pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Mon Mar 9 02:59:35 2026
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-03-09_040000.log
Parsed 1,337,475 log entries in 34s
Log start from 2026-03-09 04:00:00 to 2026-03-09 04:59:33

Global Stats

227 Number of unique normalized queries
166,559 Number of queries
1h44m10s Total query duration
2026-03-09 04:00:00 First query
2026-03-09 04:59:33 Last query
2,324 queries/s at 2026-03-09 04:30:03 Query peak

1h44m10s Total query duration
6s443ms Prepare/parse total duration
39s341ms Bind total duration
1h43m24s Execute total duration

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

40 Total number of automatic vacuums
54 Total number of automatic analyzes

1,019 Number temporary file
192.92 MiB Max size of temporary file
6.36 MiB Average size of temporary file

2,595 Total number of sessions
12 sessions at 2026-03-09 04:54:06 Session peak
4d5h13m31s Total duration of sessions
2m20s Average duration of sessions
64 Average queries per session
2s408ms Average queries duration per session
2m18s Average idle time per session

2,595 Total number of connections
28 connections/s at 2026-03-09 04:48:48 Connection peak
3 Total number of databases

SQL Traffic

Key values

2,324 queries/s Query Peak
2026-03-09 04:30:03 Date

SELECT Traffic

Key values

1,115 queries/s Query Peak
2026-03-09 04:30:03 Date

INSERT/UPDATE/DELETE Traffic

Key values

194 queries/s Query Peak
2026-03-09 04:00:53 Date

Queries duration

Key values

1h44m10s 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	04	166,559	0ms	32s886ms	37ms	2m57s	3m16s	3m32s

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Mar 09	04	53,436	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	04	20,031	1,536	16	96	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Mar 09	04	16,868	52,429	3.11	21.18%

Day	Hour	Count	Average / Second
Mar 09	04	2,595	0.72/s

Day	Hour	Count	Average Duration	Average idle time
Mar 09	04	2,595	2m20s	2m18s

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Established Connections

Key values

28 connections Connection Peak
2026-03-09 04:48:48 Date

Connections per database

Key values

acaweb_fx Main Database
2,595 connections Total

Chart
Table

Database	User	Count
acaweb_fx		2,526
	postgres	2,168
	psql	358
socialmedia		69
	postgres	69

Connections per user

Key values

postgres Main User
2,595 connections Total

Chart
Table

User	Count
postgres	2,237
psql	358

Connections per host

Key values

192.168.4.142 Main host with 926 connections
2,595 Total connections

Chart
Table

Host	Count
127.0.0.1	111
192.168.0.114	1
192.168.0.216	106
192.168.0.74	272
192.168.1.145	140
192.168.1.15	60
192.168.1.20	152
192.168.1.239	20
192.168.1.90	40
192.168.2.126	38
192.168.2.182	12
192.168.3.199	36
192.168.4.142	926
192.168.4.150	10
192.168.4.180	6
192.168.4.238	14
192.168.4.33	69
192.168.4.83	1
192.168.4.87	4
192.168.4.98	330
[local]	247

Simultaneous sessions

Key values

12 sessions Session Peak
2026-03-09 04:54:06 Date

Histogram of session times

Key values

2,114 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	2,114	81.46%
500ms-1s	128	4.93%
1s-30s	261	10.06%
30s-1m	8	0.31%
1m-10m	26	1.00%
10m-30m	36	1.39%
30m-1h	4	0.15%
1h-8h	15	0.58%
> 8h	3	0.12%

Sessions per database

Key values

acaweb_fx Main Database
2,595 sessions Total

Chart
Table

Database	User	Count	Total Duration	Average Duration
acaweb_fx	2,526	4d5h12m53s	2m24s
socialmedia	69	37s298ms	540ms

Sessions per user

Key values

postgres Main User
2,595 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
2,595 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
127.0.0.1	111	12s186ms	109ms
192.168.0.114	1	5m4s	5m4s
192.168.0.216	106	3m23s	1s923ms
192.168.0.74	272	4h30m15s	59s614ms
192.168.1.145	140	6h50m35s	2m55s
192.168.1.15	60	1d13h24m25s	37m24s
192.168.1.20	152	1d8h3m55s	12m39s
192.168.1.239	20	351ms	17ms
192.168.1.90	40	38s74ms	951ms
192.168.2.126	38	5s655ms	148ms
192.168.2.182	12	866ms	72ms
192.168.3.199	36	1s502ms	41ms
192.168.4.142	926	7m20s	475ms
192.168.4.150	10	20h2m46s	2h16s
192.168.4.180	6	67ms	11ms
192.168.4.238	14	16s765ms	1s197ms
192.168.4.33	69	37s298ms	540ms
192.168.4.83	1	228ms	228ms
192.168.4.87	4	7s599ms	1s899ms
192.168.4.98	330	15s101ms	45ms
[local]	247	3m28s	843ms

Sessions per application

Key values

unknown Main Host
2,595 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	2,595	4d5h13m31s	2m20s

Checkpoints Buffers

Key values

53,619 buffers Checkpoint Peak
2026-03-09 04:11:05 Date
210.027 seconds Highest write time
0.038 seconds Sync time

Checkpoints Wal files

Key values

8 files Wal files usage Peak
2026-03-09 04:11:05 Date

Checkpoints distance

Key values

281.42 Mo Distance Peak
2026-03-09 04:11:05 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Mar 09	04	85,598	1,712.503s	0.101s	1,712.917s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Mar 09	04	0	0	25	1,758	0.009s	0s

