pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Sun Feb 22 04:59:21 2026
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-02-22_060000.log
Parsed 530,247 log entries in 19s
Log start from 2026-02-22 06:00:00 to 2026-02-22 06:59:18

Global Stats

978 Number of unique normalized queries
106,930 Number of queries
3h17m42s Total query duration
2026-02-22 06:00:00 First query
2026-02-22 06:59:18 Last query
6,426 queries/s at 2026-02-22 06:05:02 Query peak

3h17m42s Total query duration
2s185ms Prepare/parse total duration
21s451ms Bind total duration
3h17m19s Execute total duration

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

26 Total number of automatic vacuums
39 Total number of automatic analyzes

492 Number temporary file
137.42 MiB Max size of temporary file
6.26 MiB Average size of temporary file

1,658 Total number of sessions
13 sessions at 2026-02-22 06:53:48 Session peak
11h21m55s Total duration of sessions
24s677ms Average duration of sessions
64 Average queries per session
7s154ms Average queries duration per session
17s522ms Average idle time per session

1,658 Total number of connections
27 connections/s at 2026-02-22 06:03:48 Connection peak
6 Total number of databases

SQL Traffic

Key values

6,426 queries/s Query Peak
2026-02-22 06:05:02 Date

SELECT Traffic

Key values

3,210 queries/s Query Peak
2026-02-22 06:05:02 Date

INSERT/UPDATE/DELETE Traffic

Key values

114 queries/s Query Peak
2026-02-22 06:38:49 Date

Queries duration

Key values

3h17m42s Total query duration

Prepared queries ratio

Key values

0.00 Ratio of bind vs prepare
0.00 % Ratio between prepared and "usual" statements

General Activity

Day	Hour	Count	Min duration	Max duration	Avg duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Feb 22	06	106,930	0ms	14m14s	110ms	5m18s	7m10s	36m44s

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Feb 22	06	33,958	601	0ms	0ms	0ms	0ms

Day	Hour	INSERT	UPDATE	DELETE	COPY FROM	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Feb 22	06	12,702	542	13	78	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Feb 22	06	7,942	19,768	2.49	15.58%

Day	Hour	Count	Average / Second
Feb 22	06	1,658	0.46/s

Day	Hour	Count	Average Duration	Average idle time
Feb 22	06	1,658	24s677ms	17s537ms

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Established Connections

Key values

27 connections Connection Peak
2026-02-22 06:03:48 Date

Connections per database

Key values

acaweb_fx Main Database
1,658 connections Total

Chart
Table

Database	User	Count
acaweb_fx		1,580
	pg_dump	1
	postgres	1,275
	psql	304
acaweb_fx_integer		1
	pg_dump	1
postgres		3
	pg_dump	1
	psql	2
socialmedia		73
	pg_dump	1
	postgres	72
translations		1
	pg_dump	1

Connections per user

Key values

postgres Main User
1,658 connections Total

Chart
Table

User	Count
pg_dump	5
postgres	1,347
psql	306

Connections per host

Key values

192.168.4.142 Main host with 688 connections
1,658 Total connections

Chart
Table

Host	Count
127.0.0.1	111
192.168.0.114	3
192.168.0.216	116
192.168.1.20	20
192.168.1.239	56
192.168.1.90	6
192.168.2.126	18
192.168.3.199	39
192.168.4.142	688
192.168.4.33	71
192.168.4.98	330
[local]	200

Simultaneous sessions

Key values

13 sessions Session Peak
2026-02-22 06:53:48 Date

Histogram of session times

Key values

1,284 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	1,284	77.44%
500ms-1s	111	6.69%
1s-30s	226	13.63%
30s-1m	9	0.54%
1m-10m	5	0.30%
10m-30m	23	1.39%
30m-1h	0	0.00%
1h-8h	0	0.00%
> 8h	0	0.00%

Sessions per database

Key values

acaweb_fx Main Database
1,658 sessions Total

Chart
Table

Database	User	Count	Total Duration
acaweb_fx	1,580	10h53m59s	24s835ms
acaweb_fx_integer	1	19m39s	19m39s
postgres	3	224ms	74ms
socialmedia	73	8m16s	6s799ms
translations	1	188ms	188ms

Sessions per user

Key values

postgres Main User
1,658 sessions Total

Chart
Table

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

Sessions per host

Key values

192.168.4.142 Main Host
1,658 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
127.0.0.1	111	36m12s	19s572ms
192.168.0.114	3	15m	5m
192.168.0.216	116	7m26s	3s845ms
192.168.1.20	20	9h52m11s	29m36s
192.168.1.239	56	280ms	5ms
192.168.1.90	6	56ms	9ms
192.168.2.126	18	5s318ms	295ms
192.168.3.199	39	31s766ms	814ms
192.168.4.142	688	7m33s	658ms
192.168.4.33	71	1m11s	1s10ms
192.168.4.98	330	21s342ms	64ms
[local]	200	21m21s	6s405ms

Sessions per application

Key values

unknown Main Host
1,658 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	1,658	11h21m55s	24s677ms

Checkpoints Buffers

Key values

21,643 buffers Checkpoint Peak
2026-02-22 06:47:57 Date
209.827 seconds Highest write time
0.014 seconds Sync time

Checkpoints Wal files

Key values

12 files Wal files usage Peak
2026-02-22 06:47:57 Date

Checkpoints distance

Key values

399.76 Mo Distance Peak
2026-02-22 06:47:57 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Feb 22	06	33,950	1,631.343s	0.063s	1,631.722s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Feb 22	06	0	0	22	1,351	0.005s	0s

