pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Mon Mar 9 09:59:45 2026
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-03-09_110000.log
Parsed 1,727,050 log entries in 44s
Log start from 2026-03-09 11:00:00 to 2026-03-09 11:59:43

Global Stats

263 Number of unique normalized queries
214,392 Number of queries
1h30m50s Total query duration
2026-03-09 11:00:00 First query
2026-03-09 11:59:43 Last query
3,898 queries/s at 2026-03-09 11:45:04 Query peak

1h30m50s Total query duration
7s89ms Prepare/parse total duration
42s151ms Bind total duration
1h30m1s Execute total duration

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

51 Total number of automatic vacuums
58 Total number of automatic analyzes

867 Number temporary file
163.68 MiB Max size of temporary file
6.86 MiB Average size of temporary file

2,857 Total number of sessions
12 sessions at 2026-03-09 11:58:21 Session peak
2d14h53m54s Total duration of sessions
1m19s Average duration of sessions
75 Average queries per session
1s907ms Average queries duration per session
1m17s Average idle time per session

2,856 Total number of connections
28 connections/s at 2026-03-09 11:18:48 Connection peak
4 Total number of databases

SQL Traffic

Key values

3,898 queries/s Query Peak
2026-03-09 11:45:04 Date

SELECT Traffic

Key values

1,936 queries/s Query Peak
2026-03-09 11:45:04 Date

INSERT/UPDATE/DELETE Traffic

Key values

201 queries/s Query Peak
2026-03-09 11:45:51 Date

Queries duration

Key values

1h30m50s 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)
Mar 09	11	214,392	0ms	22s451ms	25ms	2m36s	3m11s	3m51s

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Mar 09	11	70,259	26	0ms	0ms	0ms	0ms

Day	Hour	INSERT	UPDATE	DELETE	COPY FROM	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Mar 09	11	25,951	1,956	16	96	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Mar 09	11	19,517	72,145	3.70	18.94%

Day	Hour	Count	Average / Second
Mar 09	11	2,856	0.79/s

Day	Hour	Count	Average Duration	Average idle time
Mar 09	11	2,857	1m19s	1m17s

↑ Back to the top of the General Activity table

Established Connections

Key values

28 connections Connection Peak
2026-03-09 11:18:48 Date

Connections per database

Key values

acaweb_fx Main Database
2,856 connections Total

Chart
Table

Database	User	Count
acaweb_fx		2,772
	pgAdmin 4 - DB:acaweb_fx	1
	postgres	2,413
	psql	358
postgres		1
	pgAdmin 4 - DB:postgres	1
socialmedia		83
	postgres	83

Connections per user

Key values

postgres Main User
2,856 connections Total

Chart
Table

User	Count
pgAdmin 4 - DB:acaweb_fx	1
pgAdmin 4 - DB:postgres	1
postgres	2,496
psql	358

Connections per host

Key values

192.168.4.142 Main host with 1161 connections
2,856 Total connections

Chart
Table

Host	Count
104.30.164.187	2
127.0.0.1	113
192.168.0.114	3
192.168.0.216	103
192.168.0.74	19
192.168.1.127	10
192.168.1.145	181
192.168.1.15	237
192.168.1.154	1
192.168.1.20	199
192.168.1.239	14
192.168.1.90	55
192.168.2.126	33
192.168.2.182	12
192.168.3.199	36
192.168.4.142	1,161
192.168.4.150	10
192.168.4.238	16
192.168.4.33	71
192.168.4.42	1
192.168.4.9	4
192.168.4.98	330
[local]	245

Simultaneous sessions

Key values

12 sessions Session Peak
2026-03-09 11:58:21 Date

Histogram of session times

Key values

2,264 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	2,264	79.24%
500ms-1s	170	5.95%
1s-30s	309	10.82%
30s-1m	11	0.39%
1m-10m	35	1.23%
10m-30m	50	1.75%
30m-1h	2	0.07%
1h-8h	16	0.56%
> 8h	0	0.00%

Sessions per database

Key values

acaweb_fx Main Database
2,857 sessions Total

Chart
Table

Database	User	Count	Total Duration	Average Duration
acaweb_fx	2,773	2d14h23m24s	1m20s
socialmedia	84	30m30s	21s789ms

Sessions per user

Key values

postgres Main User
2,857 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
2,857 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
127.0.0.1	113	15s218ms	134ms
192.168.0.114	4	32m54s	8m13s
192.168.0.216	103	1m43s	1s2ms
192.168.0.74	22	20h12m37s	55m7s
192.168.1.127	10	510ms	51ms
192.168.1.145	181	4h14m3s	1m24s
192.168.1.15	237	3h33m55s	54s159ms
192.168.1.20	199	13h42m	4m7s
192.168.1.239	14	82ms	5ms
192.168.1.90	55	40s431ms	735ms
192.168.2.126	33	5s337ms	161ms
192.168.2.182	12	892ms	74ms
192.168.3.199	36	1s425ms	39ms
192.168.4.142	1,161	9m24s	486ms
192.168.4.150	10	20h19m9s	2h1m54s
192.168.4.238	16	21s610ms	1s350ms
192.168.4.33	71	2m35s	2s186ms
192.168.4.42	1	183ms	183ms
192.168.4.9	4	24s300ms	6s75ms
192.168.4.98	330	14s293ms	43ms
[local]	245	3m26s	844ms

Sessions per application

Key values

unknown Main Host
2,857 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	2,857	2d14h53m54s	1m19s

Checkpoints Buffers

Key values

12,998 buffers Checkpoint Peak
2026-03-09 11:06:09 Date
210.014 seconds Highest write time
0.013 seconds Sync time

Checkpoints Wal files

Key values

5 files Wal files usage Peak
2026-03-09 11:06:09 Date

Checkpoints distance

Key values

163.16 Mo Distance Peak
2026-03-09 11:06:09 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Mar 09	11	46,596	1,830.626s	0.062s	1,830.968s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Mar 09	11	0	0	23	2,031	0.008s	0s

Day	Hour	Count	Avg time (sec)
Mar 09	11	0	0s

Day	Hour	Mean distance	Mean estimate
Mar 09	11	31,137.50 kB	65,042.08 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