Day	Hour	Count	Avg time (sec)
Mar 09	04	0	0s

Day	Hour	Mean distance	Mean estimate
Mar 09	04	34,504.92 kB	95,888.25 kB

↑ Back to the top of the Checkpoint Activity table

Checkpoint causes

Key values

time (12) Main checkpoint cause
12 checkpoints Total

Chart
Table

Cause	Number of checkpoints
time	12
Total	12

Size of temporary files

Key values

183.97 MiB Temp Files size Peak
2026-03-09 04:20:08 Date

Number of temporary files

Key values

33 per second Temp Files Peak
2026-03-09 04:47:09 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Mar 09	04	1,019	6.33 GiB	6.36 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	261	430.77 MiB	137.65 KiB	3.89 MiB	1.65 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)) AND ($15 = 0 OR ar.pattern in ($16)) AND ($17 = 0 OR ($18 = 1 AND ar.breakout >= 0) OR ($19 = 2 AND ar.breakout < 0)) AND ($20 = 0 OR ar.patternlengthbars <= $21) 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 = $22 OR relevant = 1) AND ($23 = 0 OR age <= $24) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-03-09 04:00:02 Duration: 0ms
2	78	136.54 MiB	137.65 KiB	4.57 MiB	1.75 MiB	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 ? ; WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = $1 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4)) AND ($5 = 0 OR s.exchange in ($6)) AND ($7 = 0 OR coalesce(bim.code, s.symbol) in ($8)) AND ($9 = 0 OR p.patternname in ($10)) AND ($11 = 0 OR kr.patternclassid in ($12)) AND ($13 = 0 OR kr.patternlengthbars <= $14) AND kr.patternstarttime::timestamp without time zone >= 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 = $15 OR relevant = 1) AND ($16 = 0 OR age <= $17) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200; Date: 2026-03-09 04:02:51 Duration: 0ms
3	68	349.16 MiB	5.07 MiB	5.20 MiB	5.13 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)) AND ($15 = 0 OR fr.pattern in ($16)) AND ($17 = 0 OR fr.patternlengthbars <= $18) AND ($19 = 0 OR ($20 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($21 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) FROM all_results WHERE (FALSE = $22 OR relevant = 1) AND ($23 = 0 OR age <= $24) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-03-09 04:00:12 Duration: 0ms
4	30	1.66 GiB	3.74 MiB	192.92 MiB	56.72 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 04:00:06 Duration: 0ms
5	16	739.12 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 04:01:13 Duration: 0ms
6	16	52.65 MiB	3.21 MiB	3.49 MiB	3.29 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 04:01:08 Duration: 0ms
7	16	1.23 GiB	78.43 MiB	78.43 MiB	78.43 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 04:01:16 Duration: 0ms
8	12	102.94 MiB	8.57 MiB	8.59 MiB	8.58 MiB	jr.resultuid as resultuid, jr.direction as direction, jr.patternendtime as identified, jr.patternlengthbars as length, jr.patternstarttime as patternstarttime, case when jr.trendchangeid = ? then ? else ? end as trendchange, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, jp.patternname as pattern_name, dtt.timezone as timezone, ? as age, cps.pip, g.basegroupname from japsticks_results jr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = jr.symbolid inner join relevance_japsticks_results rar on rar.resultuid = jr.resultuid inner join symbols s on jr.symbolid = s.symbolid and s.nonliquid = ? inner join japsticks_patterns jp on jr.patternid = jp.id inner join downloadersymbolsettings dss on jr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where jr.gmttimefound > now() - interval ? and s.deleted = ? and (jr.simulation = ? or jr.simulation is null) and (rar.relevant = ?) --and (semicolon_age = ? or rar.age <= semicolon_age) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or jp.patternname in (...)) and (? = ? or jr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results order by symbolid, resultuid ) select * from results order by identified desc, length desc ; jr.resultuid AS resultuid, jr.direction AS direction, jr.patternendtime AS identified, jr.patternlengthbars AS length, jr.patternstarttime AS patternstarttime, case when jr.trendchangeid = 1 then 'Continuation' else 'Reversal' end AS trendchange, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, jp.patternname AS pattern_name, dtt.timezone AS timezone, 0 AS age, cps.pip, g.basegroupname FROM japsticks_results jr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = jr.symbolid INNER JOIN relevance_japsticks_results rar ON rar.resultuid = jr.resultuid INNER JOIN symbols s ON jr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN japsticks_patterns jp ON jr.patternid = jp.id INNER JOIN downloadersymbolsettings dss ON jr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE jr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (jr.simulation = 0 OR jr.simulation IS NULL) AND (rar.relevant = 1) --AND (semicolon_age = 0 OR rar.age <= semicolon_age) AND ($2 = 0 OR s.timegranularity in ($3)) AND ($4 = 0 OR s.exchange in ($5)) AND ($6 = 0 OR coalesce(bim.code, s.symbol) in ($7)) AND ($8 = 0 OR jp.patternname in ($9)) AND ($10 = 0 OR jr.patternlengthbars <= $11)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-03-09 04:03:15 Duration: 0ms
9	8	1.08 GiB	138.24 MiB	138.27 MiB	138.26 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2026-03-09 04:02:20 Duration: 0ms
10	4	311.50 MiB	77.83 MiB	77.94 MiB	77.88 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2026-03-09 04:02:06 Duration: 0ms
11	1	173.36 MiB	173.36 MiB	173.36 MiB	173.36 MiB	select cleanupconsecutivecandlesresults (); select cleanupconsecutivecandlesresults (); Date: 2026-03-09 04:05:08 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	192.92 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 04:00:04 ]
2	173.36 MiB	select cleanupconsecutivecandlesresults (); [ Date: 2026-03-09 04:05:08 ]
3	163.17 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 04:50:05 ]
4	156.61 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 04:30:08 ]
5	138.27 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 04:47:13 ]
6	138.27 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 04:32:13 ]
7	138.27 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 04:50:32 ]
8	138.26 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 04:35:32 ]
9	138.26 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 04:17:16 ]
10	138.26 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 04:02:20 ]
11	138.25 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 04:20:33 ]
12	138.24 MiB	select updateresultsmaterializedview (); [ Date: 2026-03-09 04:05:34 ]
13	137.70 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 04:10:04 ]
14	99.87 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 = 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 04:20:05 ]
15	97.45 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 04:40:04 ]
16	92.16 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 04:20:05 ]
17	78.43 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 04:01:16 ]
18	78.43 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 04:03:15 ]
19	78.43 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 04:05:15 ]
20	78.43 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 04:11:16 ]

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)
54 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	4
acaweb_fx.pg_catalog.pg_type	4
acaweb_fx.public.datafeeds_latestrun	3
acaweb_fx.pg_catalog.pg_index	2
acaweb_fx.public.latest_t15_candle_view	2
acaweb_fx.pg_catalog.pg_depend	2
acaweb_fx.public.relevance_keylevels_results	2
acaweb_fx.public.latest_candle_datetime_per_receng	2
acaweb_fx.public.relevance_fibonacci_results	2
acaweb_fx.public.relevance_autochartist_results	2
acaweb_fx.public.autochartist_symbolupdates	1
acaweb_fx.public.solr_imports	1
acaweb_fx.public.sa_hist_bigmove	1
acaweb_fx.public.relevance_consecutivecandles_results	1
acaweb_fx.public.sa_hist_consecutivecandles	1
Total	54

Vacuums per table

Key values

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

Chart
Table

		Index	Buffer usage			Skipped		WAL usage
Table	Vacuums	scans	hits	misses	dirtied	pins	frozen	records	full page	bytes
acaweb_fx.public.solr_relevance_old	16	16	10,779	0	48	0	0	7,334	16	1,343,471
acaweb_fx.public.datafeeds_latestrun	3	0	347	0	5	0	0	32	5	28,154
acaweb_fx.pg_catalog.pg_attribute	3	3	2,511	0	191	0	201	1,071	182	1,244,398
acaweb_fx.pg_catalog.pg_class	3	3	1,365	0	166	0	0	420	152	722,901
acaweb_fx.pg_toast.pg_toast_2619	2	2	263	0	74	0	0	207	63	223,004
acaweb_fx.pg_catalog.pg_type	2	2	309	0	75	0	0	148	54	271,335
acaweb_fx.pg_catalog.pg_index	1	1	105	0	16	0	0	27	15	93,102
acaweb_fx.public.solr_imports	1	1	43	0	2	0	0	6	2	14,145
acaweb_fx.pg_catalog.pg_depend	1	1	389	0	84	0	59	198	68	329,535
acaweb_fx.public.latest_t15_candle_view	1	1	66	0	1	0	0	6	1	9,073
acaweb_fx.public.relevance_keylevels_results	1	1	3,393	0	614	0	96	902	604	1,538,521
acaweb_fx.public.relevance_fibonacci_results	1	1	1,107	0	15	1	54	160	92	249,306
acaweb_fx.public.sa_hist_bigmove	1	1	5,879	0	1,038	0	52	2,407	900	2,772,634
acaweb_fx.pg_catalog.pg_statistic	1	1	1,007	0	146	0	582	492	121	537,234
acaweb_fx.public.symbollatestupdatetime	1	0	1,355	0	419	0	608	1,228	410	1,138,544
acaweb_fx.public.relevance_autochartist_results	1	1	3,349	0	91	0	250	700	456	1,184,173
acaweb_fx.public.sa_hist_consecutivecandles	1	1	302,363	0	31,077	0	4,226	140,869	31,053	39,072,742
Total	40	36	334,630	47,569	34,062	1	6,128	156,207	34,194	50,772,272