Day	Hour	Count	Avg time (sec)
Feb 22	06	0	0s

Day	Hour	Mean distance	Mean estimate
Feb 22	06	30,331.75 kB	63,387.67 kB

↑ Back to the top of the Checkpoint Activity table

Checkpoint causes

Key values

time (11) Main checkpoint cause
11 checkpoints Total

Chart
Table

Cause	Number of checkpoints
time	11
Total	11

Size of temporary files

Key values

103.19 MiB Temp Files size Peak
2026-02-22 06:47:41 Date

Number of temporary files

Key values

30 per second Temp Files Peak
2026-02-22 06:17:26 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Feb 22	06	492	3.01 GiB	6.26 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	71	288.58 MiB	3.94 MiB	4.33 MiB	4.06 MiB	select resultuid from relevance_fibonacci_results order by resultuid desc limit ?), fr as ( select a., rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp)))), results as ( select distinct on (symbolid) from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc; SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1), fr AS ( SELECT a., rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4)) AND ($5 = 0 OR s.exchange in ($6)) AND ($7 = 0 OR coalesce(bim.code, s.symbol) in ($8)) AND ($9 = 0 OR fr.pattern in ($10)) AND ($11 = 0 OR fr.patternlengthbars <= $12) AND ($13 = 0 OR ($14 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($15 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) FROM all_results WHERE (FALSE = $16 OR relevant = 1) AND ($17 = 0 OR age <= $18) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-02-22 06:00:44 Duration: 0ms
2	48	177.03 MiB	3.48 MiB	3.89 MiB	3.69 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)) AND ($226 = 0 OR ccr.patternlengthbars <= $227)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $228 OR relevant = 1) AND ($229 = 0 OR age <= $230) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-02-22 06:01:36 Duration: 0ms
3	44	292.15 MiB	3.52 MiB	9.76 MiB	6.64 MiB	jr.resultuid as resultuid, jr.direction as direction, jr.patternendtime as identified, jr.patternlengthbars as length, jr.patternstarttime as patternstarttime, case when jr.trendchangeid = ? then ? else ? end as trendchange, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, jp.patternname as pattern_name, dtt.timezone as timezone, ? as age, cps.pip, g.basegroupname from japsticks_results jr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = jr.symbolid inner join relevance_japsticks_results rar on rar.resultuid = jr.resultuid inner join symbols s on jr.symbolid = s.symbolid and s.nonliquid = ? inner join japsticks_patterns jp on jr.patternid = jp.id inner join downloadersymbolsettings dss on jr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where jr.gmttimefound > now() - interval ? and s.deleted = ? and (jr.simulation = ? or jr.simulation is null) and (rar.relevant = ?) --and (semicolon_age = ? or rar.age <= semicolon_age) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or jp.patternname in (...)) and (? = ? or jr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results order by symbolid, resultuid ) select * from results order by identified desc, length desc ; jr.resultuid AS resultuid, jr.direction AS direction, jr.patternendtime AS identified, jr.patternlengthbars AS length, jr.patternstarttime AS patternstarttime, case when jr.trendchangeid = 1 then 'Continuation' else 'Reversal' end AS trendchange, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, jp.patternname AS pattern_name, dtt.timezone AS timezone, 0 AS age, cps.pip, g.basegroupname FROM japsticks_results jr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = jr.symbolid INNER JOIN relevance_japsticks_results rar ON rar.resultuid = jr.resultuid INNER JOIN symbols s ON jr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN japsticks_patterns jp ON jr.patternid = jp.id INNER JOIN downloadersymbolsettings dss ON jr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE jr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (jr.simulation = 0 OR jr.simulation IS NULL) AND (rar.relevant = 1) --AND (semicolon_age = 0 OR rar.age <= semicolon_age) AND ($2 = 0 OR s.timegranularity in ($3)) AND ($4 = 0 OR s.exchange in ($5)) AND ($6 = 0 OR coalesce(bim.code, s.symbol) in ($7)) AND ($8 = 0 OR jp.patternname in ($9)) AND ($10 = 0 OR jr.patternlengthbars <= $11)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-02-22 06:01:39 Duration: 0ms
4	13	504.66 MiB	38.82 MiB	38.82 MiB	38.82 MiB	update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid; UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid; Date: 2026-02-22 06:01:13 Duration: 0ms
5	13	931.12 MiB	71.62 MiB	71.62 MiB	71.62 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid; with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; Date: 2026-02-22 06:01:18 Duration: 0ms
6	4	549.68 MiB	137.42 MiB	137.42 MiB	137.42 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2026-02-22 06:02:15 Duration: 0ms
7	4	339.00 MiB	84.75 MiB	84.75 MiB	84.75 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2026-02-22 06:02:04 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	137.42 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-22 06:02:15 ]
2	137.42 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-22 06:17:34 ]
3	137.42 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-22 06:32:37 ]
4	137.42 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-22 06:47:34 ]
5	84.75 MiB	select updateageforrelevantresults (); [ Date: 2026-02-22 06:32:21 ]
6	84.75 MiB	select updateageforrelevantresults (); [ Date: 2026-02-22 06:02:04 ]
7	84.75 MiB	select updateageforrelevantresults (); [ Date: 2026-02-22 06:17:19 ]
8	84.75 MiB	select updateageforrelevantresults (); [ Date: 2026-02-22 06:47:19 ]
9	71.62 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-02-22 06:01:18 ]
10	71.62 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-02-22 06:03:15 ]
11	71.62 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-02-22 06:19:32 ]
12	71.62 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-02-22 06:20:15 ]
13	71.62 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-02-22 06:26:19 ]
14	71.62 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-02-22 06:31:21 ]
15	71.62 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-02-22 06:33:18 ]
16	71.62 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-02-22 06:35:16 ]
17	71.62 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-02-22 06:41:16 ]
18	71.62 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-02-22 06:46:18 ]
19	71.62 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-02-22 06:48:15 ]
20	71.62 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-02-22 06:50:15 ]

Vacuums / Analyzes Distribution

Key values

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

Analyzes per table

Key values

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

Chart
Table

Table	Number of analyzes
acaweb_fx.public.solr_relevance_old	13
acaweb_fx.pg_catalog.pg_attribute	6
acaweb_fx.pg_catalog.pg_type	4
acaweb_fx.pg_catalog.pg_class	4
acaweb_fx.public.datafeeds_latestrun	3
acaweb_fx.pg_catalog.pg_depend	2
acaweb_fx.pg_catalog.pg_index	1
acaweb_fx.public.t60	1
socialmedia.public.processes	1
acaweb_fx.public.symbollatestupdatetime	1
acaweb_fx.public.latest_t15_candle_view	1
acaweb_fx.public.relevance_autochartist_results	1
acaweb_fx.public.latest_candle_datetime_per_receng	1
Total	39

Vacuums per table

Key values

public.solr_relevance_old (13) Main table vacuumed on database acaweb_fx
26 vacuums Total

Chart
Table

		Index	Buffer usage			Skipped		WAL usage
Table	Vacuums	scans	hits	misses	dirtied	pins	frozen	records	full page	bytes
acaweb_fx.public.solr_relevance_old	13	13	9,796	0	47	0	0	7,502	99	1,410,370
acaweb_fx.pg_catalog.pg_attribute	4	3	2,819	0	374	0	268	1,014	316	1,833,146
acaweb_fx.public.datafeeds_latestrun	3	0	363	0	6	0	0	39	6	41,004
acaweb_fx.pg_catalog.pg_type	2	2	335	0	49	0	0	146	39	224,645
acaweb_fx.pg_catalog.pg_class	2	2	898	0	96	0	0	268	91	471,468
acaweb_fx.pg_toast.pg_toast_2619	1	1	134	0	23	0	0	107	24	90,272
acaweb_fx.pg_catalog.pg_depend	1	1	389	0	77	0	59	174	64	339,074
Total	26	22	14,734	2,299	672	0	327	9,250	639	4,409,979

Tuples removed per table

Key values

public.solr_relevance_old (68145) Main table with removed tuples on database acaweb_fx
75236 tuples Total removed

Chart
Table

		Index	Tuples			Pages
Table	Vacuums	scans	removed	remain	not yet removable	removed	remain
acaweb_fx.public.solr_relevance_old	13	13	68,145	74,326	0	0	2,387
acaweb_fx.pg_catalog.pg_attribute	4	3	5,259	45,738	4,209	0	1,130
acaweb_fx.pg_catalog.pg_depend	1	1	614	14,394	8	0	143
acaweb_fx.pg_catalog.pg_type	2	2	561	2,902	6	0	88
acaweb_fx.pg_catalog.pg_class	2	2	399	3,409	109	0	300
acaweb_fx.public.datafeeds_latestrun	3	0	178	42	0	0	48
acaweb_fx.pg_toast.pg_toast_2619	1	1	80	168	0	0	50
Total	26	22	75,236	140,979	4,332	0	4,146

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_toast.pg_toast_2619	1	1	80
acaweb_fx.pg_catalog.pg_depend	1	1	614
acaweb_fx.pg_catalog.pg_type	2	2	561
acaweb_fx.public.datafeeds_latestrun	3	0	178
acaweb_fx.pg_catalog.pg_attribute	4	3	5259
acaweb_fx.pg_catalog.pg_class	2	2	399
acaweb_fx.public.solr_relevance_old	13	13	68145
Total	26	22	75,236

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Feb 22	06	26	39

↑ Back to the top of the Autovacuum Activity table

Locks by types

Key values

AccessShareLock Main Lock Type
11 locks Total

Chart
Table

Type	Object	Count	Total Duration	Average Duration (s)
AccessExclusiveLock		2	16m37s	8m18s
	relation	2	16m37s	8m18s
AccessShareLock		9	18m2s	2m
	relation	9	18m2s	2m
	Total	11	34m39s	3m9s

