database());

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Feb 19	06	5	0ms	0ms

14

0ms

1

Details

0ms

select usename, array_to_string(array ( select quote_ident(option_name) || ? || quote_literal(option_value) from pg_options_to_table(umoptions) order by option_name), e ?) as umoptions from pg_user_mappings where srvid = ? order by usename;

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1	0ms	0ms

15

0ms

2

Details

0ms

copy archive.sa_hist_consecutivecandles (id, symbolid, datetime, image, qty, percentile, direction, lastupdated, height) to stdout;

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

16

0ms

1

Details

0ms

copy public.commoncontenttypeparams (id, name, required, description, "default", type) to stdout;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1	0ms	0ms

17

0ms

319

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 #17

Day	Hour	Count	Duration	Avg duration
Feb 19	06	319	0ms	0ms

18

0ms

2

Details

0ms

lock table public.powerstats in access share mode;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

19

0ms

4

Details

0ms

select oid, enumlabel from pg_catalog.pg_enum where enumtypid = ? order by enumsortorder;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 19	06	4	0ms	0ms

20

0ms

2

Details

0ms

lock table public.market_report_results in access share mode;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

12,737

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 19	06	12,737	0ms	0ms

2

7,246

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 #2

Day	Hour	Count	Duration	Avg duration
Feb 19	06	7,246	0ms	0ms

3

6,012

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 #3

Day	Hour	Count	Duration	Avg duration
Feb 19	06	6,012	0ms	0ms

4

5,698

Details

0ms

insert into t15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Feb 19	06	5,698	0ms	0ms

5

4,036

Details

0ms

insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Feb 19	06	4,036	0ms	0ms

6

3,477

Details

0ms

insert into autochartist_results (resultid, symbolid, bandwidth, pattern, qtytp, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, relevancestartdistance, simulation, writtendatetime) values (?, ?, ?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Feb 19	06	3,477	0ms	0ms

7

3,323

Details

0ms

select datid, datname, pid, usesysid, usename, application_name, client_addr, client_hostname, client_port, backend_start, xact_start, query_start, state_change, wait_event_type, wait_event, state, backend_xid, backend_xmin, query, backend_type from pg_stat_activity where backend_type != ? or (coalesce(trim(query), ?) != ? and pid != pg_backend_pid() and query_start is not null and datname not ilike ? and datname not ilike ? and datname not ilike ? and datname not ilike ? and not (query_start < ?::timestamptz and state = ?));

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Feb 19	06	3,323	0ms	0ms

8

3,243

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 #8

Day	Hour	Count	Duration	Avg duration
Feb 19	06	3,243	0ms	0ms

9

2,132

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 #9

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2,132	0ms	0ms

10

1,870

Details

0ms

insert into fibonacci_results (bandwidth, pattern, gmttimefound, direction, patternstarttime, patternendtime, patternstartprice, patternendprice, qtytp, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, patternlengthbars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) values (?.?, ?, ?::timestamp without time zone, ?, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?, ?, ?, ?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1,870	0ms	0ms

11

1,727

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1,727	0ms	0ms

12

1,701

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1,701	0ms	0ms

13

1,664

Details

0ms

select pg_catalog.format_type(?::pg_catalog.oid, null);

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1,664	0ms	0ms

14

1,471

Details

0ms

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

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1,471	0ms	0ms

15

1,194

Details

0ms

select mode, locktype, pn.nspname, pd.datname, pc.relname, granted, fastpath, count(*) as lock_count from pg_locks l join pg_database pd on (l.database = pd.oid) join pg_class pc on (l.relation = pc.oid) left join pg_namespace pn on (pn.oid = pc.relnamespace) where ((relname ~ ?)) and l.mode is not null and pc.relname not like ? escape ? group by pd.datname, pc.relname, pn.nspname, locktype, mode, granted, fastpath;

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1,194	0ms	0ms

16

1,194

Details

0ms

select relname, schemaname, seq_scan, seq_tup_read, idx_scan, idx_tup_fetch, n_tup_ins, n_tup_upd, n_tup_del, n_tup_hot_upd, n_live_tup, n_dead_tup, vacuum_count, autovacuum_count, analyze_count, autoanalyze_count, extract(epoch from age(current_timestamp, last_vacuum)), extract(epoch from age(current_timestamp, last_autovacuum)), extract(epoch from age(current_timestamp, last_analyze)), extract(epoch from age(current_timestamp, last_autoanalyze)) from pg_stat_user_tables where ((relname ~ ?));