Tuples removed per table

Key values

public.sa_hist_consecutivecandles (300006) Main table with removed tuples on database acaweb_fx
394199 tuples Total removed

Chart
Table

		Index	Tuples			Pages
Table	Vacuums	scans	removed	remain	not yet removable	removed	remain
acaweb_fx.public.sa_hist_consecutivecandles	1	1	300,006	289,814	0	0	41,209
acaweb_fx.public.solr_relevance_old	16	16	42,432	77,141	0	0	2,555
acaweb_fx.public.sa_hist_bigmove	1	1	22,472	45,455	0	0	1,286
acaweb_fx.public.symbollatestupdatetime	1	0	18,608	102,668	0	0	1,714
acaweb_fx.pg_catalog.pg_attribute	3	3	5,362	32,334	252	0	795
acaweb_fx.pg_catalog.pg_depend	1	1	1,383	14,483	90	0	144
acaweb_fx.public.relevance_autochartist_results	1	1	1,129	7,564	0	0	380
acaweb_fx.public.relevance_keylevels_results	1	1	656	11,125	0	0	279
acaweb_fx.pg_catalog.pg_statistic	1	1	584	3,736	0	0	1,194
acaweb_fx.pg_catalog.pg_type	2	2	578	2,946	36	0	88
acaweb_fx.pg_catalog.pg_class	3	3	381	4,968	0	0	450
acaweb_fx.public.relevance_fibonacci_results	1	1	174	1,160	0	0	102
acaweb_fx.public.datafeeds_latestrun	3	0	166	52	10	0	48
acaweb_fx.pg_toast.pg_toast_2619	2	2	152	334	2	0	110
acaweb_fx.public.latest_t15_candle_view	1	1	62	12	0	0	1
acaweb_fx.public.solr_imports	1	1	51	1	0	0	2
acaweb_fx.pg_catalog.pg_index	1	1	3	815	0	0	22
Total	40	36	394,199	594,608	390	0	50,379

Pages removed per table

Key values

unknown (0) Main table with removed pages on database unknown
0 pages Total removed

Chart
Table

Pages removed per tables

NO DATASET

Table	Number of vacuums	Index scans	Tuples removed
acaweb_fx.pg_catalog.pg_index	1	1	3
acaweb_fx.pg_toast.pg_toast_2619	2	2	152
acaweb_fx.public.datafeeds_latestrun	3	0	166
acaweb_fx.public.solr_imports	1	1	51
acaweb_fx.pg_catalog.pg_attribute	3	3	5362
acaweb_fx.pg_catalog.pg_depend	1	1	1383
acaweb_fx.public.latest_t15_candle_view	1	1	62
acaweb_fx.public.relevance_keylevels_results	1	1	656
acaweb_fx.pg_catalog.pg_class	3	3	381
acaweb_fx.public.relevance_fibonacci_results	1	1	174
acaweb_fx.public.sa_hist_bigmove	1	1	22472
acaweb_fx.pg_catalog.pg_type	2	2	578
acaweb_fx.pg_catalog.pg_statistic	1	1	584
acaweb_fx.public.symbollatestupdatetime	1	0	18608
acaweb_fx.public.solr_relevance_old	16	16	42432
acaweb_fx.public.relevance_autochartist_results	1	1	1129
acaweb_fx.public.sa_hist_consecutivecandles	1	1	300006
Total	40	36	394,199

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Mar 09	04	40	54

↑ 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

53,436 Total read queries
26,219 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	53,436	32.08%
INSERT	20,031	12.03%
UPDATE	1,536	0.92%
DELETE	16	0.01%
COPY FROM	96	0.06%
COPY TO	26	0.02%
CTE	3,818	2.29%
DDL	16	0.01%
TCL	680	0.41%
CURSOR	0	0.00%
OTHERS	86,904	52.18%

Queries by database

Key values

unknown Main database
165,627 Requests
1h43m24s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	863	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	179	0ms
	select	74	0ms
	tcl	331	0ms
	update	37	0ms
socialmedia	Total	69	0ms
	select	69	0ms
unknown	Total	165,627	1h43m24s
	copy from	16	0ms
	cte	3,714	0ms
	insert	20,031	0ms
	others	3,645	0ms
	select	53,293	0ms
	tcl	349	0ms
	update	1,499	0ms

Queries by user

Key values

unknown Main user
165,627 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	932	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	179	0ms
	select	143	0ms
	tcl	331	0ms
	update	37	0ms
unknown	Total	165,627	1h43m24s
	copy from	16	0ms
	cte	3,714	0ms
	insert	20,031	0ms
	others	3,645	0ms
	select	53,293	0ms
	tcl	349	0ms
	update	1,499	0ms

Duration by user

Key values

1h43m24s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	932	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	179	0ms
	select	143	0ms
	tcl	331	0ms
	update	37	0ms
unknown	Total	165,627	1h43m24s
	copy from	16	0ms
	cte	3,714	0ms
	insert	20,031	0ms
	others	3,645	0ms
	select	53,293	0ms
	tcl	349	0ms
	update	1,499	0ms

Queries by host

Key values

unknown Main host
166,559 Requests
1h43m24s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	166,559	1h43m24s
	copy from	96	0ms
	copy to	26	0ms
	cte	3,818	0ms
	ddl	16	0ms
	delete	16	0ms
	insert	20,031	0ms
	others	3,824	0ms
	select	53,436	0ms
	tcl	680	0ms
	update	1,536	0ms

Queries by application

Key values

unknown Main application
166,201 Requests
1h43m24s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
psql	Total	358	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	5	0ms
	select	74	0ms
	update	37	0ms
unknown	Total	166,201	1h43m24s
	copy from	16	0ms
	cte	3,714	0ms
	insert	20,031	0ms
	others	3,819	0ms
	select	53,362	0ms
	tcl	680	0ms
	update	1,499	0ms

Number of cancelled queries

Key values

0 per second Cancelled query Peak
2026-03-09 04:22:43 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

49,746 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	49,746	59.88%
1-5ms	25,340	30.50%
5-10ms	2,077	2.50%
10-25ms	1,411	1.70%
25-50ms	1,436	1.73%
50-100ms	1,375	1.66%
100-500ms	721	0.87%
500-1000ms	86	0.10%
1000-10000ms	730	0.88%
> 10000ms	158	0.19%

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

10

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	04	10	0ms	0ms

2

0ms

178

Details

0ms

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

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Mar 09	04	178	0ms	0ms

3

0ms

1

Details

0ms

select trumpetsymbolid as sid, trumpettimegranularity as tg from brokersymbollist bsl left join powerstats_symboldata psd on bsl.symbolid = psd.symbolid left join downloadersymbolsettings dss on psd.symbolid = dss.symbolid left join symbols s on dss.symbolid = s.symbolid left outer join brokerinstrumentmap bdfi on code = ? and bdfi.brokerid = ? and dss.datafeedinstrumentid = bdfi.datafeedinstrumentid where (code = ? or s.symbol = ?) and bsl.brokerid = ? and dss.classname <> ? group by trumpetsymbolid, trumpettimegranularity;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1	0ms	0ms