Most frequent waiting queries (N)

Rank	Count	Total time	Min time	Max time	Avg duration	Query
1	8	17m57s	1m58s	2m24s	2m14s	select datetimeupdate from latest_candle_datetime_per_receng where recognitionengine ilike ?; SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'HOTFOREX - 1'; Date: 2026-02-22 06:19:27
2	1	14m14s	14m14s	14m14s	14m14s	truncate table solr_relevance_old; TRUNCATE TABLE solr_relevance_old; Date: 2026-02-22 06:19:25
3	1	2m23s	2m23s	2m23s	2m23s	refresh materialized view latest_candle_datetime_per_receng; refresh materialized view latest_candle_datetime_per_receng; Date: 2026-02-22 06:19:25
4	1	4s897ms	4s897ms	4s897ms	4s897ms	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; /* service='datadog-agent' / 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 0 END as index_size, CASE WHEN C.reltoastrelid > 0 THEN pg_relation_size(C.reltoastrelid) ELSE 0 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 = 'relation' WHERE NOT (nspname = ANY ('{pg_catalog,information_schema}')) AND (L.relation IS NULL OR L.mode <> 'AccessExclusiveLock' OR NOT L.granted) AND relkind = 'r' AND ((relname ~ '.')) LIMIT 300) as s; Date: 2026-02-22 06:19:25

Queries that waited the most

Rank	Wait time	Query
1	14m14s	TRUNCATE TABLE solr_relevance_old; [ Date: 2026-02-22 06:19:25 ]
2	2m24s	SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'MILLENNIUMPF - 1'; [ Date: 2026-02-22 06:19:27 ]
3	2m24s	SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'PEPPERSTONE - 1'; [ Date: 2026-02-22 06:19:27 ]
4	2m23s	refresh materialized view latest_candle_datetime_per_receng; [ Date: 2026-02-22 06:19:25 ]
5	2m23s	SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'Alpari - 1'; [ Date: 2026-02-22 06:19:27 ]
6	2m23s	SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'HOTFOREX - 1'; [ Date: 2026-02-22 06:19:27 ]
7	2m15s	SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'IQFEED_FX - 1'; [ Date: 2026-02-22 06:19:27 ]
8	2m7s	SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'FPMARKETS - 1'; [ Date: 2026-02-22 06:19:27 ]
9	1m59s	SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'ATFX - 1'; [ Date: 2026-02-22 06:19:27 ]
10	1m58s	SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'AXIORY - 1'; [ Date: 2026-02-22 06:19:27 ]
11	4s897ms	/* service='datadog-agent' / 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 0 END as index_size, CASE WHEN C.reltoastrelid > 0 THEN pg_relation_size(C.reltoastrelid) ELSE 0 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 = 'relation' WHERE NOT (nspname = ANY ('{pg_catalog,information_schema}')) AND (L.relation IS NULL OR L.mode <> 'AccessExclusiveLock' OR NOT L.granted) AND relkind = 'r' AND ((relname ~ '.')) LIMIT 300) as s; [ Date: 2026-02-22 06:19:25 ]

Queries by type

Key values

33,958 Total read queries
17,012 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	33,958	31.76%
INSERT	12,702	11.88%
UPDATE	542	0.51%
DELETE	13	0.01%
COPY FROM	78	0.07%
COPY TO	601	0.56%
CTE	2,382	2.23%
DDL	13	0.01%
TCL	681	0.64%
CURSOR	0	0.00%
OTHERS	55,960	52.33%

Queries by database

Key values

unknown Main database
106,004 Requests
3h17m19s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	848	0ms
	copy from	65	0ms
	copy to	26	0ms
	cte	82	0ms
	ddl	13	0ms
	delete	13	0ms
	others	215	0ms
	select	65	0ms
	tcl	332	0ms
	update	37	0ms
acaweb_fx_integer	Total	1	0ms
	select	1	0ms
postgres	Total	3	0ms
	select	3	0ms
socialmedia	Total	73	0ms
	select	72	0ms
	tcl	1	0ms
translations	Total	1	0ms
	select	1	0ms
unknown	Total	106,004	3h17m19s
	copy from	13	0ms
	copy to	575	0ms
	cte	2,300	0ms
	insert	12,702	0ms
	others	2,510	0ms
	select	33,816	0ms
	tcl	348	0ms
	update	505	0ms

Queries by user

Key values

unknown Main user
106,004 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	926	0ms
	copy from	65	0ms
	copy to	26	0ms
	cte	82	0ms
	ddl	13	0ms
	delete	13	0ms
	others	215	0ms
	select	142	0ms
	tcl	333	0ms
	update	37	0ms
unknown	Total	106,004	3h17m19s
	copy from	13	0ms
	copy to	575	0ms
	cte	2,300	0ms
	insert	12,702	0ms
	others	2,510	0ms
	select	33,816	0ms
	tcl	348	0ms
	update	505	0ms

Duration by user

Key values

3h17m19s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	926	0ms
	copy from	65	0ms
	copy to	26	0ms
	cte	82	0ms
	ddl	13	0ms
	delete	13	0ms
	others	215	0ms
	select	142	0ms
	tcl	333	0ms
	update	37	0ms
unknown	Total	106,004	3h17m19s
	copy from	13	0ms
	copy to	575	0ms
	cte	2,300	0ms
	insert	12,702	0ms
	others	2,510	0ms
	select	33,816	0ms
	tcl	348	0ms
	update	505	0ms

Queries by host

Key values

unknown Main host
106,930 Requests
3h17m19s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	106,930	3h17m19s
	copy from	78	0ms
	copy to	601	0ms
	cte	2,382	0ms
	ddl	13	0ms
	delete	13	0ms
	insert	12,702	0ms
	others	2,725	0ms
	select	33,958	0ms
	tcl	681	0ms
	update	542	0ms

Queries by application

Key values

unknown Main application
106,619 Requests
3h17m19s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
pg_dump	Total	5	0ms
	select	5	0ms
psql	Total	306	0ms
	copy from	65	0ms
	copy to	26	0ms
	cte	82	0ms
	ddl	13	0ms
	delete	13	0ms
	others	4	0ms
	select	66	0ms
	update	37	0ms
unknown	Total	106,619	3h17m19s
	copy from	13	0ms
	copy to	575	0ms
	cte	2,300	0ms
	insert	12,702	0ms
	others	2,721	0ms
	select	33,887	0ms
	tcl	681	0ms
	update	505	0ms

Number of cancelled queries

Key values

1 per second Cancelled query Peak
2026-02-22 06:17:11 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

32,119 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	32,119	60.33%
1-5ms	16,328	30.67%
5-10ms	1,412	2.65%
10-25ms	1,634	3.07%
25-50ms	191	0.36%
50-100ms	116	0.22%
100-500ms	312	0.59%
500-1000ms	131	0.25%
1000-10000ms	739	1.39%
> 10000ms	253	0.48%

Slowest individual queries

Rank	Duration	Query
NO DATASET

Time consuming queries

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

0ms

1

Details

0ms

lock table public.stats_hrs_summary_by_groups in access share mode;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1	0ms	0ms

2

0ms

2

Details

0ms

copy public.powerstats_trumpet (symbolid, dayofweek, fromtime, enddate, stddev_15, ave_15, stddev_30, ave_30, stddev_60, ave_60, stddev_240, ave_240, stddev_1440, ave_1440) to stdout;

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

3

0ms

2

Details

0ms

select last_value, is_called from public.stats_by_groups_statsid_seq;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