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1,194	0ms	0ms

17

1,193

Details

0ms

select relname, schemaname, indexrelname, idx_scan, idx_tup_read, idx_tup_fetch, pg_relation_size(indexrelid) as index_size from pg_stat_user_indexes where ((relname ~ ?));

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1,193	0ms	0ms

18

1,193

Details

0ms

select relname, schemaname, heap_blks_read, heap_blks_hit, idx_blks_read, idx_blks_hit, toast_blks_read, toast_blks_hit, tidx_blks_read, tidx_blks_hit from pg_statio_user_tables where ((relname ~ ?));

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1,193	0ms	0ms

19

1,190

Details

0ms

select n.nspname as schemaname, count(*) from ( select c.relnamespace from pg_class c where c.relkind in (...)) as subquery left join pg_namespace n on (n.oid = relnamespace) where n.nspname not in (...) group by n.nspname;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1,190	0ms	0ms

20

1,190

Details

0ms

select current_database(), s.schemaname, s.table, s.partition_of, s.relpages, s.reltuples, s.relallvisible, s.relation_size + s.toast_size, s.relation_size, s.index_size, s.toast_size, s.relation_size + s.index_size + s.toast_size from ( select n.nspname as schemaname, relname as table, i.inhparent::regclass as partition_of, c.relpages, c.reltuples, c.relallvisible, pg_relation_size(c.oid) as relation_size, case when c.relhasindex then pg_indexes_size(c.oid) else ? end as index_size, case when c.reltoastrelid > ? then pg_relation_size(c.reltoastrelid) else ? end as toast_size from pg_class c left join pg_namespace n on (n.oid = c.relnamespace) left join pg_inherits i on (i.inhrelid = c.oid) left join pg_locks l on c.oid = l.relation and l.locktype = ? where not (nspname = any (?)) and (l.relation is null or l.mode <> ? or not l.granted) and relkind = ? and ((relname ~ ?)) limit ?) as s;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1,190	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

1

Details

0ms

lock table public.stats_hrs_summary_by_groups in access share mode;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1	0ms	0ms

2

0ms

2

Details

0ms

lock table public.timezones_korean in access share mode;

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

3

0ms

13

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 #3

Day	Hour	Count	Duration	Avg duration
Feb 19	06	13	0ms	0ms

4

0ms

2

Details

0ms

copy public.t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived, pricesadjusted, relevanceprocessed, recengprocessedadjusted, historical) to stdout;

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

5

0ms

1

Details

0ms

copy public.processresults (id, processid, resultdate, shorttext, longtext, title, test) to stdout;

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1	0ms	0ms

6

0ms

2,132

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 19	06	2,132	0ms	0ms

7

0ms

976

Details

0ms

select oid, tableoid, pol.polname, pol.polcmd, pol.polpermissive, case when pol.polroles = ? then null else pg_catalog.array_to_string(array ( select pg_catalog.quote_ident(rolname) from pg_catalog.pg_roles where oid = any (pol.polroles)), ?) end as polroles, pg_catalog.pg_get_expr(pol.polqual, pol.polrelid) as polqual, pg_catalog.pg_get_expr(pol.polwithcheck, pol.polrelid) as polwithcheck from pg_catalog.pg_policy pol where polrelid = ?;

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Feb 19	06	976	0ms	0ms

8

0ms

2

Details

0ms

copy public.timezones_greek (timezoneid, timezone) to stdout;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

9

0ms

2

Details

0ms

lock table public.futures_symbols in access share mode;

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

10

0ms

2

Details

0ms

copy archive.autochartist_results (resultid, bandwidth, pattern, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, qtytp, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, symbolid, resultuid, relevancestartdistance, simulation, writtendatetime, old_resultuid) to stdout;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

11

0ms

2

Details

0ms

copy public.satelliteauthentication (id, satelliteserverid, brokerid, authenticationstatus, maketradeurl, notifications, validusername, validpassword, enabled) to stdout;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