4

0ms

120

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 #4

Day	Hour	Count	Duration	Avg duration
Mar 09	04	120	0ms	0ms

5

0ms

2,173

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 #5

Day	Hour	Count	Duration	Avg duration
Mar 09	04	2,173	0ms	0ms

6

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 #6

Day	Hour	Count	Duration	Avg duration
Mar 09	04	4	0ms	0ms

7

0ms

137

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Mar 09	04	137	0ms	0ms

8

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Mar 09	04	4	0ms	0ms

9

0ms

1

Details

0ms

select count(*) from autochartist_stocklist where base_engine = recognitionengine and base_engine ilike ?;

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1	0ms	0ms

10

0ms

1,079

Details

0ms

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

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1,079	0ms	0ms

11

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 #11

Day	Hour	Count	Duration	Avg duration
Mar 09	04	18	0ms	0ms

12

0ms

238

Details

0ms

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

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Mar 09	04	238	0ms	0ms

13

0ms

53

Details

0ms

select symbolid, pricedatetime, classname, downloadfrequency, downloadersymbol, open, high, low, close, volume, bsf, sastdatetimereceived from ( select pricedatetime, dss.classname, dss.downloadfrequency, dss.symbolid, dss.downloadersymbol, t.open, t.high, t.low, t.close, t.volume, t.bsf, t.sastdatetimereceived, row_number() over (partition by t.symbolid order by t.pricedatetime desc) as rn from t240 t, downloadersymbolsettings dss, symbols s where dss.classname = ? and dss.downloadfrequency = ? and dss.symbolid = t.symbolid and s.symbolid = dss.symbolid and dss.enabled = ? and s.deleted = ? and dss.downloadersymbol in (...) and t.pricedatetime > now() - interval ?) as ranked_candles_table where rn = ?;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Mar 09	04	53	0ms	0ms

14

0ms

30

Details

0ms

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

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Mar 09	04	30	0ms	0ms

15

0ms

56

Details

0ms

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

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Mar 09	04	56	0ms	0ms

16

0ms

1

Details

0ms

select count(*) from autochartist_stocklist where base_engine = recognitionengine and enabled = ?;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1	0ms	0ms

17

0ms

33

Details

0ms

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

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Mar 09	04	33	0ms	0ms

18

0ms

2

Details

0ms

with pre_symbols as ( select s.symbolid, s.symbol, s.timegranularity, dss.downloadersymbol, dtt.timezone, s.exchange, s.longname 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 and brokerid = ? where dss.classname in (...) and (dss.downloadersymbol in (...) or s.symbol in (...)) and dss.enabled = ? and s.nonliquid = ? and s.deleted = ? ), report_symbols as ( select ps1.*, ps2.symbolid as price_symbol_id from pre_symbols ps1 inner join pre_symbols ps2 on ps1.symbol = ps2.symbol and ps1.downloadersymbol = ps2.downloadersymbol and ps2.timegranularity = ? ), rbr_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ) select bmr.resultuid as ruid, ? as direction, rs.symbol as sym, rs.downloadersymbol, rs.symbolid as sid, rs.timegranularity as tg, rs.timezone, rs.exchange as e, rs.longname, bmr.patternendtime as pet, lpi.latestpricedatetime as lpdt, bmr.patternlengthbars as l, bmr.breakout >= ? as complete, rbr.age as age from bigmovement_results bmr inner join report_symbols rs on rs.symbolid = bmr.symbolid inner join autochartist_symbolupdates lpi on lpi.symbolid = rs.price_symbol_id inner join rbr_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid where patternendtime >= (now() - ? * interval ?) -- results can't be more than ? days old and (bmr.resultuid > rm.resultuid or rbr.relevant = ?) ;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Mar 09	04	2	0ms	0ms

19

0ms

2

Details

0ms

update correlating_signals set sent = true where id = ?;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Mar 09	04	2	0ms	0ms

20

0ms

340

Details

0ms

commit;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Mar 09	04	340	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

15,376

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Mar 09	04	15,376	0ms	0ms

2

7,808

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	04	7,808	0ms	0ms

3

6,031

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	04	6,031	0ms	0ms

4

4,667

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	04	4,667	0ms	0ms

5

3,737

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Mar 09	04	3,737	0ms	0ms

6

3,311

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 #6

Day	Hour	Count	Duration	Avg duration
Mar 09	04	3,311	0ms	0ms

7

2,908

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	04	2,908	0ms	0ms

8

2,847

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 #8

Day	Hour	Count	Duration	Avg duration
Mar 09	04	2,847	0ms	0ms

9

2,173

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Mar 09	04	2,173	0ms	0ms

10

1,795

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 #10

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1,795	0ms	0ms

11

1,623

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1,623	0ms	0ms

12

1,597

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1,597	0ms	0ms

13

1,190

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 #13

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1,190	0ms	0ms

14

1,190

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 #14

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1,190	0ms	0ms

15

1,190

Details

0ms

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

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1,190	0ms	0ms

16

1,190

Details

0ms

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

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1,190	0ms	0ms

17

1,190

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 #17

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1,190	0ms	0ms

18

1,190

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 #18

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1,190	0ms	0ms

19

1,079

Details

0ms

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

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1,079	0ms	0ms

20

1,022

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 #20

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1,022	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

10

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	04	10	0ms	0ms

2

0ms

178

Details

0ms

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

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Mar 09	04	178	0ms	0ms

3

0ms

1

Details

0ms

select trumpetsymbolid as sid, trumpettimegranularity as tg from brokersymbollist bsl left join powerstats_symboldata psd on bsl.symbolid = psd.symbolid left join downloadersymbolsettings dss on psd.symbolid = dss.symbolid left join symbols s on dss.symbolid = s.symbolid left outer join brokerinstrumentmap bdfi on code = ? and bdfi.brokerid = ? and dss.datafeedinstrumentid = bdfi.datafeedinstrumentid where (code = ? or s.symbol = ?) and bsl.brokerid = ? and dss.classname <> ? group by trumpetsymbolid, trumpettimegranularity;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1	0ms	0ms

4

0ms

120

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 #4

Day	Hour	Count	Duration	Avg duration
Mar 09	04	120	0ms	0ms

5

0ms

2,173

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 #5

Day	Hour	Count	Duration	Avg duration
Mar 09	04	2,173	0ms	0ms

6

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 #6

Day	Hour	Count	Duration	Avg duration
Mar 09	04	4	0ms	0ms

7

0ms

137

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Mar 09	04	137	0ms	0ms

8

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Mar 09	04	4	0ms	0ms

9

0ms

1

Details

0ms

select count(*) from autochartist_stocklist where base_engine = recognitionengine and base_engine ilike ?;

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1	0ms	0ms

10

0ms

1,079

Details

0ms

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

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1,079	0ms	0ms

11

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 #11

Day	Hour	Count	Duration	Avg duration
Mar 09	04	18	0ms	0ms

12

0ms

238

Details

0ms

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

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Mar 09	04	238	0ms	0ms

13

0ms

53

Details

0ms

select symbolid, pricedatetime, classname, downloadfrequency, downloadersymbol, open, high, low, close, volume, bsf, sastdatetimereceived from ( select pricedatetime, dss.classname, dss.downloadfrequency, dss.symbolid, dss.downloadersymbol, t.open, t.high, t.low, t.close, t.volume, t.bsf, t.sastdatetimereceived, row_number() over (partition by t.symbolid order by t.pricedatetime desc) as rn from t240 t, downloadersymbolsettings dss, symbols s where dss.classname = ? and dss.downloadfrequency = ? and dss.symbolid = t.symbolid and s.symbolid = dss.symbolid and dss.enabled = ? and s.deleted = ? and dss.downloadersymbol in (...) and t.pricedatetime > now() - interval ?) as ranked_candles_table where rn = ?;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Mar 09	04	53	0ms	0ms