167.34 MiB Temp Files size Peak
2026-03-09 11:20:08 Date

Number of temporary files

Key values

30 per second Temp Files Peak
2026-03-09 11:02:15 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Mar 09	11	867	5.81 GiB	6.86 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	214	350.35 MiB	137.65 KiB	3.87 MiB	1.64 MiB	with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ), ar as ( select a., rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end ), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on sg.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc ; WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a., rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4, $5, $6, $7, $8, $9, $10)) AND ($11 = 0 OR s.exchange in ($12)) AND ($13 = 0 OR coalesce(bim.code, s.symbol) in ($14, $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 ar.pattern in ($325)) AND ($326 = 0 OR ($327 = 1 AND ar.breakout >= 0) OR ($328 = 2 AND ar.breakout < 0)) AND ($329 = 0 OR ar.patternlengthbars <= $330) and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) FROM all_results WHERE (FALSE = $331 OR relevant = 1) AND ($332 = 0 OR age <= $333) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-03-09 11:00:35 Duration: 0ms
2	49	247.71 MiB	4.99 MiB	5.14 MiB	5.06 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: 2026-03-09 11:00:48 Duration: 0ms
3	29	1.67 GiB	3.83 MiB	163.68 MiB	58.87 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: 2026-03-09 11:00:06 Duration: 0ms
4	23	76.30 MiB	3.19 MiB	3.46 MiB	3.32 MiB	select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ?), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?)), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc; SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ($2 = 0 OR s.timegranularity in ($3, $4, $5, $6, $7, $8, $9)) AND ($10 = 0 OR s.exchange in ($11)) AND ($12 = 0 OR coalesce(bim.code, s.symbol) in ($13, $14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226, $227, $228, $229, $230, $231, $232, $233, $234, $235, $236, $237, $238, $239, $240, $241, $242, $243, $244, $245, $246, $247, $248, $249, $250, $251, $252, $253, $254, $255, $256, $257, $258, $259, $260, $261, $262, $263, $264, $265, $266, $267, $268, $269, $270, $271, $272, $273, $274, $275, $276, $277, $278, $279, $280, $281, $282, $283, $284, $285, $286, $287, $288, $289, $290, $291, $292, $293, $294, $295, $296, $297, $298, $299, $300, $301, $302, $303, $304, $305, $306, $307, $308, $309, $310, $311, $312, $313, $314, $315, $316, $317, $318, $319, $320, $321, $322)) AND ($323 = 0 OR ccr.patternlengthbars <= $324)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $325 OR relevant = 1) AND ($326 = 0 OR age <= $327) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-03-09 11:01:07 Duration: 0ms
5	16	739.25 MiB	46.20 MiB	46.20 MiB	46.20 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: 2026-03-09 11:01:13 Duration: 0ms
6	16	1.23 GiB	78.45 MiB	78.45 MiB	78.45 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: 2026-03-09 11:01:16 Duration: 0ms
7	8	1.08 GiB	138.48 MiB	138.56 MiB	138.52 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2026-03-09 11:02:20 Duration: 0ms
8	4	312.97 MiB	78.17 MiB	78.30 MiB	78.24 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2026-03-09 11:02:09 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	163.68 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: 2026-03-09 11:50:05 ]
2	138.56 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 11:32:14 ]
3	138.55 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 11:47:16 ]
4	138.54 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 11:50:32 ]
5	138.54 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 11:35:32 ]
6	138.52 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 11:02:20 ]
7	138.49 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 11:17:16 ]
8	138.48 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 11:20:33 ]
9	138.48 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 11:05:32 ]
10	115.76 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: 2026-03-09 11:00:04 ]
11	106.83 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: 2026-03-09 11:40:04 ]
12	104.92 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: 2026-03-09 11:30:04 ]
13	99.23 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: 2026-03-09 11:20:04 ]
14	98.16 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: 2026-03-09 11:40:05 ]
15	92.73 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: 2026-03-09 11:10:04 ]
16	86.20 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: 2026-03-09 11:10:07 ]
17	83.84 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: 2026-03-09 11:20:04 ]
18	81.19 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: 2026-03-09 11:20:04 ]
19	78.45 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-03-09 11:01:16 ]
20	78.45 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-03-09 11:03:17 ]

Vacuums / Analyzes Distribution

Key values

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

Analyzes per table

Key values

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

Chart
Table

Table	Number of analyzes
acaweb_fx.public.solr_relevance_old	16
acaweb_fx.pg_catalog.pg_attribute	8
acaweb_fx.pg_catalog.pg_class	6
acaweb_fx.public.relevance_keylevels_results	4
acaweb_fx.public.relevance_fibonacci_results	4
acaweb_fx.pg_catalog.pg_type	4
acaweb_fx.public.relevance_autochartist_results	4
acaweb_fx.public.datafeeds_latestrun	2
acaweb_fx.public.latest_t15_candle_view	2
acaweb_fx.pg_catalog.pg_depend	2
acaweb_fx.pg_catalog.pg_index	1
acaweb_fx.public.autochartist_symbolupdates	1
acaweb_fx.public.solr_imports	1
acaweb_fx.public.latest_candle_datetime_per_receng	1
acaweb_fx.public.relevance_consecutivecandles_results	1
acaweb_fx.public.symbollatestupdatetime	1
Total	58

Vacuums per table

Key values

public.solr_relevance_old (27) Main table vacuumed on database acaweb_fx
51 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	27	22	16,598	0	91	0	358	8,452	16	1,519,451
acaweb_fx.pg_catalog.pg_type	3	3	474	0	98	0	0	224	74	365,909
acaweb_fx.pg_catalog.pg_attribute	3	3	2,558	0	296	0	201	1,114	265	1,705,638
acaweb_fx.pg_toast.pg_toast_2619	2	2	310	0	60	0	0	206	60	224,318
acaweb_fx.public.datafeeds_latestrun	2	0	240	0	11	0	0	26	6	31,402
acaweb_fx.public.relevance_keylevels_results	2	2	7,783	0	945	0	202	1,769	1,145	2,889,700
acaweb_fx.pg_catalog.pg_class	2	2	912	0	118	0	0	276	111	586,885
acaweb_fx.public.relevance_autochartist_results	2	2	6,715	0	195	2	502	1,286	935	2,542,869
acaweb_fx.public.relevance_fibonacci_results	2	2	2,408	0	64	2	103	402	236	738,281
acaweb_fx.pg_catalog.pg_index	1	1	90	0	13	0	0	27	10	75,218
acaweb_fx.public.autochartist_symbolupdates	1	1	23,074	0	2,158	1	38,000	7,028	2,134	1,230,494
acaweb_fx.public.solr_imports	1	1	64	0	2	0	0	5	1	5,867
acaweb_fx.pg_catalog.pg_statistic	1	1	1,022	0	110	0	582	477	96	471,950
acaweb_fx.public.latest_t15_candle_view	1	1	66	0	1	0	0	6	1	8,318
acaweb_fx.pg_catalog.pg_depend	1	1	391	0	77	0	59	184	71	352,119
Total	51	44	62,705	47,780	4,239	5	40,007	21,482	5,161	12,748,419

Tuples removed per table

Key values

public.solr_relevance_old (51051) Main table with removed tuples on database acaweb_fx
68926 tuples Total removed