12

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 #12

Day	Hour	Count	Duration	Avg duration
Feb 19	06	18	0ms	0ms

13

0ms

5

Details

0ms

select s.tableoid, s.oid, s.subname, ( select rolname from pg_catalog.pg_roles where oid = s.subowner) as rolname, s.subconninfo, s.subslotname, s.subsynccommit, s.subpublications from pg_subscription s where s.subdbid = ( select oid from pg_database where datname = current_database());

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Feb 19	06	5	0ms	0ms

14

0ms

1

Details

0ms

select usename, array_to_string(array ( select quote_ident(option_name) || ? || quote_literal(option_value) from pg_options_to_table(umoptions) order by option_name), e ?) as umoptions from pg_user_mappings where srvid = ? order by usename;

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1	0ms	0ms

15

0ms

2

Details

0ms

copy archive.sa_hist_consecutivecandles (id, symbolid, datetime, image, qty, percentile, direction, lastupdated, height) to stdout;

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

16

0ms

1

Details

0ms

copy public.commoncontenttypeparams (id, name, required, description, "default", type) to stdout;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 19	06	1	0ms	0ms

17

0ms

319

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 #17

Day	Hour	Count	Duration	Avg duration
Feb 19	06	319	0ms	0ms

18

0ms

2

Details

0ms

lock table public.powerstats in access share mode;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

19

0ms

4

Details

0ms

select oid, enumlabel from pg_catalog.pg_enum where enumtypid = ? order by enumsortorder;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 19	06	4	0ms	0ms

20

0ms

2

Details

0ms

lock table public.market_report_results in access share mode;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2	0ms	0ms

Time consuming prepare


Date: 2026-02-19 06:19:43
Duration: 1m44s
Database: postgres
Date: 2026-02-19 06:47:21
Duration: 13ms
Database: postgres
Date: 2026-02-19 06:37:01
Duration: 13ms
Database: postgres
Date: 2026-02-19 06:25:55
Duration: 22ms
Database: postgres
Date: 2026-02-19 06:30:53
Duration: 2ms
Database: postgres
Date: 2026-02-19 06:12:17
Duration: 3ms
Database: postgres
Date: 2026-02-19 06:30:59
Duration: 1ms
Database: postgres
Date: 2026-02-19 06:05:24
Duration: 0ms
Database: postgres
Date: 2026-02-19 06:02:11
Duration: 0ms
Database: postgres
Date: 2026-02-19 06:36:00
Duration: 8ms
Database: postgres
Date: 2026-02-19 06:40:03
Duration: 22ms
Database: postgres
Date: 2026-02-19 06:36:43
Duration: 7ms
Database: postgres
Date: 2026-02-19 06:51:00
Duration: 3ms
Database: postgres
Date: 2026-02-19 06:12:48
Duration: 0ms
Database: postgres
Date: 2026-02-19 06:30:53
Duration: 6ms
Database: postgres
Date: 2026-02-19 06:12:17
Duration: 0ms
Database: postgres
Date: 2026-02-19 06:16:04
Duration: 0ms
Database: postgres
Date: 2026-02-19 06:50:45
Duration: 1ms
Database: postgres
Date: 2026-02-19 06:30:03
Duration: 3ms
Database: postgres
Date: 2026-02-19 06:20:04
Duration: 3ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

29s413ms

2,785

Details

0ms

59ms

10ms

WITH rar_max as ( ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Feb 19	06	2,785	29s413ms	10ms

WITH rar_max as ( ;

Date: 2026-02-19 06:31:16 Duration: 59ms Database: postgres parameters: $1 = '607697496748959302', $2 = '607697496748959302', $3 = '607697496748959302'
WITH rar_max as ( ;

Date: 2026-02-19 06:26:06 Duration: 58ms Database: postgres parameters: $1 = 't', $2 = '489', $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'
WITH rar_max as ( ;

Date: 2026-02-19 06:12:58 Duration: 51ms 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

6s256ms

15,771

Details

0ms

16ms

0ms

SELECT ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	06	15,771	6s256ms	0ms

SELECT ;

Date: 2026-02-19 06:24:59 Duration: 16ms Database: postgres parameters: $1 = '515840233925362300'
SELECT ;