4

0ms

2

Details

0ms

lock table public.timezones_korean in access share mode;

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

5

0ms

13

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Feb 22	06	13	0ms	0ms

6

0ms

2

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

7

0ms

1

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1	0ms	0ms

8

0ms

2,425

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 #8

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2,425	0ms	0ms

9

0ms

2

Details

0ms

select last_value, is_called from public.keylevels_results_resultuid_seq19;

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

10

0ms

2

Details

0ms

copy archive.whatshot (whid, brokerid, whdatetime, jobcompletiontime) to stdout;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

11

0ms

5

Details

0ms

set synchronize_seqscans to off;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 22	06	5	0ms	0ms

12

0ms

1

Details

0ms

select last_value, is_called from public."ProcessLocaleParameters_id_seq";

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1	0ms	0ms

13

0ms

976

Details

0ms

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

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Feb 22	06	976	0ms	0ms

14

0ms

2

Details

0ms

lock table public.timezones_turkish in access share mode;

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

15

0ms

2

Details

0ms

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

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

16

0ms

2

Details

0ms

lock table public.futures_symbols in access share mode;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

17

0ms

2

Details

0ms

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

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

18

0ms

2

Details

0ms

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

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

19

0ms

2

Details

0ms

lock table archive.patternresultsage in access share mode;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

20

0ms

1

Details

0ms

copy public.processes (id, locale, region, schedule, enabled, live, lastmodified, lastrun, contenttypeid, brokerid, uuid) to stdout;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

4,213

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 22	06	4,213	0ms	0ms

2

3,955

Details

0ms

select ?;

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Feb 22	06	3,955	0ms	0ms

3

3,295

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 #3

Day	Hour	Count	Duration	Avg duration
Feb 22	06	3,295	0ms	0ms

4

2,931

Details

0ms

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

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2,931	0ms	0ms

5

2,496

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 #5

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2,496	0ms	0ms

6

2,425

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2,425	0ms	0ms

7

1,742

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 #7

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1,742	0ms	0ms

8

1,730

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 #8

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1,730	0ms	0ms

9

1,664

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1,664	0ms	0ms

10

1,185

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 #10

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1,185	0ms	0ms

11

1,185

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 #11

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1,185	0ms	0ms

12

1,185

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 #12

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1,185	0ms	0ms

13

1,185

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 #13

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1,185	0ms	0ms

14

1,185

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 #14

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1,185	0ms	0ms

/* service='datadog-agent' */ 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 0 END as index_size, CASE WHEN C.reltoastrelid > 0 THEN pg_relation_size(C.reltoastrelid) ELSE 0 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 = 'relation' WHERE NOT (nspname = ANY ('{pg_catalog,information_schema}')) AND (L.relation IS NULL OR L.mode <> 'AccessExclusiveLock' OR NOT L.granted) AND relkind = 'r' AND ((relname ~ '.*')) LIMIT 300) as s;

Date: 2026-02-22 06:19:25 Duration: 0ms

15

1,185

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 #15

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1,185	0ms	0ms

16

976

Details

0ms

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

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 22	06	976	0ms	0ms

17

936

Details

0ms

select datetimeupdate from latest_candle_datetime_per_receng where recognitionengine ilike ?;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Feb 22	06	936	0ms	0ms

SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'HOTFOREX - 1';

Date: 2026-02-22 06:19:27 Duration: 0ms

18

786

Details

0ms

select a.attnum, a.attname, a.atttypmod, a.attstattarget, a.attstorage, t.typstorage, a.attnotnull, a.atthasdef, a.attisdropped, a.attlen, a.attalign, a.attislocal, pg_catalog.format_type(t.oid, a.atttypmod) as atttypname, a.attgenerated, case when a.atthasmissing and not a.attisdropped then a.attmissingval else null end as attmissingval, a.attidentity, pg_catalog.array_to_string(array ( select pg_catalog.quote_ident(option_name) || ? || pg_catalog.quote_literal(option_value) from pg_catalog.pg_options_to_table(attfdwoptions) order by option_name), e ?) as attfdwoptions, case when a.attcollation <> t.typcollation then a.attcollation else ? end as attcollation, array_to_string(a.attoptions, ?) as attoptions from pg_catalog.pg_attribute a left join pg_catalog.pg_type t on a.atttypid = t.oid where a.attrelid = ?::pg_catalog.oid and a.attnum > ?::pg_catalog.int2 order by a.attnum;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 22	06	786	0ms	0ms

19

720

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 22	06	720	0ms	0ms

20

708

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 22	06	708	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

1

Details

0ms

lock table public.stats_hrs_summary_by_groups in access share mode;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1	0ms	0ms

2

0ms

2

Details

0ms

copy public.powerstats_trumpet (symbolid, dayofweek, fromtime, enddate, stddev_15, ave_15, stddev_30, ave_30, stddev_60, ave_60, stddev_240, ave_240, stddev_1440, ave_1440) to stdout;

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

3

0ms

2

Details

0ms

select last_value, is_called from public.stats_by_groups_statsid_seq;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

4

0ms

2

Details

0ms

lock table public.timezones_korean in access share mode;

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

5

0ms

13

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Feb 22	06	13	0ms	0ms

6

0ms

2

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

7

0ms

1

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1	0ms	0ms

8

0ms

2,425

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 #8

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2,425	0ms	0ms

9

0ms

2

Details

0ms

select last_value, is_called from public.keylevels_results_resultuid_seq19;

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

10

0ms

2

Details

0ms

copy archive.whatshot (whid, brokerid, whdatetime, jobcompletiontime) to stdout;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

11

0ms

5

Details

0ms

set synchronize_seqscans to off;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 22	06	5	0ms	0ms

12

0ms

1

Details

0ms

select last_value, is_called from public."ProcessLocaleParameters_id_seq";

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1	0ms	0ms

13

0ms

976

Details

0ms

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

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Feb 22	06	976	0ms	0ms

14

0ms

2

Details

0ms

lock table public.timezones_turkish in access share mode;

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

15

0ms

2

Details

0ms

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

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

16

0ms

2

Details

0ms

lock table public.futures_symbols in access share mode;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

17

0ms

2

Details

0ms

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

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

18

0ms

2

Details

0ms

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

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

19

0ms

2

Details

0ms

lock table archive.patternresultsage in access share mode;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 22	06	2	0ms	0ms

20

0ms

1

Details

0ms

copy public.processes (id, locale, region, schedule, enabled, live, lastmodified, lastrun, contenttypeid, brokerid, uuid) to stdout;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1	0ms	0ms

Time consuming prepare


Date: 2026-02-22 06:16:15
Duration: 17ms
Database: postgres
Date: 2026-02-22 06:11:38
Duration: 0ms
Database: postgres
Date: 2026-02-22 06:02:37
Duration: 0ms
Database: postgres
Date: 2026-02-22 06:31:19
Duration: 1ms
Database: postgres
Date: 2026-02-22 06:05:59
Duration: 3ms
Database: postgres
Date: 2026-02-22 06:46:23
Duration: 0ms
Database: postgres
Date: 2026-02-22 06:32:05
Duration: 0ms
Database: postgres
Date: 2026-02-22 06:40:03
Duration: 12ms
Database: postgres
Date: 2026-02-22 06:10:43
Duration: 2ms
Database: postgres
Date: 2026-02-22 06:20:04
Duration: 3ms
Database: postgres
Date: 2026-02-22 06:47:22
Duration: 0ms
Database: postgres
Date: 2026-02-22 06:32:05
Duration: 0ms
Database: postgres
Date: 2026-02-22 06:46:58
Duration: 0ms
Database: postgres
Date: 2026-02-22 06:37:50
Duration: 2ms
Database: postgres
Date: 2026-02-22 06:07:25
Duration: 0ms
Database: postgres
Date: 2026-02-22 06:51:04
Duration: 0ms
Database: postgres
Date: 2026-02-22 06:07:26
Duration: 0ms
Database: postgres
Date: 2026-02-22 06:07:26
Duration: 0ms
Database: postgres
Date: 2026-02-22 06:07:25
Duration: 0ms
Database: postgres
Date: 2026-02-22 06:07:25
Duration: 0ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