14

0ms

30

Details

0ms

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

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Mar 09	04	30	0ms	0ms

15

0ms

56

Details

0ms

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

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Mar 09	04	56	0ms	0ms

16

0ms

1

Details

0ms

select count(*) from autochartist_stocklist where base_engine = recognitionengine and enabled = ?;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Mar 09	04	1	0ms	0ms

17

0ms

33

Details

0ms

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

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Mar 09	04	33	0ms	0ms

18

0ms

2

Details

0ms

with pre_symbols as ( select s.symbolid, s.symbol, s.timegranularity, dss.downloadersymbol, dtt.timezone, s.exchange, s.longname 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 and brokerid = ? where dss.classname in (...) and (dss.downloadersymbol in (...) or s.symbol in (...)) and dss.enabled = ? and s.nonliquid = ? and s.deleted = ? ), report_symbols as ( select ps1.*, ps2.symbolid as price_symbol_id from pre_symbols ps1 inner join pre_symbols ps2 on ps1.symbol = ps2.symbol and ps1.downloadersymbol = ps2.downloadersymbol and ps2.timegranularity = ? ), rbr_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ) select bmr.resultuid as ruid, ? as direction, rs.symbol as sym, rs.downloadersymbol, rs.symbolid as sid, rs.timegranularity as tg, rs.timezone, rs.exchange as e, rs.longname, bmr.patternendtime as pet, lpi.latestpricedatetime as lpdt, bmr.patternlengthbars as l, bmr.breakout >= ? as complete, rbr.age as age from bigmovement_results bmr inner join report_symbols rs on rs.symbolid = bmr.symbolid inner join autochartist_symbolupdates lpi on lpi.symbolid = rs.price_symbol_id inner join rbr_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid where patternendtime >= (now() - ? * interval ?) -- results can't be more than ? days old and (bmr.resultuid > rm.resultuid or rbr.relevant = ?) ;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Mar 09	04	2	0ms	0ms

19

0ms

2

Details

0ms

update correlating_signals set sent = true where id = ?;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Mar 09	04	2	0ms	0ms

20

0ms

340

Details

0ms

commit;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Mar 09	04	340	0ms	0ms

Time consuming prepare


Date: 2026-03-09 04:30:03
Duration: 19ms
Database: postgres
Date: 2026-03-09 04:32:24
Duration: 2ms
Database: postgres
Date: 2026-03-09 04:36:21
Duration: 19ms
Database: postgres
Date: 2026-03-09 04:15:24
Duration: 2ms
Database: postgres
Date: 2026-03-09 04:45:38
Duration: 10ms
Database: postgres
Date: 2026-03-09 04:02:08
Duration: 2ms
Database: postgres
Date: 2026-03-09 04:10:35
Duration: 0ms
Database: postgres
Date: 2026-03-09 04:40:35
Duration: 0ms
Database: postgres
Date: 2026-03-09 04:37:39
Duration: 2ms
Database: postgres
Date: 2026-03-09 04:51:50
Duration: 7ms
Database: postgres
Date: 2026-03-09 04:40:02
Duration: 3ms
Database: postgres
Date: 2026-03-09 04:00:41
Duration: 6ms
Database: postgres
Date: 2026-03-09 04:11:50
Duration: 0ms
Database: postgres
Date: 2026-03-09 04:15:04
Duration: 3ms
Database: postgres
Date: 2026-03-09 04:50:48
Duration: 3ms
Database: postgres
Date: 2026-03-09 04:30:32
Duration: 0ms
Database: postgres
Date: 2026-03-09 04:00:05
Duration: 3ms
Database: postgres
Date: 2026-03-09 04:00:02
Duration: 3ms
Database: postgres
Date: 2026-03-09 04:20:05
Duration: 0ms
Database: postgres
Date: 2026-03-09 04:22:05
Duration: 1ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

26s549ms

2,681

Details

0ms

61ms

9ms

WITH rar_max as ( ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Mar 09	04	2,681	26s549ms	9ms

WITH rar_max as ( ;

Date: 2026-03-09 04:24:20 Duration: 61ms Database: postgres parameters: $1 = '607805475060173301', $2 = '607805475060173301', $3 = '607805475060173301'
WITH rar_max as ( ;

Date: 2026-03-09 04:59:16 Duration: 54ms Database: postgres parameters: $1 = '607805594979515301', $2 = '607805594979515301', $3 = '607805594979515301'
WITH rar_max as ( ;

Date: 2026-03-09 04:00:41 Duration: 50ms Database: postgres parameters: $1 = '607804827800283301', $2 = '607804827800283301', $3 = '607804827800283301'

2

6s553ms

16,829

Details

0ms

11ms

0ms

SELECT ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	04	16,829	6s553ms	0ms

SELECT ;

Date: 2026-03-09 04:37:23 Duration: 11ms Database: postgres parameters: $1 = '689', $2 = '689', $3 = '515840245886551300'
SELECT ;

Date: 2026-03-09 04:15:00 Duration: 9ms Database: postgres parameters: $1 = '515840233926223300'
SELECT ;

Date: 2026-03-09 04:00:03 Duration: 8ms Database: postgres parameters: $1 = '558', $2 = '0', $3 = '0', $4 = 'ES35', $5 = 'ES35'

3

2s154ms

893

Details

0ms

4ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	04	893	2s154ms	2ms

SELECT symbolid, ;

Date: 2026-03-09 04:02:07 Duration: 4ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'DOTBTC', $4 = 'EURGBP', $5 = 'EURJPY', $6 = 'BTCXAU', $7 = 'BTCZAR', $8 = 'ETHJPY', $9 = 'EURHUF', $10 = 'BTCUSD', $11 = 'BCHUSD', $12 = 'ETHUSD', $13 = 'DOGUSD', $14 = 'AUDUSD', $15 = 'GBPJPY', $16 = 'BTCAPL', $17 = 'EURUSD', $18 = 'AUDJPY', $19 = 'EURAUD', $20 = 'BCHJPY', $21 = 'BTCJPY', $22 = 'GBPUSD', $23 = 'BTCUSO'
SELECT symbolid, ;

Date: 2026-03-09 04:17:42 Duration: 3ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'CADJPY.FX', $4 = 'CHFJPY.FX', $5 = 'DOW30', $6 = 'CHFJPY'
SELECT symbolid, ;

Date: 2026-03-09 04:01:29 Duration: 3ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '60', $3 = '#GE', $4 = '#FDX', $5 = '#GM', $6 = '#EA', $7 = '#FB'

4

576ms

331

Details

1ms

2ms

1ms

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

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	04	331	576ms	1ms

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

Date: 2026-03-09 04:45:22 Duration: 2ms Database: postgres parameters: $1 = 'Alpari'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-03-09 04:31:52 Duration: 2ms Database: postgres parameters: $1 = 'PEPPERSTONEMT5'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-03-09 04:47:06 Duration: 2ms Database: postgres parameters: $1 = 'GLOBALGTMT5'

5

564ms

19

Details

0ms

47ms

29ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	04	19	564ms	29ms

with wh_patitioned as ( ;