Date: 2026-02-19 06:25:02 Duration: 10ms Database: postgres parameters: $1 = '500991628204999200'
SELECT ;

Date: 2026-02-19 06:52:01 Duration: 10ms Database: postgres parameters: $1 = '515840233916163300'

3

3s93ms

1,239

Details

1ms

13ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	06	1,239	3s93ms	2ms

SELECT symbolid, ;

Date: 2026-02-19 06:30:57 Duration: 13ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '30', $3 = 'NZDCAD', $4 = 'NZDUSD', $5 = 'NAS100', $6 = 'NEOUSD', $7 = 'NZDJPY', $8 = 'NZDCHF', $9 = 'NOKJPY'
SELECT symbolid, ;

Date: 2026-02-19 06:15:55 Duration: 9ms Database: postgres parameters: $1 = 'AXIORY', $2 = '15', $3 = 'CADCHF', $4 = 'CHFHUF', $5 = 'CADJPY', $6 = 'CHFJPY'
SELECT symbolid, ;

Date: 2026-02-19 06:30:53 Duration: 9ms Database: postgres parameters: $1 = 'ICMARKETS-AU-MT5', $2 = '15', $3 = 'SUN.ASX'

4

916ms

516

Details

1ms

34ms

1ms

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

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	06	516	916ms	1ms

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

Date: 2026-02-19 06:31:05 Duration: 34ms Database: postgres parameters: $1 = 'FPMARKETS'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-02-19 06:30:53 Duration: 2ms Database: postgres parameters: $1 = 'DXFEED_FX'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-02-19 06:30:55 Duration: 2ms Database: postgres parameters: $1 = 'GLOBALGTMT5'

5

501ms

53

Details

4ms

30ms

9ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	06	53	501ms	9ms

WITH last_candle AS ( ;

Date: 2026-02-19 06:36:00 Duration: 30ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-02-19 06:32:06 Duration: 21ms Database: postgres parameters: $1 = '667', $2 = '667'
WITH last_candle AS ( ;

Date: 2026-02-19 06:52:03 Duration: 18ms Database: postgres parameters: $1 = '667', $2 = '667'

6

471ms

17

Details

0ms

54ms

27ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	06	17	471ms	27ms

with wh_patitioned as ( ;

Date: 2026-02-19 06:21:16 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: 2026-02-19 06:08:04 Duration: 47ms 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: 2026-02-19 06:28:01 Duration: 45ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'

7

455ms

12,629

Details

0ms

13ms

0ms

select 1;

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	06	12,629	455ms	0ms

select 1;

Date: 2026-02-19 06:06:08 Duration: 13ms Database: postgres
select 1;

Date: 2026-02-19 06:06:04 Duration: 12ms Database: postgres
select 1;

Date: 2026-02-19 06:08:01 Duration: 10ms Database: postgres

8

383ms

8

Details

29ms

76ms

47ms

with sym_info as ( ;

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	06	8	383ms	47ms

with sym_info as ( ;

Date: 2026-02-19 06:06:51 Duration: 76ms Database: postgres parameters: $1 = '627', $2 = 'Forex', $3 = 'Forex', $4 = '627', $5 = 'Forex', $6 = '627', $7 = '627', $8 = 'Forex', $9 = '627'
with sym_info as ( ;

Date: 2026-02-19 06:36:43 Duration: 58ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
with sym_info as ( ;

Date: 2026-02-19 06:36:58 Duration: 45ms Database: postgres parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'

9

287ms

48

Details

0ms

19ms

5ms

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

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	06	48	287ms	5ms

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

Date: 2026-02-19 06:16:07 Duration: 19ms Database: postgres parameters: $1 = '489', $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: 2026-02-19 06:06:15 Duration: 18ms Database: postgres parameters: $1 = '489', $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: 2026-02-19 06:26:17 Duration: 18ms Database: postgres parameters: $1 = '489', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