16s282ms

1,423

Details

0ms

56ms

11ms

WITH rar_max as ( ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Feb 22	06	1,423	16s282ms	11ms

WITH rar_max as ( ;

Date: 2026-02-22 06:36:21 Duration: 56ms Database: postgres parameters: $1 = 't', $2 = '558', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '160', $14 = 'AUDSGD', $15 = 'CHFSGD', $16 = 'EURDKK', $17 = 'EURHKD', $18 = 'EURNOK', $19 = 'EURPLN', $20 = 'EURSEK', $21 = 'EURSGD', $22 = 'EURTRY', $23 = 'EURZAR', $24 = 'GBPDKK', $25 = 'GBPNOK', $26 = 'GBPSEK', $27 = 'GBPSGD', $28 = 'NOKJPY', $29 = 'NOKSEK', $30 = 'SEKJPY', $31 = 'SGDJPY', $32 = 'USDCNH', $33 = 'USDCZK', $34 = 'USDDKK', $35 = 'USDHKD', $36 = 'USDHUF', $37 = 'USDMXN', $38 = 'USDNOK', $39 = 'USDPLN', $40 = 'USDRUB', $41 = 'USDSEK', $42 = 'USDTHB', $43 = 'USDTRY', $44 = 'USDZAR', $45 = 'AUDUSD', $46 = 'EURUSD', $47 = 'GBPUSD', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDJPY', $51 = 'AUDCAD', $52 = 'AUDCHF', $53 = 'AUDJPY', $54 = 'AUDNZD', $55 = 'CADCHF', $56 = 'CADJPY', $57 = 'CHFJPY', $58 = 'EURAUD', $59 = 'EURCAD', $60 = 'EURCHF', $61 = 'EURGBP', $62 = 'EURJPY', $63 = 'EURNZD', $64 = 'GBPAUD', $65 = 'GBPCAD', $66 = 'GBPCHF', $67 = 'GBPJPY', $68 = 'GBPNZD', $69 = 'NZDCAD', $70 = 'NZDCHF', $71 = 'NZDJPY', $72 = 'NZDUSD', $73 = 'USDSGD', $74 = 'AUS200', $75 = 'DE30', $76 = 'ES35', $77 = 'F40', $78 = 'HK50', $79 = 'IT40', $80 = 'JP225', $81 = 'STOXX50', $82 = 'UK100', $83 = 'US2000', $84 = 'US30', $85 = 'US500', $86 = 'CHINA50', $87 = 'USTEC', $88 = 'XAGEUR', $89 = 'XAGUSD', $90 = 'XAUUSD', $91 = 'XAUEUR', $92 = 'XPDUSD', $93 = 'XPTUSD', $94 = 'AUDSGD', $95 = 'CHFSGD', $96 = 'EURDKK', $97 = 'EURHKD', $98 = 'EURNOK', $99 = 'EURPLN', $100 = 'EURSEK', $101 = 'EURSGD', $102 = 'EURTRY', $103 = 'EURZAR', $104 = 'GBPDKK', $105 = 'GBPNOK', $106 = 'GBPSEK', $107 = 'GBPSGD', $108 = 'NOKJPY', $109 = 'NOKSEK', $110 = 'SEKJPY', $111 = 'SGDJPY', $112 = 'USDCNH', $113 = 'USDCZK', $114 = 'USDDKK', $115 = 'USDHKD', $116 = 'USDHUF', $117 = 'USDMXN', $118 = 'USDNOK', $119 = 'USDPLN', $120 = 'USDRUB', $121 = 'USDSEK', $122 = 'USDTHB', $123 = 'USDTRY', $124 = 'USDZAR', $125 = 'AUDUSD', $126 = 'EURUSD', $127 = 'GBPUSD', $128 = 'USDCAD', $129 = 'USDCHF', $130 = 'USDJPY', $131 = 'AUDCAD', $132 = 'AUDCHF', $133 = 'AUDJPY', $134 = 'AUDNZD', $135 = 'CADCHF', $136 = 'CADJPY', $137 = 'CHFJPY', $138 = 'EURAUD', $139 = 'EURCAD', $140 = 'EURCHF', $141 = 'EURGBP', $142 = 'EURJPY', $143 = 'EURNZD', $144 = 'GBPAUD', $145 = 'GBPCAD', $146 = 'GBPCHF', $147 = 'GBPJPY', $148 = 'GBPNZD', $149 = 'NZDCAD', $150 = 'NZDCHF', $151 = 'NZDJPY', $152 = 'NZDUSD', $153 = 'USDSGD', $154 = 'AUS200', $155 = 'DE30', $156 = 'ES35', $157 = 'F40', $158 = 'HK50', $159 = 'IT40', $160 = 'JP225', $161 = 'STOXX50', $162 = 'UK100', $163 = 'US2000', $164 = 'US30', $165 = 'US500', $166 = 'CHINA50', $167 = 'USTEC', $168 = 'XAGEUR', $169 = 'XAGUSD', $170 = 'XAUUSD', $171 = 'XAUEUR', $172 = 'XPDUSD', $173 = 'XPTUSD', $174 = '0', $175 = '', $176 = '0', $177 = '0', $178 = '0', $179 = '500', $180 = '500', $181 = 't', $182 = '10', $183 = '10'
WITH rar_max as ( ;

Date: 2026-02-22 06:46:12 Duration: 54ms Database: postgres parameters: $1 = 't', $2 = '667', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '84', $14 = 'AUDCAD', $15 = 'AUDCHF', $16 = 'AUDJPY', $17 = 'AUDNZD', $18 = 'AUDSGD', $19 = 'CADCHF', $20 = 'CADJPY', $21 = 'CHFJPY', $22 = 'EURAUD', $23 = 'EURCAD', $24 = 'EURCHF', $25 = 'EURCZK', $26 = 'EURGBP', $27 = 'EURHUF', $28 = 'EURJPY', $29 = 'EURNOK', $30 = 'EURNZD', $31 = 'EURPLN', $32 = 'EURSEK', $33 = 'EURSGD', $34 = 'EURTRY', $35 = 'EURZAR', $36 = 'GBPAUD', $37 = 'GBPCAD', $38 = 'GBPCHF', $39 = 'GBPJPY', $40 = 'GBPNZD', $41 = 'GBPPLN', $42 = 'GBPSEK', $43 = 'GBPSGD', $44 = 'NZDCAD', $45 = 'NZDCHF', $46 = 'NZDJPY', $47 = 'NZDSGD', $48 = 'USDCNH', $49 = 'USDCZK', $50 = 'USDHUF', $51 = 'USDNOK', $52 = 'USDPLN', $53 = 'USDSEK', $54 = 'USDSGD', $55 = 'USDTRY', $56 = 'USDZAR', $57 = 'WTI', $58 = 'XBRUSD', $59 = 'XTIUSD', $60 = 'BTCUSD', $61 = 'XAGAUD', $62 = 'XAGUSD', $63 = 'XAUAUD', $64 = 'XAUUSD', $65 = 'XPTUSD', $66 = 'XPDUSD', $67 = 'AUDUSD', $68 = 'EURUSD', $69 = 'GBPUSD', $70 = 'NZDUSD', $71 = 'USDCAD', $72 = 'USDCHF', $73 = 'USDHKD', $74 = 'USDJPY', $75 = 'AUS200', $76 = 'CHINA300', $77 = 'CHINA50', $78 = 'DJ30', $79 = 'ESP35t', $80 = 'EUR50', $81 = 'EURO50', $82 = 'FRA40', $83 = 'GDAXI', $84 = 'GDAXIm', $85 = 'HK50', $86 = 'ITA40', $87 = 'J225', $88 = 'JP225', $89 = 'NAS100', $90 = 'SING30', $91 = 'SPA35', $92 = 'STOXX50', $93 = 'SUI20', $94 = 'UK100', $95 = 'US100', $96 = 'US30', $97 = 'US500', $98 = '0', $99 = '', $100 = '0', $101 = '0', $102 = '0', $103 = '700', $104 = '700', $105 = 't', $106 = '10', $107 = '10'
WITH rar_max as ( ;