Chart
Table

		Index	Tuples			Pages
Table	Vacuums	scans	removed	remain	not yet removable	removed	remain
acaweb_fx.public.solr_relevance_old	27	22	51,051	187,789	42,755	0	4,744
acaweb_fx.public.autochartist_symbolupdates	1	1	7,047	49,289	6	0	40,691
acaweb_fx.pg_catalog.pg_attribute	3	3	5,634	32,265	0	25	784
acaweb_fx.public.relevance_keylevels_results	2	2	1,596	22,055	0	0	558
acaweb_fx.pg_catalog.pg_type	3	3	868	4,541	176	0	135
acaweb_fx.public.relevance_autochartist_results	2	2	723	15,815	0	0	760
acaweb_fx.pg_catalog.pg_statistic	1	1	648	3,764	0	0	1,194
acaweb_fx.pg_catalog.pg_depend	1	1	520	14,393	0	0	144
acaweb_fx.pg_catalog.pg_class	2	2	301	3,312	0	0	300
acaweb_fx.public.relevance_fibonacci_results	2	2	165	2,904	0	0	204
acaweb_fx.pg_toast.pg_toast_2619	2	2	148	342	10	0	110
acaweb_fx.public.datafeeds_latestrun	2	0	126	28	0	0	32
acaweb_fx.public.solr_imports	1	1	49	3	2	0	2
acaweb_fx.public.latest_t15_candle_view	1	1	44	24	12	0	1
acaweb_fx.pg_catalog.pg_index	1	1	6	815	0	0	22
Total	51	44	68,926	337,339	42,961	25	49,681

Pages removed per table

Key values

pg_catalog.pg_attribute (25) Main table with removed pages on database acaweb_fx
25 pages Total removed

Chart
Table

Table	Number of vacuums	Index scans	Tuples removed	Pages removed
acaweb_fx.pg_catalog.pg_attribute	3	3	5634	25
acaweb_fx.pg_toast.pg_toast_2619	2	2	148	0
acaweb_fx.pg_catalog.pg_index	1	1	6	0
acaweb_fx.pg_catalog.pg_type	3	3	868	0
acaweb_fx.public.autochartist_symbolupdates	1	1	7047	0
acaweb_fx.public.datafeeds_latestrun	2	0	126	0
acaweb_fx.public.solr_imports	1	1	49	0
acaweb_fx.pg_catalog.pg_statistic	1	1	648	0
acaweb_fx.public.latest_t15_candle_view	1	1	44	0
acaweb_fx.pg_catalog.pg_depend	1	1	520	0
acaweb_fx.public.relevance_keylevels_results	2	2	1596	0
acaweb_fx.pg_catalog.pg_class	2	2	301	0
acaweb_fx.public.solr_relevance_old	27	22	51051	0
acaweb_fx.public.relevance_autochartist_results	2	2	723	0
acaweb_fx.public.relevance_fibonacci_results	2	2	165	0
Total	51	44	68,926	25

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Mar 09	11	51	58

↑ Back to the top of the Autovacuum Activity table

Locks by types

Key values

unknown Main Lock Type
0 locks Total

Chart
Table

Type of locks

NO DATASET

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

Most frequent waiting queries (N)

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

Queries that waited the most

Rank	Wait time	Query
NO DATASET

Queries by type

Key values

70,259 Total read queries
32,778 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	70,259	32.77%
INSERT	25,951	12.10%
UPDATE	1,956	0.91%
DELETE	16	0.01%
COPY FROM	96	0.04%
COPY TO	26	0.01%
CTE	4,003	1.87%
DDL	16	0.01%
TCL	714	0.33%
CURSOR	0	0.00%
OTHERS	111,355	51.94%

Queries by database

Key values

unknown Main database
213,453 Requests
1h30m1s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	855	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	170	0ms
	select	73	0ms
	tcl	331	0ms
	update	39	0ms
postgres	Total	1	0ms
	others	1	0ms
socialmedia	Total	83	0ms
	others	10	0ms
	select	71	0ms
	tcl	2	0ms
unknown	Total	213,453	1h30m1s
	copy from	16	0ms
	cte	3,899	0ms
	insert	25,951	0ms
	others	4,176	0ms
	select	70,115	0ms
	tcl	381	0ms
	update	1,917	0ms

Queries by user

Key values

unknown Main user
213,453 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	939	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	181	0ms
	select	144	0ms
	tcl	333	0ms
	update	39	0ms
unknown	Total	213,453	1h30m1s
	copy from	16	0ms
	cte	3,899	0ms
	insert	25,951	0ms
	others	4,176	0ms
	select	70,115	0ms
	tcl	381	0ms
	update	1,917	0ms

Duration by user

Key values

1h30m1s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	939	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	181	0ms
	select	144	0ms
	tcl	333	0ms
	update	39	0ms
unknown	Total	213,453	1h30m1s
	copy from	16	0ms
	cte	3,899	0ms
	insert	25,951	0ms
	others	4,176	0ms
	select	70,115	0ms
	tcl	381	0ms
	update	1,917	0ms

Queries by host

Key values

unknown Main host
214,392 Requests
1h30m1s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	214,392	1h30m1s
	copy from	96	0ms
	copy to	26	0ms
	cte	4,003	0ms
	ddl	16	0ms
	delete	16	0ms
	insert	25,951	0ms
	others	4,357	0ms
	select	70,259	0ms
	tcl	714	0ms
	update	1,956	0ms

Queries by application

Key values

unknown Main application
214,032 Requests
1h30m1s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
pgAdmin 4 - DB:acaweb_fx	Total	1	0ms
	others	1	0ms
pgAdmin 4 - DB:postgres	Total	1	0ms
	others	1	0ms
psql	Total	358	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	4	0ms
	select	73	0ms
	update	39	0ms
unknown	Total	214,032	1h30m1s
	copy from	16	0ms
	cte	3,899	0ms
	insert	25,951	0ms
	others	4,351	0ms
	select	70,186	0ms
	tcl	714	0ms
	update	1,917	0ms

Number of cancelled queries

Key values

0 per second Cancelled query Peak
2026-03-09 11:48:33 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

64,966 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	64,966	60.72%
1-5ms	33,217	31.04%
5-10ms	2,432	2.27%
10-25ms	1,455	1.36%
25-50ms	1,877	1.75%
50-100ms	1,609	1.50%
100-500ms	559	0.52%
500-1000ms	83	0.08%
1000-10000ms	651	0.61%
> 10000ms	149	0.14%

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

16

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Mar 09	11	16	0ms	0ms

2

0ms

1

Details

0ms

select distinct "public"."processes"."live" AS "live" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? order by ? asc;

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1	0ms	0ms

3

0ms

84

Details

0ms

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

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Mar 09	11	84	0ms	0ms

4

0ms

2,178

Details

0ms

insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Mar 09	11	2,178	0ms	0ms

5

0ms

4

Details

0ms

select count(*) from datafeeds_latestrun where feedname ilike ? and ((latestrxtime > current_timestamp - interval ? and latestdbwritetime > current_timestamp - interval ?) or (latestdbwritetime > current_timestamp - interval ? and lateststartuptime > current_timestamp - interval ?));