10

276ms

5,698

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 #10

Day	Hour	Count	Duration	Avg duration
	06	5,698	276ms	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: 2026-02-19 06:47:28 Duration: 0ms Database: postgres parameters: $1 = '2026-02-19 07:30:00', $2 = '557.245', $3 = '558.29', $4 = '557.185', $5 = '557.79', $6 = '231', $7 = '515840249398052300', $8 = '0', $9 = '2026-02-19 06:47:28.131', $10 = '2026-02-19 06:47:28.031', $11 = '557.245', $12 = '558.29', $13 = '557.185', $14 = '557.79', $15 = '231', $16 = '0', $17 = '2026-02-19 06:47:28.131', $18 = '2026-02-19 06:47:28.031'
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: 2026-02-19 06:55:57 Duration: 0ms Database: postgres parameters: $1 = '2026-02-19 06:15:00', $2 = '6882.78', $3 = '6883.3', $4 = '6879.28', $5 = '6880.18', $6 = '1601', $7 = '515840248032019300', $8 = '0', $9 = '2026-02-19 06:55:57.891', $10 = '2026-02-19 06:55:57.79', $11 = '6882.78', $12 = '6883.3', $13 = '6879.28', $14 = '6880.18', $15 = '1601', $16 = '0', $17 = '2026-02-19 06:55:57.891', $18 = '2026-02-19 06:55:57.79'
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: 2026-02-19 06:25:59 Duration: 0ms Database: postgres parameters: $1 = '2026-02-19 05:45:00', $2 = '49639.3', $3 = '49660.25', $4 = '49633', $5 = '49654.3', $6 = '1994', $7 = '515840248000537300', $8 = '0', $9 = '2026-02-19 06:25:59.714', $10 = '2026-02-19 06:25:59.644', $11 = '49639.3', $12 = '49660.25', $13 = '49633', $14 = '49654.3', $15 = '1994', $16 = '0', $17 = '2026-02-19 06:25:59.714', $18 = '2026-02-19 06:25:59.644'

11

245ms

3,243

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 #11

Day	Hour	Count	Duration	Avg duration
	06	3,243	245ms	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: 2026-02-19 06:31:05 Duration: 0ms Database: postgres parameters: $1 = '2026-02-19 06:00:00', $2 = '14855', $3 = '14855', $4 = '14846.5', $5 = '14847', $6 = '296', $7 = '500991628278678200', $8 = '0', $9 = '2026-02-19 06:31:05.934', $10 = '2026-02-19 06:31:05.933', $11 = '14855', $12 = '14855', $13 = '14846.5', $14 = '14847', $15 = '296', $16 = '0', $17 = '2026-02-19 06:31:05.934', $18 = '2026-02-19 06:31:05.933'
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: 2026-02-19 06:32:35 Duration: 0ms Database: postgres parameters: $1 = '2026-02-19 06:00:00', $2 = '0.772895', $3 = '0.77327', $4 = '0.77287', $5 = '0.77319', $6 = '814', $7 = '515840230587467300', $8 = '0', $9 = '2026-02-19 06:32:35.667', $10 = '2026-02-19 06:32:35.667', $11 = '0.772895', $12 = '0.77327', $13 = '0.77287', $14 = '0.77319', $15 = '814', $16 = '0', $17 = '2026-02-19 06:32:35.667', $18 = '2026-02-19 06:32:35.667'
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: 2026-02-19 06:40:54 Duration: 0ms Database: postgres parameters: $1 = '2026-02-16 05:00:00', $2 = '26655.2', $3 = '26695', $4 = '26631.7', $5 = '26651.2', $6 = '8674', $7 = '515840247933633300', $8 = '0', $9 = '2026-02-19 06:40:54.747', $10 = '2026-02-19 06:40:54.708', $11 = '26655.2', $12 = '26695', $13 = '26631.7', $14 = '26651.2', $15 = '8674', $16 = '0', $17 = '2026-02-19 06:40:54.747', $18 = '2026-02-19 06:40:54.708'