Date: 2026-03-09 04:07:16 Duration: 47ms Database: postgres parameters: $1 = '621', $2 = '621', $3 = '621', $4 = '621', $5 = '621', $6 = '621', $7 = '621', $8 = '621', $9 = '621'
with wh_patitioned as ( ;

Date: 2026-03-09 04:45:03 Duration: 43ms 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 04:07:23 Duration: 43ms Database: postgres parameters: $1 = '621', $2 = '621', $3 = '621', $4 = '621', $5 = '621', $6 = '621', $7 = '621', $8 = '621', $9 = '621'

6

416ms

67

Details

4ms

13ms

6ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	04	67	416ms	6ms

WITH last_candle AS ( ;

Date: 2026-03-09 04:52:00 Duration: 13ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-03-09 04:52:00 Duration: 12ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-03-09 04:04:00 Duration: 11ms Database: postgres parameters: $1 = '558', $2 = '558'

7

375ms

12

Details

28ms

49ms

31ms

with sym_info as ( ;

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	04	12	375ms	31ms

with sym_info as ( ;

Date: 2026-03-09 04:51:50 Duration: 49ms 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 04:06:55 Duration: 36ms 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 04:51:44 Duration: 29ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'

8

373ms

15,277

Details

0ms

12ms

0ms

select 1;

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	04	15,277	373ms	0ms

select 1;

Date: 2026-03-09 04:03:18 Duration: 12ms Database: postgres
select 1;

Date: 2026-03-09 04:07:17 Duration: 6ms Database: postgres
select 1;

Date: 2026-03-09 04:50:51 Duration: 5ms Database: postgres

9

266ms

27

Details

0ms

19ms

9ms

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

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	04	27	266ms	9ms

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

Date: 2026-03-09 04:40:45 Duration: 19ms Database: postgres parameters: $1 = '689', $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 04:24:06 Duration: 17ms Database: postgres parameters: $1 = '689', $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 04:19:12 Duration: 12ms Database: postgres parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

10

201ms

2,908

Details

0ms

2ms

0ms

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

Times Reported Time consuming bind #10

Day	Hour	Count	Duration	Avg duration
	04	2,908	201ms	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 04:02:08 Duration: 2ms Database: postgres parameters: $1 = '2026-03-07 00:30:00', $2 = '13.154', $3 = '13.2135', $4 = '13.1495', $5 = '13.2015', $6 = '2131', $7 = '515840249402508300', $8 = '0', $9 = '2026-03-09 04:02:08.866', $10 = '2026-03-09 04:02:08.763', $11 = '13.154', $12 = '13.2135', $13 = '13.1495', $14 = '13.2015', $15 = '2131', $16 = '0', $17 = '2026-03-09 04:02:08.866', $18 = '2026-03-09 04:02:08.763'
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 04:41:35 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 03:30:00', $2 = '8463.9', $3 = '8499.75', $4 = '8454.3', $5 = '8478.4', $6 = '9724', $7 = '515840248015340300', $8 = '0', $9 = '2026-03-09 04:41:35.767', $10 = '2026-03-09 04:41:35.676', $11 = '8463.9', $12 = '8499.75', $13 = '8454.3', $14 = '8478.4', $15 = '9724', $16 = '0', $17 = '2026-03-09 04:41:35.767', $18 = '2026-03-09 04:41:35.676'
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 04:02:50 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 03:00:00', $2 = '46569.35', $3 = '46586.85', $4 = '46484.85', $5 = '46534.85', $6 = '4830', $7 = '515840248000726300', $8 = '0', $9 = '2026-03-09 04:02:50.862', $10 = '2026-03-09 04:02:50.783', $11 = '46569.35', $12 = '46586.85', $13 = '46484.85', $14 = '46534.85', $15 = '4830', $16 = '0', $17 = '2026-03-09 04:02:50.862', $18 = '2026-03-09 04:02:50.783'

11

192ms

30

Details

0ms

27ms

6ms

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

Times Reported Time consuming bind #11

Day	Hour	Count	Duration	Avg duration
	04	30	192ms	6ms

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

Date: 2026-03-09 04:17:09 Duration: 27ms Database: postgres parameters: $1 = '1436', $2 = '1436'
select distinct s.statsid as statsid, sy.exchange as name;

Date: 2026-03-09 04:17:10 Duration: 18ms Database: postgres parameters: $1 = '1504', $2 = '1504'
select distinct s.statsid as statsid, sy.exchange as name;

Date: 2026-03-09 04:17:10 Duration: 18ms Database: postgres parameters: $1 = '1471', $2 = '1471'

12

182ms

4,667

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 #12

Day	Hour	Count	Duration	Avg duration
	04	4,667	182ms	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 04:00:09 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 04:45:00', $2 = '92.986', $3 = '93.012', $4 = '92.922', $5 = '92.957', $6 = '2311', $7 = '500991628234818200', $8 = '0', $9 = '2026-03-09 04:00:09.606', $10 = '2026-03-09 04:00:09.271', $11 = '92.986', $12 = '93.012', $13 = '92.922', $14 = '92.957', $15 = '2311', $16 = '0', $17 = '2026-03-09 04:00:09.606', $18 = '2026-03-09 04:00:09.271'
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 04:40:35 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 04:00:00', $2 = '8472.75', $3 = '8499.75', $4 = '8467.4', $5 = '8478.4', $6 = '5219', $7 = '515840248015086300', $8 = '0', $9 = '2026-03-09 04:40:35.342', $10 = '2026-03-09 04:40:35.257', $11 = '8472.75', $12 = '8499.75', $13 = '8467.4', $14 = '8478.4', $15 = '5219', $16 = '0', $17 = '2026-03-09 04:40:35.342', $18 = '2026-03-09 04:40:35.257'
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 04:41:35 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 04:15:00', $2 = '8478.3', $3 = '8488.4', $4 = '8470.4', $5 = '8486.1', $6 = '4699', $7 = '515840248015086300', $8 = '0', $9 = '2026-03-09 04:41:35.748', $10 = '2026-03-09 04:41:35.666', $11 = '8478.3', $12 = '8488.4', $13 = '8470.4', $14 = '8486.1', $15 = '4699', $16 = '0', $17 = '2026-03-09 04:41:35.748', $18 = '2026-03-09 04:41:35.666'

13

171ms

2,173

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 #13

Day	Hour	Count	Duration	Avg duration
	04	2,173	171ms	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 04:10:35 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 02:00:00', $2 = '8497.55', $3 = '8503.4', $4 = '8461.1', $5 = '8463.4', $6 = '19143', $7 = '515840248015562300', $8 = '0', $9 = '2026-03-09 04:10:35.746', $10 = '2026-03-09 04:10:35.576', $11 = '8497.55', $12 = '8503.4', $13 = '8461.1', $14 = '8463.4', $15 = '19143', $16 = '0', $17 = '2026-03-09 04:10:35.746', $18 = '2026-03-09 04:10:35.576'
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 04:17:28 Duration: 0ms Database: postgres parameters: $1 = '2026-03-09 04:00:00', $2 = '6610.4', $3 = '6613.1', $4 = '6584.2', $5 = '6586.7', $6 = '19736', $7 = '515840245924571300', $8 = '0', $9 = '2026-03-09 04:17:28.068', $10 = '2026-03-09 04:17:28.068', $11 = '6610.4', $12 = '6613.1', $13 = '6584.2', $14 = '6586.7', $15 = '19736', $16 = '0', $17 = '2026-03-09 04:17:28.069', $18 = '2026-03-09 04:17:28.068'
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 04:11:28 Duration: 0ms Database: postgres parameters: $1 = '2026-03-06 21:00:00', $2 = '692.25', $3 = '692.85', $4 = '679.55', $5 = '680.02', $6 = '2429', $7 = '515840247889020300', $8 = '0', $9 = '2026-03-09 04:11:28.116', $10 = '2026-03-09 04:11:28.077', $11 = '692.25', $12 = '692.85', $13 = '679.55', $14 = '680.02', $15 = '2429', $16 = '0', $17 = '2026-03-09 04:11:28.116', $18 = '2026-03-09 04:11:28.077'