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Mar 09	11	4	0ms	0ms

6

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Mar 09	11	4	0ms	0ms

7

0ms

10

Details

0ms

set datestyle = iso;

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Mar 09	11	10	0ms	0ms

8

0ms

10

Details

0ms

set client_encoding to ?;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Mar 09	11	10	0ms	0ms

9

0ms

18

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Mar 09	11	18	0ms	0ms

10

0ms

1

Details

0ms

select distinct "public"."processes"."enabled" AS "enabled" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? order by ? asc;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1	0ms	0ms

11

0ms

1

Details

0ms

select count(*) from ( select max(lastupdated) from sa_hist_bigmove where symbolid in ( select symbolid from t60 group by symbolid order by max(sastdatetimereceived) desc limit ?) group by symbolid having max(lastupdated) > current_timestamp - interval ? order by max(lastupdated) desc limit ?) as k;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1	0ms	0ms

12

0ms

357

Details

0ms

commit;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Mar 09	11	357	0ms	0ms

13

0ms

241

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 #13

Day	Hour	Count	Duration	Avg duration
Mar 09	11	241	0ms	0ms

14

0ms

1

Details

0ms

select "public"."processes"."id" AS "id", "public"."processes"."locale" AS "locale", "public"."processes"."region" AS "region", "public"."processes"."schedule" AS "schedule", "public"."processes"."enabled" AS "enabled", "public"."processes"."live" AS "live", "public"."processes"."lastmodified" AS "lastmodified", "public"."processes"."lastrun" AS "lastrun", "public"."processes"."contenttypeid" AS "contenttypeid", "public"."processes"."brokerid" AS "brokerid", "public"."processes"."uuid" AS "uuid", "LT?"."name" AS "LA?", "LT?"."name" AS "LA?" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? and (brokerid = ?) order by "public"."processes"."id" asc limit ? offset ?;

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1	0ms	0ms

15

0ms

239

Details

0ms

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

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Mar 09	11	239	0ms	0ms

16

0ms

239

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Mar 09	11	239	0ms	0ms

17

0ms

7

Details

0ms

select groupid, exchange, groupname, symbol, longname from prfsymboltree where brokerid = ? order by groupname, symbol;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Mar 09	11	7	0ms	0ms

18

0ms

1

Details

0ms

select futures_setfutureautomatically ();

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1	0ms	0ms

19

0ms

7

Details

0ms

select "public"."processes"."id" AS "id", "public"."processes"."locale" AS "locale", "public"."processes"."region" AS "region", "public"."processes"."schedule" AS "schedule", "public"."processes"."enabled" AS "enabled", "public"."processes"."live" AS "live", "public"."processes"."lastmodified" AS "lastmodified", "public"."processes"."lastrun" AS "lastrun", "public"."processes"."contenttypeid" AS "contenttypeid", "public"."processes"."brokerid" AS "brokerid", "public"."processes"."uuid" AS "uuid", "LT?"."name" AS "LA?", "LT?"."name" AS "LA?" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ?;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Mar 09	11	7	0ms	0ms

20

0ms

241

Details

0ms

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

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Mar 09	11	241	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

21,163

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Mar 09	11	21,163	0ms	0ms

2

13,070

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
Mar 09	11	13,070	0ms	0ms

3

10,845

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
Mar 09	11	10,845	0ms	0ms

4

5,755

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
Mar 09	11	5,755	0ms	0ms

5

5,183

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 #5

Day	Hour	Count	Duration	Avg duration
Mar 09	11	5,183	0ms	0ms

6

3,733

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Mar 09	11	3,733	0ms	0ms

7

3,347

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Mar 09	11	3,347	0ms	0ms

8

3,302

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 #8

Day	Hour	Count	Duration	Avg duration
Mar 09	11	3,302	0ms	0ms

9

2,199

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 #9

Day	Hour	Count	Duration	Avg duration
Mar 09	11	2,199	0ms	0ms

10

2,178

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 #10

Day	Hour	Count	Duration	Avg duration
Mar 09	11	2,178	0ms	0ms

11

1,949

Details

0ms

insert into keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errormargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestprice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) values (?.?, ?, ?, ?::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 #11

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1,949	0ms	0ms

12

1,874

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1,874	0ms	0ms

13

1,850

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1,850	0ms	0ms

14

1,500

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
Mar 09	11	1,500	0ms	0ms

15

1,195

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 #15

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1,195	0ms	0ms

16

1,195

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 #16

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1,195	0ms	0ms

17

1,195

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 #17

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1,195	0ms	0ms

18

1,195

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 #18

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1,195	0ms	0ms

19

1,195

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 #19

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1,195	0ms	0ms

20

1,195

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 #20

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1,195	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

16

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Mar 09	11	16	0ms	0ms

2

0ms

1

Details

0ms

select distinct "public"."processes"."live" AS "live" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? order by ? asc;

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1	0ms	0ms

3

0ms

84

Details

0ms

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

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Mar 09	11	84	0ms	0ms

4

0ms

2,178

Details

0ms

insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Mar 09	11	2,178	0ms	0ms

5

0ms

4

Details

0ms

select count(*) from datafeeds_latestrun where feedname ilike ? and ((latestrxtime > current_timestamp - interval ? and latestdbwritetime > current_timestamp - interval ?) or (latestdbwritetime > current_timestamp - interval ? and lateststartuptime > current_timestamp - interval ?));

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Mar 09	11	4	0ms	0ms

6

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Mar 09	11	4	0ms	0ms

7

0ms

10

Details

0ms

set datestyle = iso;

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Mar 09	11	10	0ms	0ms

8

0ms

10

Details

0ms

set client_encoding to ?;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Mar 09	11	10	0ms	0ms

9

0ms

18

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Mar 09	11	18	0ms	0ms

10

0ms

1

Details

0ms

select distinct "public"."processes"."enabled" AS "enabled" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? order by ? asc;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1	0ms	0ms

11

0ms

1

Details

0ms

select count(*) from ( select max(lastupdated) from sa_hist_bigmove where symbolid in ( select symbolid from t60 group by symbolid order by max(sastdatetimereceived) desc limit ?) group by symbolid having max(lastupdated) > current_timestamp - interval ? order by max(lastupdated) desc limit ?) as k;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1	0ms	0ms

12

0ms

357

Details

0ms

commit;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Mar 09	11	357	0ms	0ms

13

0ms

241

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 #13

Day	Hour	Count	Duration	Avg duration
Mar 09	11	241	0ms	0ms

14

0ms

1

Details

0ms

select "public"."processes"."id" AS "id", "public"."processes"."locale" AS "locale", "public"."processes"."region" AS "region", "public"."processes"."schedule" AS "schedule", "public"."processes"."enabled" AS "enabled", "public"."processes"."live" AS "live", "public"."processes"."lastmodified" AS "lastmodified", "public"."processes"."lastrun" AS "lastrun", "public"."processes"."contenttypeid" AS "contenttypeid", "public"."processes"."brokerid" AS "brokerid", "public"."processes"."uuid" AS "uuid", "LT?"."name" AS "LA?", "LT?"."name" AS "LA?" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? and (brokerid = ?) order by "public"."processes"."id" asc limit ? offset ?;