12

178ms

2,132

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 #12

Day	Hour	Count	Duration	Avg duration
	06	2,132	178ms	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: 2026-02-19 06:02:11 Duration: 0ms Database: postgres parameters: $1 = '2026-02-19 05:00:00', $2 = '0.910865', $3 = '0.911335', $4 = '0.910855', $5 = '0.911315', $6 = '1704', $7 = '515840230468781300', $8 = '0', $9 = '2026-02-19 06:02:11.8', $10 = '2026-02-19 06:02:11.8', $11 = '0.910865', $12 = '0.911335', $13 = '0.910855', $14 = '0.911315', $15 = '1704', $16 = '0', $17 = '2026-02-19 06:02:11.8', $18 = '2026-02-19 06:02:11.8'
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: 2026-02-19 06:02:05 Duration: 0ms Database: postgres parameters: $1 = '2026-02-19 05:00:00', $2 = '1.6681', $3 = '1.66921', $4 = '1.667625', $5 = '1.669165', $6 = '3151', $7 = '515840230459451300', $8 = '0', $9 = '2026-02-19 06:02:05.702', $10 = '2026-02-19 06:02:05.701', $11 = '1.6681', $12 = '1.66921', $13 = '1.667625', $14 = '1.669165', $15 = '3151', $16 = '0', $17 = '2026-02-19 06:02:05.702', $18 = '2026-02-19 06:02:05.701'
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: 2026-02-19 06:02:48 Duration: 0ms Database: postgres parameters: $1 = '2026-02-19 05:00:00', $2 = '0.707', $3 = '0.70729', $4 = '0.70646', $5 = '0.70654', $6 = '1241', $7 = '515840230435374300', $8 = '0', $9 = '2026-02-19 06:02:48.13', $10 = '2026-02-19 06:02:48.13', $11 = '0.707', $12 = '0.70729', $13 = '0.70646', $14 = '0.70654', $15 = '1241', $16 = '0', $17 = '2026-02-19 06:02:48.13', $18 = '2026-02-19 06:02:48.13'

13

118ms

193

Details

0ms

2ms

0ms

SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Times Reported Time consuming bind #13

Day	Hour	Count	Duration	Avg duration
	06	193	118ms	0ms

SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2026-02-19 06:12:48 Duration: 2ms Database: postgres
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2026-02-19 06:12:50 Duration: 1ms Database: postgres
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2026-02-19 06:12:48 Duration: 1ms Database: postgres

14

81ms

6

Details

3ms

49ms

13ms

with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;

Times Reported Time consuming bind #14

Day	Hour	Count	Duration	Avg duration
	06	6	81ms	13ms

with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;

Date: 2026-02-19 06:40:02 Duration: 49ms Database: postgres
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;

Date: 2026-02-19 06:50:02 Duration: 9ms Database: postgres
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;

Date: 2026-02-19 06:20:02 Duration: 6ms Database: postgres

15

63ms

14

Details

1ms

18ms

4ms

WITH rcr_max as ( ;

Times Reported Time consuming bind #15

Day	Hour	Count	Duration	Avg duration
	06	14	63ms	4ms

WITH rcr_max as ( ;

Date: 2026-02-19 06:30:53 Duration: 18ms Database: postgres parameters: $1 = '607702674021148305', $2 = '607702674021148305', $3 = '607702674021148305'
WITH rcr_max as ( ;

Date: 2026-02-19 06:15:55 Duration: 7ms Database: postgres parameters: $1 = '607702674021148305', $2 = '607702674021148305', $3 = '607702674021148305'
WITH rcr_max as ( ;

Date: 2026-02-19 06:15:40 Duration: 6ms Database: postgres parameters: $1 = '607703620986290305', $2 = '607703620986290305', $3 = '607703620986290305'

16

54ms

50

Details

0ms

3ms

1ms

SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Times Reported Time consuming bind #16

Day	Hour	Count	Duration	Avg duration
	06	50	54ms	1ms

SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2026-02-19 06:35:41 Duration: 3ms Database: postgres parameters: $1 = '538', $2 = 'XAUUSDr', $3 = '538'
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2026-02-19 06:39:14 Duration: 1ms Database: postgres parameters: $1 = '689', $2 = 'XAUUSD', $3 = '689'
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2026-02-19 06:06:56 Duration: 1ms Database: postgres parameters: $1 = '632', $2 = 'EURGBP', $3 = '632'

17

50ms

1

Details

50ms

with maxwhid as ( ;

Times Reported Time consuming bind #17

Day	Hour	Count	Duration	Avg duration
	06	1	50ms	50ms

with maxwhid as ( ;