14

107ms

16

Details

1ms

24ms

6ms

WITH rcr_max as ( ;

Times Reported Time consuming bind #14

Day	Hour	Count	Duration	Avg duration
	04	16	107ms	6ms

WITH rcr_max as ( ;

Date: 2026-03-09 04:24:20 Duration: 24ms Database: postgres parameters: $1 = '607805537880976305', $2 = '607805537880976305', $3 = '607805537880976305'
WITH rcr_max as ( ;

Date: 2026-03-09 04:45:40 Duration: 16ms Database: postgres parameters: $1 = '607805304458173305', $2 = '607805304458173305', $3 = '607805304458173305'
WITH rcr_max as ( ;

Date: 2026-03-09 04:37:03 Duration: 7ms Database: postgres parameters: $1 = '607805536688051305', $2 = '607805536688051305', $3 = '607805536688051305'

15

85ms

1,064

Details

0ms

1ms

0ms

select category, ;

Times Reported Time consuming bind #15

Day	Hour	Count	Duration	Avg duration
	04	1,064	85ms	0ms

select category, ;

Date: 2026-03-09 04:17:15 Duration: 1ms Database: postgres parameters: $1 = '515852059324736307', $2 = 'symbol', $3 = 'USDMXN', $4 = 'CHFZAR', $5 = 'AUDJPY', $6 = 'USDZAR', $7 = 'USDJPY', $8 = 'ZARJPY', $9 = 'CADJPY', $10 = 'CHFJPY', $11 = 'GBPZAR', $12 = 'EURCNH', $13 = 'EURMXN', $14 = 'NZDJPY', $15 = 'TRYJPY', $16 = 'GBPJPY', $17 = 'AUDZAR', $18 = 'USDHUF', $19 = 'USDNOK', $20 = 'EURNOK', $21 = 'EURZAR', $22 = 'USDCZK', $23 = 'USDSEK', $24 = 'EURHKD', $25 = 'EURTRY', $26 = 'EURSEK', $27 = 'SGDJPY', $28 = 'USDDKK', $29 = 'NZDSEK', $30 = 'EURJPY', $31 = 'CHFHUF', $32 = 'EURHUF', $33 = 'USDPLN', $34 = 'GBPNZD', $35 = 'USDCNH', $36 = 'EURCZK', $37 = 'USDILS', $38 = 'EURNZD', $39 = 'EURGBP', $40 = 'EURPLN', $41 = 'GBPAUD', $42 = 'EURCZK', $43 = 'TRYJPY', $44 = 'EURAUD', $45 = 'CHFHUF', $46 = 'GBPCAD', $47 = 'EURHUF', $48 = 'ZARJPY', $49 = 'USDCAD', $50 = 'EURDKK', $51 = 'AUDZAR', $52 = 'USDZAR', $53 = '515852059324736307', $54 = 'symbol', $55 = 'USDMXN', $56 = 'CHFZAR', $57 = 'AUDJPY', $58 = 'USDZAR', $59 = 'USDJPY', $60 = 'ZARJPY', $61 = 'CADJPY', $62 = 'CHFJPY', $63 = 'GBPZAR', $64 = 'EURCNH', $65 = 'EURMXN', $66 = 'NZDJPY', $67 = 'TRYJPY', $68 = 'GBPJPY', $69 = 'AUDZAR', $70 = 'USDHUF', $71 = 'USDNOK', $72 = 'EURNOK', $73 = 'EURZAR', $74 = 'USDCZK', $75 = 'USDSEK', $76 = 'EURHKD', $77 = 'EURTRY', $78 = 'EURSEK', $79 = 'SGDJPY', $80 = 'USDDKK', $81 = 'NZDSEK', $82 = 'EURJPY', $83 = 'CHFHUF', $84 = 'EURHUF', $85 = 'USDPLN', $86 = 'GBPNZD', $87 = 'USDCNH', $88 = 'EURCZK', $89 = 'USDILS', $90 = 'EURNZD', $91 = 'EURGBP', $92 = 'EURPLN', $93 = 'GBPAUD', $94 = 'EURCZK', $95 = 'TRYJPY', $96 = 'EURAUD', $97 = 'CHFHUF', $98 = 'GBPCAD', $99 = 'EURHUF', $100 = 'ZARJPY', $101 = 'USDCAD', $102 = 'EURDKK', $103 = 'AUDZAR', $104 = 'USDZAR'
select category, ;

Date: 2026-03-09 04:17:16 Duration: 1ms Database: postgres parameters: $1 = '515852059312800307', $2 = 'symbol', $3 = 'XMRUSD', $4 = 'BTCGBP', $5 = 'LTCUSD', $6 = 'BTCEUR', $7 = 'ETHGBP', $8 = 'LTCEUR', $9 = 'NEOUSD', $10 = 'BTCUSD', $11 = 'ETHEUR', $12 = 'DASHUSD', $13 = 'XRPUSD', $14 = 'ETHUSD', $15 = 'ZECUSD', $16 = 'EOSUSD', $17 = 'USOIL', $18 = 'XAGUSD', $19 = 'XAUUSD', $20 = 'NEOUSD', $21 = 'US30', $22 = 'SPX500', $23 = 'NAS100', $24 = 'XAUEUR', $25 = 'LTCUSD', $26 = 'LTCEUR', $27 = 'DASHUSD', $28 = 'IOTAUSD', $29 = 'EOSUSD', $30 = 'XPTUSD', $31 = 'IOTAUSD', $32 = 'CL_BRENT', $33 = 'ETHEUR', $34 = 'AUS_200', $35 = 'XRPUSD', $36 = 'ETHGBP', $37 = 'XMRUSD', $38 = 'BTCUSD', $39 = 'ETHUSD', $40 = 'ZECUSD', $41 = 'BTCEUR', $42 = 'TRXUSD', $43 = 'TRXUSD', $44 = 'BTCGBP', $45 = 'EUR_50', $46 = 'FRA_40', $47 = 'GBR_100', $48 = 'US30', $49 = 'NAS100', $50 = 'XAUUSD', $51 = 'XPTUSD', $52 = 'XAGUSD', $53 = '515852059312800307', $54 = 'symbol', $55 = 'XMRUSD', $56 = 'BTCGBP', $57 = 'LTCUSD', $58 = 'BTCEUR', $59 = 'ETHGBP', $60 = 'LTCEUR', $61 = 'NEOUSD', $62 = 'BTCUSD', $63 = 'ETHEUR', $64 = 'DASHUSD', $65 = 'XRPUSD', $66 = 'ETHUSD', $67 = 'ZECUSD', $68 = 'EOSUSD', $69 = 'USOIL', $70 = 'XAGUSD', $71 = 'XAUUSD', $72 = 'NEOUSD', $73 = 'US30', $74 = 'SPX500', $75 = 'NAS100', $76 = 'XAUEUR', $77 = 'LTCUSD', $78 = 'LTCEUR', $79 = 'DASHUSD', $80 = 'IOTAUSD', $81 = 'EOSUSD', $82 = 'XPTUSD', $83 = 'IOTAUSD', $84 = 'CL_BRENT', $85 = 'ETHEUR', $86 = 'AUS_200', $87 = 'XRPUSD', $88 = 'ETHGBP', $89 = 'XMRUSD', $90 = 'BTCUSD', $91 = 'ETHUSD', $92 = 'ZECUSD', $93 = 'BTCEUR', $94 = 'TRXUSD', $95 = 'TRXUSD', $96 = 'BTCGBP', $97 = 'EUR_50', $98 = 'FRA_40', $99 = 'GBR_100', $100 = 'US30', $101 = 'NAS100', $102 = 'XAUUSD', $103 = 'XPTUSD', $104 = 'XAGUSD'
select category, ;