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1	0ms	0ms

15

0ms

239

Details

0ms

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

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Mar 09	11	239	0ms	0ms

16

0ms

239

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Mar 09	11	239	0ms	0ms

17

0ms

7

Details

0ms

select groupid, exchange, groupname, symbol, longname from prfsymboltree where brokerid = ? order by groupname, symbol;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Mar 09	11	7	0ms	0ms

18

0ms

1

Details

0ms

select futures_setfutureautomatically ();

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Mar 09	11	1	0ms	0ms

19

0ms

7

Details

0ms

select "public"."processes"."id" AS "id", "public"."processes"."locale" AS "locale", "public"."processes"."region" AS "region", "public"."processes"."schedule" AS "schedule", "public"."processes"."enabled" AS "enabled", "public"."processes"."live" AS "live", "public"."processes"."lastmodified" AS "lastmodified", "public"."processes"."lastrun" AS "lastrun", "public"."processes"."contenttypeid" AS "contenttypeid", "public"."processes"."brokerid" AS "brokerid", "public"."processes"."uuid" AS "uuid", "LT?"."name" AS "LA?", "LT?"."name" AS "LA?" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ?;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Mar 09	11	7	0ms	0ms

20

0ms

241

Details

0ms

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

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Mar 09	11	241	0ms	0ms

Time consuming prepare


Date: 2026-03-09 11:15:04
Duration: 11ms
Database: postgres
Date: 2026-03-09 11:31:11
Duration: 3ms
Database: postgres
Date: 2026-03-09 11:45:04
Duration: 10ms
Database: postgres
Date: 2026-03-09 11:30:08
Duration: 1ms
Database: postgres
Date: 2026-03-09 11:21:11
Duration: 0ms
Database: postgres
Date: 2026-03-09 11:00:19
Duration: 1ms
Database: postgres
Date: 2026-03-09 11:01:14
Duration: 0ms
Database: postgres
Date: 2026-03-09 11:00:24
Duration: 1ms
Database: postgres
Date: 2026-03-09 11:20:10
Duration: 1ms
Database: postgres
Date: 2026-03-09 11:21:43
Duration: 7ms
Database: postgres
Date: 2026-03-09 11:05:09
Duration: 2ms
Database: postgres
Date: 2026-03-09 11:50:03
Duration: 2ms
Database: postgres
Date: 2026-03-09 11:12:00
Duration: 4ms
Database: postgres
Date: 2026-03-09 11:55:38
Duration: 4ms
Database: postgres
Date: 2026-03-09 11:40:07
Duration: 1ms
Database: postgres
Date: 2026-03-09 11:21:07
Duration: 1ms
Database: postgres
Date: 2026-03-09 11:52:46
Duration: 2ms
Database: postgres
Date: 2026-03-09 11:10:04
Duration: 3ms
Database: postgres
Date: 2026-03-09 11:30:02
Duration: 3ms
Database: postgres
Date: 2026-03-09 11:47:08
Duration: 0ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

24s901ms

2,914

Details

0ms

51ms

8ms

WITH rar_max as ( ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Mar 09	11	2,914	24s901ms	8ms

WITH rar_max as ( ;

Date: 2026-03-09 11:45:03 Duration: 51ms Database: postgres parameters: $1 = '607807306703877301', $2 = '607807306703877301', $3 = '607807306703877301'
WITH rar_max as ( ;

Date: 2026-03-09 11:30:42 Duration: 48ms Database: postgres parameters: $1 = '607807069395771301', $2 = '607807069395771301', $3 = '607807069395771301'
WITH rar_max as ( ;

Date: 2026-03-09 11:15:42 Duration: 48ms Database: postgres parameters: $1 = '607807068783220301', $2 = '607807068783220301', $3 = '607807068783220301'

2

9s993ms

27,657

Details

0ms

13ms

0ms

SELECT ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	11	27,657	9s993ms	0ms

SELECT ;

Date: 2026-03-09 11:52:02 Duration: 13ms Database: postgres parameters: $1 = '515840243194668300'
SELECT ;

Date: 2026-03-09 11:52:02 Duration: 10ms Database: postgres parameters: $1 = '515840243194668300'
SELECT ;

Date: 2026-03-09 11:00:02 Duration: 9ms Database: postgres parameters: $1 = '515840243194668300'

3

2s718ms

1,133

Details

1ms

9ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	11	1,133	2s718ms	2ms

SELECT symbolid, ;

Date: 2026-03-09 11:01:14 Duration: 9ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'VIX', $4 = 'XAGUSD', $5 = 'XAUUSD'
SELECT symbolid, ;

Date: 2026-03-09 11:30:39 Duration: 5ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '15', $3 = 'DASHUSD', $4 = 'EOSUSD', $5 = 'CADJPY', $6 = 'CL_BRENT', $7 = 'CHFJPY'
SELECT symbolid, ;

Date: 2026-03-09 11:47:10 Duration: 4ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'BTCAPL', $4 = 'BCHJPY', $5 = 'BCHUSD', $6 = 'AUDUSD'

4

705ms

406

Details

1ms

9ms

1ms

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

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	11	406	705ms	1ms

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

Date: 2026-03-09 11:00:24 Duration: 9ms Database: postgres parameters: $1 = 'BDSWISS'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-03-09 11:30:17 Duration: 3ms Database: postgres parameters: $1 = 'ATFX'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-03-09 11:30:11 Duration: 2ms Database: postgres parameters: $1 = 'FPMARKETS'

5

681ms

26

Details

0ms

44ms

26ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	11	26	681ms	26ms

with wh_patitioned as ( ;

Date: 2026-03-09 11:36:17 Duration: 44ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2026-03-09 11:46:58 Duration: 44ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2026-03-09 11:52:02 Duration: 42ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'

6

560ms

16

Details

28ms

45ms

35ms

with sym_info as ( ;

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	11	16	560ms	35ms

with sym_info as ( ;

Date: 2026-03-09 11:51:56 Duration: 45ms Database: postgres parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'
with sym_info as ( ;

Date: 2026-03-09 11:36:50 Duration: 43ms 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: 2026-03-09 11:51:52 Duration: 43ms Database: postgres parameters: $1 = '627', $2 = 'Forex', $3 = 'Forex', $4 = '627', $5 = 'Forex', $6 = '627', $7 = '627', $8 = 'Forex', $9 = '627'

7

480ms

21,048

Details

0ms

4ms

0ms

select 1;

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	11	21,048	480ms	0ms

select 1;

Date: 2026-03-09 11:14:15 Duration: 4ms Database: postgres
select 1;