Date: 2026-02-22 06:46:25 Duration: 53ms Database: postgres parameters: $1 = 't', $2 = '667', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '84', $14 = 'AUDCAD', $15 = 'AUDCHF', $16 = 'AUDJPY', $17 = 'AUDNZD', $18 = 'AUDSGD', $19 = 'CADCHF', $20 = 'CADJPY', $21 = 'CHFJPY', $22 = 'EURAUD', $23 = 'EURCAD', $24 = 'EURCHF', $25 = 'EURCZK', $26 = 'EURGBP', $27 = 'EURHUF', $28 = 'EURJPY', $29 = 'EURNOK', $30 = 'EURNZD', $31 = 'EURPLN', $32 = 'EURSEK', $33 = 'EURSGD', $34 = 'EURTRY', $35 = 'EURZAR', $36 = 'GBPAUD', $37 = 'GBPCAD', $38 = 'GBPCHF', $39 = 'GBPJPY', $40 = 'GBPNZD', $41 = 'GBPPLN', $42 = 'GBPSEK', $43 = 'GBPSGD', $44 = 'NZDCAD', $45 = 'NZDCHF', $46 = 'NZDJPY', $47 = 'NZDSGD', $48 = 'USDCNH', $49 = 'USDCZK', $50 = 'USDHUF', $51 = 'USDNOK', $52 = 'USDPLN', $53 = 'USDSEK', $54 = 'USDSGD', $55 = 'USDTRY', $56 = 'USDZAR', $57 = 'WTI', $58 = 'XBRUSD', $59 = 'XTIUSD', $60 = 'BTCUSD', $61 = 'XAGAUD', $62 = 'XAGUSD', $63 = 'XAUAUD', $64 = 'XAUUSD', $65 = 'XPTUSD', $66 = 'XPDUSD', $67 = 'AUDUSD', $68 = 'EURUSD', $69 = 'GBPUSD', $70 = 'NZDUSD', $71 = 'USDCAD', $72 = 'USDCHF', $73 = 'USDHKD', $74 = 'USDJPY', $75 = 'AUS200', $76 = 'CHINA300', $77 = 'CHINA50', $78 = 'DJ30', $79 = 'ESP35t', $80 = 'EUR50', $81 = 'EURO50', $82 = 'FRA40', $83 = 'GDAXI', $84 = 'GDAXIm', $85 = 'HK50', $86 = 'ITA40', $87 = 'J225', $88 = 'JP225', $89 = 'NAS100', $90 = 'SING30', $91 = 'SPA35', $92 = 'STOXX50', $93 = 'SUI20', $94 = 'UK100', $95 = 'US100', $96 = 'US30', $97 = 'US500', $98 = '0', $99 = '', $100 = '0', $101 = '0', $102 = '0', $103 = '700', $104 = '700', $105 = 't', $106 = '10', $107 = '10'

2

1s756ms

605

Details

1ms

15ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	06	605	1s756ms	2ms

SELECT symbolid, ;

Date: 2026-02-22 06:10:23 Duration: 15ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '60', $3 = '#ADBE'
SELECT symbolid, ;

Date: 2026-02-22 06:16:14 Duration: 13ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'GBPJPY', $4 = 'GBPUSD'
SELECT symbolid, ;

Date: 2026-02-22 06:06:06 Duration: 9ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'USDJPY', $4 = 'XAGUSD.FX', $5 = 'USDJPY.ID', $6 = 'XAGUSD', $7 = 'XAUUSD.FX', $8 = 'USDJPY.FX', $9 = 'XAGUSD.ID', $10 = 'XAUUSD'

3

1s279ms

3,740

Details

0ms

13ms

0ms

SELECT ;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	06	3,740	1s279ms	0ms

SELECT ;

Date: 2026-02-22 06:43:38 Duration: 13ms Database: postgres parameters: $1 = '515840233928754300'
SELECT ;

Date: 2026-02-22 06:43:38 Duration: 11ms Database: postgres parameters: $1 = '515840233928754300'
SELECT ;

Date: 2026-02-22 06:46:05 Duration: 7ms Database: postgres parameters: $1 = '607720284681523301', $2 = '607720284681523301', $3 = '607720284681523301'

4

415ms

45

Details

4ms

43ms

9ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	06	45	415ms	9ms

WITH last_candle AS ( ;

Date: 2026-02-22 06:36:00 Duration: 43ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-02-22 06:24:00 Duration: 25ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-02-22 06:48:00 Duration: 20ms Database: postgres parameters: $1 = '558', $2 = '558'

5

384ms

13

Details

0ms

56ms

29ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	06	13	384ms	29ms

with wh_patitioned as ( ;

Date: 2026-02-22 06:10:02 Duration: 56ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2026-02-22 06:26:19 Duration: 51ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2026-02-22 06:35:02 Duration: 41ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'

6

227ms

2,425

Details

0ms

13ms

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 #6

Day	Hour	Count	Duration	Avg duration
	06	2,425	227ms	0ms

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

Date: 2026-02-22 06:46:22 Duration: 13ms Database: postgres parameters: $1 = '2026-02-20 22:00:00', $2 = '127.26', $3 = '127.775', $4 = '126.995', $5 = '127.765', $6 = '1021', $7 = '515840249450718300', $8 = '0', $9 = '2026-02-22 06:46:22.721', $10 = '2026-02-22 06:46:22.72', $11 = '127.26', $12 = '127.775', $13 = '126.995', $14 = '127.765', $15 = '1021', $16 = '0', $17 = '2026-02-22 06:46:22.721', $18 = '2026-02-22 06:46:22.72'
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-22 06:46:18 Duration: 0ms Database: postgres parameters: $1 = '2026-02-20 22:00:00', $2 = '209.2025', $3 = '209.2175', $4 = '209.0525', $5 = '209.172', $6 = '5338', $7 = '515840230497281300', $8 = '0', $9 = '2026-02-22 06:46:18.436', $10 = '2026-02-22 06:46:18.435', $11 = '209.2025', $12 = '209.2175', $13 = '209.0525', $14 = '209.172', $15 = '5338', $16 = '0', $17 = '2026-02-22 06:46:18.436', $18 = '2026-02-22 06:46:18.435'
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-22 06:31:26 Duration: 0ms Database: postgres parameters: $1 = '2026-02-20 22:00:00', $2 = '134.45', $3 = '135.645', $4 = '134.325', $5 = '135.27', $6 = '3323', $7 = '515840249453020300', $8 = '0', $9 = '2026-02-22 06:31:26.629', $10 = '2026-02-22 06:31:26.629', $11 = '134.45', $12 = '135.645', $13 = '134.325', $14 = '135.27', $15 = '3323', $16 = '0', $17 = '2026-02-22 06:31:26.629', $18 = '2026-02-22 06:31:26.629'