Date: 2026-03-09 04:17:10 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307', $2 = 'symbol', $3 = 'XAUUSD', $4 = 'DOW30', $5 = 'XAGUSD', $6 = 'USDJPY', $7 = 'AUDJPY', $8 = 'GBPJPY', $9 = 'NZDJPY', $10 = 'SP500', $11 = 'NASDAQ100', $12 = 'OIL', $13 = 'CHFJPY', $14 = 'EURJPY', $15 = 'GBPAUD', $16 = 'EURAUD', $17 = 'GBPCHF', $18 = 'USDCAD', $19 = 'EURCHF', $20 = 'EURGBP', $21 = 'OIL', $22 = 'EURCAD', $23 = 'EURCAD', $24 = 'DOW30', $25 = 'GBPUSD', $26 = 'EURJPY', $27 = 'NZDUSD', $28 = 'EURUSD', $29 = 'XAGUSD', $30 = 'CHFJPY', $31 = 'GBPUSD', $32 = 'GBPAUD', $33 = 'EURAUD', $34 = 'AUDJPY', $35 = 'EURUSD', $36 = 'USDCHF', $37 = 'SP500', $38 = 'NZDJPY', $39 = 'RK_SSI', $40 = 'R_SSI', $41 = 'GBPJPY', $42 = 'XAUUSD', $43 = 'AUDNZD', $44 = 'USDCAD', $45 = 'AUDUSD', $46 = 'NASDAQ100', $47 = 'USDJPY', $48 = 'NZDUSD', $49 = 'AUDUSD', $50 = 'GBPCHF', $51 = 'USDCHF', $52 = 'AUDNZD', $53 = '515852059317765307', $54 = 'symbol', $55 = 'XAUUSD', $56 = 'DOW30', $57 = 'XAGUSD', $58 = 'USDJPY', $59 = 'AUDJPY', $60 = 'GBPJPY', $61 = 'NZDJPY', $62 = 'SP500', $63 = 'NASDAQ100', $64 = 'OIL', $65 = 'CHFJPY', $66 = 'EURJPY', $67 = 'GBPAUD', $68 = 'EURAUD', $69 = 'GBPCHF', $70 = 'USDCAD', $71 = 'EURCHF', $72 = 'EURGBP', $73 = 'OIL', $74 = 'EURCAD', $75 = 'EURCAD', $76 = 'DOW30', $77 = 'GBPUSD', $78 = 'EURJPY', $79 = 'NZDUSD', $80 = 'EURUSD', $81 = 'XAGUSD', $82 = 'CHFJPY', $83 = 'GBPUSD', $84 = 'GBPAUD', $85 = 'EURAUD', $86 = 'AUDJPY', $87 = 'EURUSD', $88 = 'USDCHF', $89 = 'SP500', $90 = 'NZDJPY', $91 = 'RK_SSI', $92 = 'R_SSI', $93 = 'GBPJPY', $94 = 'XAUUSD', $95 = 'AUDNZD', $96 = 'USDCAD', $97 = 'AUDUSD', $98 = 'NASDAQ100', $99 = 'USDJPY', $100 = 'NZDUSD', $101 = 'AUDUSD', $102 = 'GBPCHF', $103 = 'USDCHF', $104 = 'AUDNZD'

16

52ms

59

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 #16

Day	Hour	Count	Duration	Avg duration
	04	59	52ms	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 04:32:10 Duration: 1ms Database: postgres parameters: $1 = '632', $2 = 'GBPUSD', $3 = '632'
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 04:05:19 Duration: 1ms Database: postgres parameters: $1 = '689', $2 = 'XAUUSD', $3 = '689'
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2026-03-09 04:25:01 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'GBPUSD', $3 = '558'

17

49ms

8

Details

3ms

10ms

6ms

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

Times Reported Time consuming bind #17

Day	Hour	Count	Duration	Avg duration
	04	8	49ms	6ms

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

Date: 2026-03-09 04:13:03 Duration: 10ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'
WITH pre_symbols AS ( /* find relevant symbols */ ;

Date: 2026-03-09 04:13:03 Duration: 9ms 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 04:13:03 Duration: 7ms 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'

18

41ms

56

Details

0ms

1ms

0ms

SELECT absolutetimezoneoffset;

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	04	56	41ms	0ms

SELECT absolutetimezoneoffset;

Date: 2026-03-09 04:17:13 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'BROKER'
SELECT absolutetimezoneoffset;

Date: 2026-03-09 04:17:10 Duration: 1ms Database: postgres parameters: $1 = '489', $2 = 'BROKER'
SELECT absolutetimezoneoffset;

Date: 2026-03-09 04:17:45 Duration: 0ms Database: postgres parameters: $1 = '932', $2 = 'Commodities'

19

39ms

10

Details

3ms

6ms

3ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #19

Day	Hour	Count	Duration	Avg duration
	04	10	39ms	3ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-03-09 04:46:00 Duration: 6ms Database: postgres parameters: $1 = '627', $2 = '627'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-03-09 04:00:02 Duration: 5ms Database: postgres parameters: $1 = '667', $2 = '667'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-03-09 04:05:27 Duration: 4ms Database: postgres parameters: $1 = '689', $2 = '689'

20

32ms

1

Details

32ms

with maxwhid as ( ;

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	04	1	32ms	32ms

with maxwhid as ( ;

Date: 2026-03-09 04:13:09 Duration: 32ms 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'

Log levels

Key values

314,578 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	424	0.13%
DETAIL	67,647	21.50%
ERROR	400	0.13%
LOG	244,800	77.82%
STATEMENT	1,307	0.42%

Events distribution

Key values

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

Most Frequent Errors/Events

Key values

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

Rank

Times reported

Error

1

357

Details

ERROR: pg_stat_statements must be loaded via shared_preload_libraries

Times Reported Most Frequent Error / Event #1

Day	Hour	Count
Mar 09	04	357

ERROR: pg_stat_statements must be loaded via shared_preload_libraries

2

43

Details

ERROR: schema "..." does not exist

Times Reported Most Frequent Error / Event #2

Day	Hour	Count
Mar 09	04	43

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

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Vacuums per table

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Tuples removed per table

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Pages removed per table

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Pages removed per tables

Autovacuum Activity

Locks

Locks by types

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Type of locks

Most frequent waiting queries (N)

Queries that waited the most

Queries

Queries by type

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Queries by database

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Queries by user

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