Date: 2026-02-19 06:12:41 Duration: 50ms Database: postgres parameters: $1 = '335', $2 = '621', $3 = '637', $4 = '642', $5 = '660', $6 = '666', $7 = '643', $8 = '630', $9 = '680', $10 = '641', $11 = '431', $12 = '622', $13 = '489', $14 = '529', $15 = '576', $16 = '665', $17 = '667', $18 = '558', $19 = '620', $20 = '125', $21 = '488', $22 = '567', $23 = '689', $24 = '700', $25 = '758', $26 = '763', $27 = '765', $28 = '817', $29 = '914', $30 = '972'

18

49ms

8

Details

2ms

10ms

6ms

WITH pre_symbols AS ( /* find relevant symbols */ ;

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	06	8	49ms	6ms

WITH pre_symbols AS ( /* find relevant symbols */ ;

Date: 2026-02-19 06:12:46 Duration: 10ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'
WITH pre_symbols AS ( /* find relevant symbols */ ;

Date: 2026-02-19 06:12:46 Duration: 10ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'
WITH pre_symbols AS ( /* find relevant symbols */ ;

Date: 2026-02-19 06:12:46 Duration: 8ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD'

19

46ms

9

Details

3ms

7ms

5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #19

Day	Hour	Count	Duration	Avg duration
	06	9	46ms	5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-19 06:27:15 Duration: 7ms Database: postgres parameters: $1 = '667', $2 = '667'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-19 06:21:01 Duration: 6ms Database: postgres parameters: $1 = '627', $2 = '627'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-19 06:31:27 Duration: 6ms Database: postgres parameters: $1 = '627', $2 = '627'

20

31ms

148

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 #20

Day	Hour	Count	Duration	Avg duration
	06	148	31ms	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: 2026-02-19 06:35:36 Duration: 4ms Database: postgres parameters: $1 = '607703617194569301'
/*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: 2026-02-19 06:35:56 Duration: 3ms Database: postgres parameters: $1 = '607703259456036301'
/*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: 2026-02-19 06:36:34 Duration: 2ms Database: postgres parameters: $1 = '607704205360256301'

Log levels

Key values

323,733 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	700	0.22%
DETAIL	66,177	20.44%
ERROR	531	0.16%
LOG	254,959	78.76%
STATEMENT	1,366	0.42%

Events distribution

Key values

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

Most Frequent Errors/Events

Key values

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

Rank

Times reported

Error

1

358

Details

ERROR: pg_stat_statements must be loaded via shared_preload_libraries

Times Reported Most Frequent Error / Event #1

Day	Hour	Count
Feb 19	06	358

ERROR: pg_stat_statements must be loaded via shared_preload_libraries

2

64

Details

LOG: process ... still waiting for AccessShareLock on relation ... of database ... after ... ms

Times Reported Most Frequent Error / Event #2

Day	Hour	Count
Feb 19	06	64

LOG: process 26045 still waiting for AccessShareLock on relation 5883477 of database 5881926 after 1000.044 ms
LOG: process 26045 still waiting for AccessShareLock on relation 5883477 of database 5881926 after 1000.043 ms
LOG: process 26045 still waiting for AccessShareLock on relation 5883477 of database 5881926 after 1000.057 ms

3

58

Details

ERROR: canceling statement due to statement timeout

Times Reported Most Frequent Error / Event #3

Day	Hour	Count
Feb 19	06	58

ERROR: canceling statement due to statement timeout

4

54

Details

ERROR: schema "..." does not exist

Times Reported Most Frequent Error / Event #4

Day	Hour	Count
Feb 19	06	54

ERROR: schema "datadog" does not exist at character 38

5

3

Details

LOG: process ... still waiting for AccessExclusiveLock on relation ... of database ... after ... ms

Times Reported Most Frequent Error / Event #5

Day	Hour	Count
Feb 19	06	3

LOG: process 10664 still waiting for AccessExclusiveLock on relation 5883477 of database 5881926 after 1000.050 ms
LOG: process 15239 still waiting for AccessExclusiveLock on relation 5894441 of database 5881926 after 1000.051 ms
LOG: process 15239 still waiting for AccessExclusiveLock on relation 5894441 of database 5881926 after 63561.773 ms

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

Established 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

Simultaneous 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 host

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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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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

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