7

223ms

67

Details

0ms

18ms

3ms

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

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	06	67	223ms	3ms

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

Date: 2026-02-22 06:51:31 Duration: 18ms 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: 2026-02-22 06:22:05 Duration: 18ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;

Date: 2026-02-22 06:51:27 Duration: 18ms Database: postgres parameters: $1 = '489', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

8

216ms

124

Details

1ms

2ms

1ms

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

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	06	124	216ms	1ms

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

Date: 2026-02-22 06:31:19 Duration: 2ms Database: postgres parameters: $1 = 'ATFX'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-02-22 06:17:05 Duration: 2ms Database: postgres parameters: $1 = 'ICMARKETS'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-02-22 06:00:58 Duration: 2ms Database: postgres parameters: $1 = 'ICMARKETS'

9

193ms

2,496

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 #9

Day	Hour	Count	Duration	Avg duration
	06	2,496	193ms	0ms

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

Date: 2026-02-22 06:31:11 Duration: 2ms Database: postgres parameters: $1 = '2026-02-20 21:00:00', $2 = '9090.4', $3 = '9090.4', $4 = '9083.9', $5 = '9085.4', $6 = '409', $7 = '515840245910472300', $8 = '0', $9 = '2026-02-22 06:31:11.446', $10 = '2026-02-22 06:31:11.445', $11 = '9090.4', $12 = '9090.4', $13 = '9083.9', $14 = '9085.4', $15 = '409', $16 = '0', $17 = '2026-02-22 06:31:11.446', $18 = '2026-02-22 06:31:11.445'
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-22 06:16:23 Duration: 0ms Database: postgres parameters: $1 = '2026-02-20 22:30:00', $2 = '199.75', $3 = '200.06', $4 = '199.295', $5 = '199.82', $6 = '1384', $7 = '515840249447081300', $8 = '0', $9 = '2026-02-22 06:16:23.345', $10 = '2026-02-22 06:16:23.332', $11 = '199.75', $12 = '200.06', $13 = '199.295', $14 = '199.82', $15 = '1384', $16 = '0', $17 = '2026-02-22 06:16:23.345', $18 = '2026-02-22 06:16:23.332'
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-22 06:11:52 Duration: 0ms Database: postgres parameters: $1 = '2026-02-20 23:00:00', $2 = '49631.05', $3 = '49655.55', $4 = '49612.55', $5 = '49621.05', $6 = '5610', $7 = '515840248000726300', $8 = '0', $9 = '2026-02-22 06:11:52.487', $10 = '2026-02-22 06:11:52.331', $11 = '49631.05', $12 = '49655.55', $13 = '49612.55', $14 = '49621.05', $15 = '5610', $16 = '0', $17 = '2026-02-22 06:11:52.487', $18 = '2026-02-22 06:11:52.331'

10

167ms

3,838

Details

0ms

14ms

0ms

select 1;

Times Reported Time consuming bind #10

Day	Hour	Count	Duration	Avg duration
	06	3,838	167ms	0ms

select 1;

Date: 2026-02-22 06:21:34 Duration: 14ms Database: postgres
select 1;

Date: 2026-02-22 06:37:48 Duration: 8ms Database: postgres
select 1;

Date: 2026-02-22 06:26:19 Duration: 8ms Database: postgres

11

145ms

2,931

Details

0ms

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

Times Reported Time consuming bind #11

Day	Hour	Count	Duration	Avg duration
	06	2,931	145ms	0ms

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

Date: 2026-02-22 06:46:05 Duration: 0ms Database: postgres parameters: $1 = '2026-02-20 22:30:00', $2 = '46565', $3 = '46575', $4 = '46540', $5 = '46545', $6 = '559', $7 = '515840233917187300', $8 = '0', $9 = '2026-02-22 06:46:05.328', $10 = '2026-02-22 06:46:05.267', $11 = '46565', $12 = '46575', $13 = '46540', $14 = '46545', $15 = '559', $16 = '0', $17 = '2026-02-22 06:46:05.328', $18 = '2026-02-22 06:46:05.267'
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-22 06:46:23 Duration: 0ms Database: postgres parameters: $1 = '2026-02-21 00:45:00', $2 = '49628.9', $3 = '49637.53', $4 = '49616.51', $5 = '49628.04', $6 = '365', $7 = '515840249387894300', $8 = '0', $9 = '2026-02-22 06:46:23.72', $10 = '2026-02-22 06:46:23.655', $11 = '49628.9', $12 = '49637.53', $13 = '49616.51', $14 = '49628.04', $15 = '365', $16 = '0', $17 = '2026-02-22 06:46:23.72', $18 = '2026-02-22 06:46:23.655'
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-22 06:46:15 Duration: 0ms Database: postgres parameters: $1 = '2026-02-20 22:45:00', $2 = '1.971795', $3 = '1.972265', $4 = '1.971715', $5 = '1.97205', $6 = '707', $7 = '515840230400034300', $8 = '0', $9 = '2026-02-22 06:46:15.295', $10 = '2026-02-22 06:46:15.22', $11 = '1.971795', $12 = '1.972265', $13 = '1.971715', $14 = '1.97205', $15 = '707', $16 = '0', $17 = '2026-02-22 06:46:15.296', $18 = '2026-02-22 06:46:15.22'

12

20ms

49

Details

0ms

12ms

0ms

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

Times Reported Time consuming bind #12

Day	Hour	Count	Duration	Avg duration
	06	49	20ms	0ms

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

Date: 2026-02-22 06:20:28 Duration: 12ms Database: postgres parameters: $1 = '607713876528419301'
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;

Date: 2026-02-22 06:08:23 Duration: 2ms Database: postgres parameters: $1 = '607712580355171301'
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;

Date: 2026-02-22 06:18:22 Duration: 2ms Database: postgres parameters: $1 = '607713760614899301'

13

15ms

11

Details

0ms

10ms

1ms

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

Times Reported Time consuming bind #13

Day	Hour	Count	Duration	Avg duration
	06	11	15ms	1ms

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

Date: 2026-02-22 06:18:02 Duration: 10ms Database: postgres parameters: $1 = '607713936437116302'
/*server.FibonacciResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, Exchange AS e, longname as lo, shortname as sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, 1 - errormargin as rq, 1 - noise as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM Fibonacci_Results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN fibonaccipatterns p on a.pattern = p.patternname where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-02-22 06:05:42 Duration: 4ms Database: postgres parameters: $1 = '607713935342476302'
/*server.FibonacciResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, Exchange AS e, longname as lo, shortname as sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, 1 - errormargin as rq, 1 - noise as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM Fibonacci_Results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN fibonaccipatterns p on a.pattern = p.patternname where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-02-22 06:34:14 Duration: 0ms Database: postgres parameters: $1 = '607713936806956302'