Date: 2026-03-09 11:50:09 Duration: 3ms Database: postgres
select 1;

Date: 2026-03-09 11:07:35 Duration: 3ms Database: postgres

8

382ms

54

Details

4ms

15ms

7ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	11	54	382ms	7ms

WITH last_candle AS ( ;

Date: 2026-03-09 11:52:00 Duration: 15ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-03-09 11:12:00 Duration: 14ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-03-09 11:52:02 Duration: 14ms Database: postgres parameters: $1 = '538', $2 = '538'

9

295ms

24

Details

10ms

18ms

12ms

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

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	11	24	295ms	12ms

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

Date: 2026-03-09 11:17:14 Duration: 18ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;

Date: 2026-03-09 11:47:05 Duration: 18ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;

Date: 2026-03-09 11:59:26 Duration: 17ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

10

228ms

5,755

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
	11	5,755	228ms	0ms

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

Date: 2026-03-09 11:32:21 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 12:00:00', $2 = '8574', $3 = '8610', $4 = '8568.5', $5 = '8605', $6 = '422', $7 = '515840245910095300', $8 = '0', $9 = '2026-03-09 11:32:21.193', $10 = '2026-03-09 11:32:20.989', $11 = '8574', $12 = '8610', $13 = '8568.5', $14 = '8605', $15 = '422', $16 = '0', $17 = '2026-03-09 11:32:21.193', $18 = '2026-03-09 11:32:20.989'
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-03-09 11:17:04 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 12:00:00', $2 = '116.8735', $3 = '116.883', $4 = '116.7425', $5 = '116.77', $6 = '2552', $7 = '515840230443624300', $8 = '0', $9 = '2026-03-09 11:17:04.313', $10 = '2026-03-09 11:17:04.207', $11 = '116.8735', $12 = '116.883', $13 = '116.7425', $14 = '116.77', $15 = '2552', $16 = '0', $17 = '2026-03-09 11:17:04.314', $18 = '2026-03-09 11:17:04.207'
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-03-09 11:26:37 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 11:00:00', $2 = '8575.4', $3 = '8611.9', $4 = '8570.05', $5 = '8604.9', $6 = '3257', $7 = '515840248015086300', $8 = '0', $9 = '2026-03-09 11:26:37.635', $10 = '2026-03-09 11:26:37.528', $11 = '8575.4', $12 = '8611.9', $13 = '8570.05', $14 = '8604.9', $15 = '3257', $16 = '0', $17 = '2026-03-09 11:26:37.635', $18 = '2026-03-09 11:26:37.528'

11

222ms

3,347

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
	11	3,347	222ms	0ms

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

Date: 2026-03-09 11:32:06 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 12:00:00', $2 = '203.293', $3 = '203.3655', $4 = '203.1775', $5 = '203.289', $6 = '8503', $7 = '515840230446646300', $8 = '0', $9 = '2026-03-09 11:32:06.858', $10 = '2026-03-09 11:32:06.857', $11 = '203.293', $12 = '203.3655', $13 = '203.1775', $14 = '203.289', $15 = '8503', $16 = '0', $17 = '2026-03-09 11:32:06.858', $18 = '2026-03-09 11:32:06.857'
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-03-09 11:30:51 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 09:00:00', $2 = '0.69928', $3 = '0.70129', $4 = '0.69882', $5 = '0.701035', $6 = '62450000000', $7 = '515840249727304300', $8 = '0', $9 = '2026-03-09 11:30:51.819', $10 = '2026-03-09 11:30:51.819', $11 = '0.69928', $12 = '0.70129', $13 = '0.69882', $14 = '0.701035', $15 = '62450000000', $16 = '0', $17 = '2026-03-09 11:30:51.819', $18 = '2026-03-09 11:30:51.819'
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-03-09 11:30:58 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 12:00:00', $2 = '1.03928', $3 = '1.03961', $4 = '1.03874', $5 = '1.03943', $6 = '8963', $7 = '515840243898525300', $8 = '0', $9 = '2026-03-09 11:30:58.367', $10 = '2026-03-09 11:30:58.366', $11 = '1.03928', $12 = '1.03961', $13 = '1.03874', $14 = '1.03943', $15 = '8963', $16 = '0', $17 = '2026-03-09 11:30:58.367', $18 = '2026-03-09 11:30:58.366'

12

158ms

2,178

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
	11	2,178	158ms	0ms

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

Date: 2026-03-09 11:01:14 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 11:00:00', $2 = '1599.04', $3 = '1600.48', $4 = '1583.56', $5 = '1594.85', $6 = '3026', $7 = '515840238063675300', $8 = '0', $9 = '2026-03-09 11:01:14.886', $10 = '2026-03-09 11:01:14.871', $11 = '1599.04', $12 = '1600.48', $13 = '1583.56', $14 = '1594.85', $15 = '3026', $16 = '0', $17 = '2026-03-09 11:01:14.886', $18 = '2026-03-09 11:01:14.871'
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-03-09 11:02:50 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 09:00:00', $2 = '24202.9', $3 = '24290.3', $4 = '24187.1', $5 = '24226.5', $6 = '20091', $7 = '515840248039327300', $8 = '0', $9 = '2026-03-09 11:02:50.511', $10 = '2026-03-09 11:02:50.392', $11 = '24202.9', $12 = '24290.3', $13 = '24187.1', $14 = '24226.5', $15 = '20091', $16 = '0', $17 = '2026-03-09 11:02:50.511', $18 = '2026-03-09 11:02:50.392'
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-03-09 11:17:16 Duration: 0ms Database: postgres parameters: $1 = '2026-03-07 00:00:00', $2 = '83.888', $3 = '84.587', $4 = '83.834', $5 = '84.466', $6 = '5125', $7 = '515840249469019300', $8 = '0', $9 = '2026-03-09 11:17:16.942', $10 = '2026-03-09 11:17:16.941', $11 = '83.888', $12 = '84.587', $13 = '83.834', $14 = '84.466', $15 = '5125', $16 = '0', $17 = '2026-03-09 11:17:16.942', $18 = '2026-03-09 11:17:16.941'

13

94ms

916

Details

0ms

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

Times Reported Time consuming bind #13

Day	Hour	Count	Duration	Avg duration
	11	916	94ms	0ms

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

Date: 2026-03-09 11:17:21 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 08:00:00', $2 = '8560.3', $3 = '8609.8', $4 = '8548.8', $5 = '8574.5', $6 = '6208', $7 = '515840245911218300', $8 = '0', $9 = '2026-03-09 11:17:21.091', $10 = '2026-03-09 11:17:21.09', $11 = '8560.3', $12 = '8609.8', $13 = '8548.8', $14 = '8574.5', $15 = '6208', $16 = '0', $17 = '2026-03-09 11:17:21.091', $18 = '2026-03-09 11:17:21.09'
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-03-09 11:01:59 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 08:00:00', $2 = '0.69923', $3 = '0.70222', $4 = '0.698175', $5 = '0.699275', $6 = '37625', $7 = '515840230436480300', $8 = '0', $9 = '2026-03-09 11:01:59.923', $10 = '2026-03-09 11:01:59.922', $11 = '0.69923', $12 = '0.70222', $13 = '0.698175', $14 = '0.699275', $15 = '37625', $16 = '0', $17 = '2026-03-09 11:01:59.923', $18 = '2026-03-09 11:01:59.922'
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-03-09 11:02:14 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 08:00:00', $2 = '1.64835', $3 = '1.65166', $4 = '1.645375', $5 = '1.649515', $6 = '50981', $7 = '515840230460794300', $8 = '0', $9 = '2026-03-09 11:02:14.059', $10 = '2026-03-09 11:02:14.059', $11 = '1.64835', $12 = '1.65166', $13 = '1.645375', $14 = '1.649515', $15 = '50981', $16 = '0', $17 = '2026-03-09 11:02:14.059', $18 = '2026-03-09 11:02:14.059'

14

66ms

74

Details

0ms

1ms

0ms

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 #14

Day	Hour	Count	Duration	Avg duration
	11	74	66ms	0ms

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: 2026-03-09 11:36:15 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'EURUSD', $3 = '558'
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: 2026-03-09 11:21:59 Duration: 1ms Database: postgres parameters: $1 = '667', $2 = 'USDJPY', $3 = '667'
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: 2026-03-09 11:21:50 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'XAUEUR', $3 = '558'

15

50ms

301

Details

0ms

3ms

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 #15

Day	Hour	Count	Duration	Avg duration
	11	301	50ms	0ms

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

Date: 2026-03-09 11:50:40 Duration: 3ms Database: postgres parameters: $1 = '607807306191804301'
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;

Date: 2026-03-09 11:20:42 Duration: 3ms Database: postgres parameters: $1 = '607807067628940301'
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;

Date: 2026-03-09 11:35:54 Duration: 2ms Database: postgres parameters: $1 = '607807186346190301'

16

47ms

418

Details

0ms

1ms

0ms

select category, ;

Times Reported Time consuming bind #16

Day	Hour	Count	Duration	Avg duration
	11	418	47ms	0ms

select category, ;

Date: 2026-03-09 11:41:44 Duration: 1ms Database: postgres parameters: $1 = '605717914809373307', $2 = 'symbol', $3 = 'AUDJPY', $4 = 'NZDJPY', $5 = 'GBPJPY', $6 = 'CHFJPY', $7 = 'CADJPY', $8 = 'EURJPY', $9 = 'GBPAUD', $10 = 'GBPNZD', $11 = 'EURAUD', $12 = 'EURNZD', $13 = 'GBPCAD', $14 = 'EURGBP', $15 = 'EURCAD', $16 = 'EURCHF', $17 = 'EURNZD', $18 = 'CADCHF', $19 = 'AUDCHF', $20 = 'GBPCAD', $21 = 'GBPCHF', $22 = 'CADJPY', $23 = 'AUDJPY', $24 = 'GBPJPY', $25 = 'NZDCAD', $26 = 'CHFJPY', $27 = 'USDSGD', $28 = 'GBPNZD', $29 = 'EURCAD', $30 = 'NZDUSD', $31 = 'EURAUD', $32 = 'AUDNZD', $33 = 'AUDCAD', $34 = 'GBPAUD', $35 = 'NZDUSD', $36 = 'NZDJPY', $37 = 'GBPCHF', $38 = 'NZDCHF', $39 = 'AUDCAD', $40 = 'USDSGD', $41 = 'NZDCAD', $42 = 'EURJPY', $43 = 'AUDCHF', $44 = 'AUDNZD', $45 = 'EURCHF', $46 = 'NZDCHF', $47 = 'CADCHF', $48 = 'EURGBP', $49 = '605717914809373307', $50 = 'symbol', $51 = 'AUDJPY', $52 = 'NZDJPY', $53 = 'GBPJPY', $54 = 'CHFJPY', $55 = 'CADJPY', $56 = 'EURJPY', $57 = 'GBPAUD', $58 = 'GBPNZD', $59 = 'EURAUD', $60 = 'EURNZD', $61 = 'GBPCAD', $62 = 'EURGBP', $63 = 'EURCAD', $64 = 'EURCHF', $65 = 'EURNZD', $66 = 'CADCHF', $67 = 'AUDCHF', $68 = 'GBPCAD', $69 = 'GBPCHF', $70 = 'CADJPY', $71 = 'AUDJPY', $72 = 'GBPJPY', $73 = 'NZDCAD', $74 = 'CHFJPY', $75 = 'USDSGD', $76 = 'GBPNZD', $77 = 'EURCAD', $78 = 'NZDUSD', $79 = 'EURAUD', $80 = 'AUDNZD', $81 = 'AUDCAD', $82 = 'GBPAUD', $83 = 'NZDUSD', $84 = 'NZDJPY', $85 = 'GBPCHF', $86 = 'NZDCHF', $87 = 'AUDCAD', $88 = 'USDSGD', $89 = 'NZDCAD', $90 = 'EURJPY', $91 = 'AUDCHF', $92 = 'AUDNZD', $93 = 'EURCHF', $94 = 'NZDCHF', $95 = 'CADCHF', $96 = 'EURGBP'
select category, ;

Date: 2026-03-09 11:41:56 Duration: 0ms Database: postgres parameters: $1 = '605717914811078307', $2 = 'symbol', $3 = 'US30', $4 = 'UK100', $5 = 'US500', $6 = 'USTEC', $7 = 'US2000', $8 = 'JP225', $9 = 'DE30', $10 = 'AUS200', $11 = 'CHINA50', $12 = 'F40', $13 = 'STOXX50', $14 = 'HK50', $15 = 'IT40', $16 = 'US2000', $17 = 'US30', $18 = 'ES35', $19 = 'UK100', $20 = 'USTEC', $21 = 'AUS200', $22 = 'US500', $23 = 'JP225', $24 = 'CHINA50', $25 = 'DE30', $26 = 'STOXX50', $27 = 'F40', $28 = 'HK50', $29 = 'ES35', $30 = 'IT40', $31 = '605717914811078307', $32 = 'symbol', $33 = 'US30', $34 = 'UK100', $35 = 'US500', $36 = 'USTEC', $37 = 'US2000', $38 = 'JP225', $39 = 'DE30', $40 = 'AUS200', $41 = 'CHINA50', $42 = 'F40', $43 = 'STOXX50', $44 = 'HK50', $45 = 'IT40', $46 = 'US2000', $47 = 'US30', $48 = 'ES35', $49 = 'UK100', $50 = 'USTEC', $51 = 'AUS200', $52 = 'US500', $53 = 'JP225', $54 = 'CHINA50', $55 = 'DE30', $56 = 'STOXX50', $57 = 'F40', $58 = 'HK50', $59 = 'ES35', $60 = 'IT40'
select category, ;

Date: 2026-03-09 11:11:17 Duration: 0ms Database: postgres parameters: $1 = '604104683405466307', $2 = 'symbol', $3 = 'USDMXN', $4 = 'EURZAR', $5 = 'USDTHB', $6 = 'USDZAR', $7 = 'USDHUF', $8 = 'USDSEK', $9 = 'EURTRY', $10 = 'SGDJPY', $11 = 'EURHKD', $12 = 'GBPSEK', $13 = 'SEKJPY', $14 = 'USDDKK', $15 = 'USDNOK', $16 = 'EURSEK', $17 = 'USDCZK', $18 = 'NOKJPY', $19 = 'GBPDKK', $20 = 'USDPLN', $21 = 'GBPNOK', $22 = 'EURNOK', $23 = 'EURPLN', $24 = 'USDTRY', $25 = 'USDCNH', $26 = 'SEKJPY', $27 = 'EURNOK', $28 = 'NOKJPY', $29 = 'GBPSGD', $30 = 'USDHUF', $31 = 'GBPNOK', $32 = 'USDMXN', $33 = 'CHFSGD', $34 = 'EURDKK', $35 = 'EURSGD', $36 = 'USDZAR', $37 = 'GBPSGD', $38 = 'CHFSGD', $39 = 'GBPDKK', $40 = 'USDHKD', $41 = 'USDCZK', $42 = 'EURZAR', $43 = 'EURSEK', $44 = 'USDPLN', $45 = 'USDSEK', $46 = 'USDTHB', $47 = 'NOKSEK', $48 = 'USDDKK', $49 = 'USDNOK', $50 = 'EURHKD', $51 = 'EURPLN', $52 = 'EURTRY', $53 = '604104683405466307', $54 = 'symbol', $55 = 'USDMXN', $56 = 'EURZAR', $57 = 'USDTHB', $58 = 'USDZAR', $59 = 'USDHUF', $60 = 'USDSEK', $61 = 'EURTRY', $62 = 'SGDJPY', $63 = 'EURHKD', $64 = 'GBPSEK', $65 = 'SEKJPY', $66 = 'USDDKK', $67 = 'USDNOK', $68 = 'EURSEK', $69 = 'USDCZK', $70 = 'NOKJPY', $71 = 'GBPDKK', $72 = 'USDPLN', $73 = 'GBPNOK', $74 = 'EURNOK', $75 = 'EURPLN', $76 = 'USDTRY', $77 = 'USDCNH', $78 = 'SEKJPY', $79 = 'EURNOK', $80 = 'NOKJPY', $81 = 'GBPSGD', $82 = 'USDHUF', $83 = 'GBPNOK', $84 = 'USDMXN', $85 = 'CHFSGD', $86 = 'EURDKK', $87 = 'EURSGD', $88 = 'USDZAR', $89 = 'GBPSGD', $90 = 'CHFSGD', $91 = 'GBPDKK', $92 = 'USDHKD', $93 = 'USDCZK', $94 = 'EURZAR', $95 = 'EURSEK', $96 = 'USDPLN', $97 = 'USDSEK', $98 = 'USDTHB', $99 = 'NOKSEK', $100 = 'USDDKK', $101 = 'USDNOK', $102 = 'EURHKD', $103 = 'EURPLN', $104 = 'EURTRY'

17

46ms

1

Details

46ms

with maxwhid as ( ;

Times Reported Time consuming bind #17

Day	Hour	Count	Duration	Avg duration
	11	1	46ms	46ms

with maxwhid as ( ;

Date: 2026-03-09 11:12:15 Duration: 46ms 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

45ms

153

Details

0ms

4ms

0ms

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

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	11	153	45ms	0ms

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

Date: 2026-03-09 11:35:43 Duration: 4ms Database: postgres parameters: $1 = '607806477386320303'
/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-03-09 11:53:30 Duration: 4ms Database: postgres parameters: $1 = '607793803666580303'
/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-03-09 11:05:11 Duration: 3ms Database: postgres parameters: $1 = '607805772457207303'

19

37ms

9

Details

3ms

5ms

4ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #19

Day	Hour	Count	Duration	Avg duration
	11	9	37ms	4ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-03-09 11:15:03 Duration: 5ms Database: postgres parameters: $1 = '667', $2 = '667'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-03-09 11:47:08 Duration: 5ms Database: postgres parameters: $1 = '689', $2 = '689'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-03-09 11:36:11 Duration: 4ms Database: postgres parameters: $1 = '627', $2 = '627'

20

36ms

8

Details

2ms

8ms

4ms

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

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	11	8	36ms	4ms

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

Date: 2026-03-09 11:14:02 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', $119 = '5'
WITH pre_symbols AS ( /* find relevant symbols */ ;

Date: 2026-03-09 11:14:02 Duration: 6ms 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: 2026-03-09 11:14:02 Duration: 3ms 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'

Log levels

Key values

411,954 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	412	0.10%
DETAIL	94,326	22.90%
ERROR	397	0.10%
LOG	315,650	76.62%
STATEMENT	1,169	0.28%

Events distribution

Key values

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

Most Frequent Errors/Events

Key values

358 Max number of times the same event was reported
397 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
Mar 09	11	358

ERROR: pg_stat_statements must be loaded via shared_preload_libraries

2

39

Details

ERROR: schema "..." does not exist

Times Reported Most Frequent Error / Event #2

Day	Hour	Count
Mar 09	11	39

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

Global information

Overview

Global Stats

SQL Traffic

Key values

SELECT Traffic

Key values

INSERT/UPDATE/DELETE Traffic

Key values

Queries duration

Key values

Prepared queries ratio

Key values

General Activity

Connections

Established Connections

Key values

Connections per database

Key values

Connections per user

Key values

Connections per host

Key values

Sessions

Simultaneous sessions

Key values

Histogram of session times

Key values

Sessions per database

Key values

Sessions per user

Key values

Sessions per host

Key values

Sessions per application

Key values

Checkpoints / Restartpoints

Checkpoints Buffers

Key values

Checkpoints Wal files

Key values

Checkpoints distance

Key values

Checkpoints Activity

Checkpoint causes

Key values

Temporary Files

Size of temporary files

Key values

Number of temporary files

Key values

Temporary Files Activity

Queries generating the most temporary files (N)

Queries generating the largest temporary files

Vacuums

Vacuums / Analyzes Distribution

Key values

Analyzes per table

Key values

Vacuums per table

Key values

Tuples removed per table

Key values

Pages removed per table

Key values

Autovacuum Activity

Locks

Locks by types

Key values

Type of locks

Most frequent waiting queries (N)

Queries that waited the most

Queries

Queries by type

Key values

Queries by database

Key values

Queries by user

Key values

Duration by user