14

14ms

96

Details

0ms

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

Times Reported Time consuming bind #14

Day	Hour	Count	Duration	Avg duration
	06	96	14ms	0ms

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

Date: 2026-02-22 06:47:22 Duration: 0ms Database: postgres parameters: $1 = '2026-02-20 16:00:00', $2 = '56755', $3 = '57270', $4 = '56660', $5 = '57060', $6 = '5989', $7 = '515840230561612300', $8 = '0', $9 = '2026-02-22 06:47:22.333', $10 = '2026-02-22 06:47:22.333', $11 = '56755', $12 = '57270', $13 = '56660', $14 = '57060', $15 = '5989', $16 = '0', $17 = '2026-02-22 06:47:22.333', $18 = '2026-02-22 06:47:22.333'
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-22 06:16:22 Duration: 0ms Database: postgres parameters: $1 = '2026-02-20 16:00:00', $2 = '56755', $3 = '57270', $4 = '56660', $5 = '57060', $6 = '5989', $7 = '515840230561612300', $8 = '0', $9 = '2026-02-22 06:16:22.147', $10 = '2026-02-22 06:16:22.146', $11 = '56755', $12 = '57270', $13 = '56660', $14 = '57060', $15 = '5989', $16 = '0', $17 = '2026-02-22 06:16:22.147', $18 = '2026-02-22 06:16:22.146'
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-22 06:01:21 Duration: 0ms Database: postgres parameters: $1 = '2026-02-20 16:00:00', $2 = '56755', $3 = '57270', $4 = '56660', $5 = '57060', $6 = '5989', $7 = '515840230561612300', $8 = '0', $9 = '2026-02-22 06:01:21.519', $10 = '2026-02-22 06:01:21.518', $11 = '56755', $12 = '57270', $13 = '56660', $14 = '57060', $15 = '5989', $16 = '0', $17 = '2026-02-22 06:01:21.519', $18 = '2026-02-22 06:01:21.518'

15

13ms

18

Details

0ms

1ms

0ms

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

Times Reported Time consuming bind #15

Day	Hour	Count	Duration	Avg duration
	06	18	13ms	0ms

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

Date: 2026-02-22 06:10:02 Duration: 1ms Database: postgres
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;

Date: 2026-02-22 06:21:03 Duration: 1ms Database: postgres
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;

Date: 2026-02-22 06:01:11 Duration: 0ms Database: postgres

16

12ms

2

Details

5ms

6ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #16

Day	Hour	Count	Duration	Avg duration
	06	2	12ms	6ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-22 06:51:04 Duration: 6ms Database: postgres parameters: $1 = '627', $2 = '627'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-22 06:36:14 Duration: 5ms Database: postgres parameters: $1 = '627', $2 = '627'

17

10ms

58

Details

0ms

INSERT INTO T1440_underlying (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 #17

Day	Hour	Count	Duration	Avg duration
	06	58	10ms	0ms

INSERT INTO T1440_underlying (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-22 06:32:51 Duration: 0ms Database: postgres parameters: $1 = '2026-02-20 00:00:00', $2 = '259.095', $3 = '264.745', $4 = '258.28', $5 = '264.6', $6 = '13305', $7 = '515840249386902300', $8 = '0', $9 = '2026-02-22 06:32:51.946', $10 = '2026-02-22 06:32:51.945', $11 = '259.095', $12 = '264.745', $13 = '258.28', $14 = '264.6', $15 = '13305', $16 = '0', $17 = '2026-02-22 06:32:51.946', $18 = '2026-02-22 06:32:51.945'
INSERT INTO T1440_underlying (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-22 06:46:58 Duration: 0ms Database: postgres parameters: $1 = '2026-02-20 00:00:00', $2 = '258.6745', $3 = '260.687', $4 = '254.729', $5 = '256.144', $6 = '82605', $7 = '515840249404368300', $8 = '0', $9 = '2026-02-22 06:46:58.348', $10 = '2026-02-22 06:46:58.347', $11 = '258.6745', $12 = '260.687', $13 = '254.729', $14 = '256.144', $15 = '82605', $16 = '0', $17 = '2026-02-22 06:46:58.348', $18 = '2026-02-22 06:46:58.347'
INSERT INTO T1440_underlying (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-22 06:30:59 Duration: 0ms Database: postgres parameters: $1 = '2026-02-20 00:00:00', $2 = '258.6745', $3 = '260.687', $4 = '254.729', $5 = '256.144', $6 = '82605', $7 = '515840249404368300', $8 = '0', $9 = '2026-02-22 06:30:59.513', $10 = '2026-02-22 06:30:59.512', $11 = '258.6745', $12 = '260.687', $13 = '254.729', $14 = '256.144', $15 = '82605', $16 = '0', $17 = '2026-02-22 06:30:59.513', $18 = '2026-02-22 06:30:59.512'

18

10ms

18

Details

0ms

2ms

0ms

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

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	06	18	10ms	0ms

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

Date: 2026-02-22 06:05:20 Duration: 2ms Database: postgres parameters: $1 = '607712581787399303'
/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-02-22 06:52:51 Duration: 2ms Database: postgres parameters: $1 = '607713291943693303'
/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, longname, shortname, Exchange AS e, timegranularity AS tg, a.PatternID AS pid, a.direction AS d, a.patternprice as pp, atbaridentified AS pet, CASE WHEN (x9 != '') THEN x9 WHEN (x8 != '') THEN x8 WHEN (x7 != '') THEN x7 WHEN (x6 != '') THEN x6 WHEN (x5 != '') THEN x5 WHEN (x4 != '') THEN x4 WHEN (x3 != '') THEN x3 WHEN (x2 != '') THEN x2 END AS pst, PatternPrice AS patp, x0, x1, x2, CASE WHEN (x3 != '') THEN x3 ELSE '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb FROM keylevels_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid INNER JOIN hrspatterns p on a.patternid = p.patternid where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-02-22 06:04:35 Duration: 2ms Database: postgres parameters: $1 = '607713058277029303'

19

7ms

2

Details

3ms

4ms

3ms

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

Times Reported Time consuming bind #19

Day	Hour	Count	Duration	Avg duration
	06	2	7ms	3ms

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

Date: 2026-02-22 06:37:50 Duration: 4ms Database: postgres
select * from datafeed_symbols where classname ilike 'ICMARKETS-AU-MT5' limit 5000;

Date: 2026-02-22 06:07:50 Duration: 3ms Database: postgres

20

5ms

43

Details

0ms

1ms

0ms

SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T15 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	06	43	5ms	0ms

SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T15 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;

Date: 2026-02-22 06:10:16 Duration: 1ms Database: postgres parameters: $1 = '515840243244148300'
SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T15 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;

Date: 2026-02-22 06:18:22 Duration: 1ms Database: postgres parameters: $1 = '500991628208235200'
SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T15 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;

Date: 2026-02-22 06:20:28 Duration: 0ms Database: postgres parameters: $1 = '515840243917260300'

Log levels

Key values

170,933 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	303	0.18%
DETAIL	29,011	16.97%
ERROR	525	0.31%
LOG	140,223	82.03%
STATEMENT	871	0.51%

Events distribution

Key values

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

Most Frequent Errors/Events

Key values

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

Rank

Times reported

Error

1

356

Details

ERROR: pg_stat_statements must be loaded via shared_preload_libraries

Times Reported Most Frequent Error / Event #1

Day	Hour	Count
Feb 22	06	356

ERROR: pg_stat_statements must be loaded via shared_preload_libraries

2

68

Details

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

Times Reported Most Frequent Error / Event #2

Day	Hour	Count
Feb 22	06	68

LOG: process 26045 still waiting for AccessShareLock on relation 5883477 of database 5881926 after 1000.036 ms
LOG: process 26045 still waiting for AccessShareLock on relation 5883477 of database 5881926 after 1000.044 ms
LOG: process 26045 still waiting for AccessShareLock on relation 5883477 of database 5881926 after 1000.047 ms

3

56

Details

ERROR: canceling statement due to statement timeout

Times Reported Most Frequent Error / Event #3

Day	Hour	Count
Feb 22	06	56

ERROR: canceling statement due to statement timeout

4

48

Details

ERROR: schema "..." does not exist

Times Reported Most Frequent Error / Event #4

Day	Hour	Count
Feb 22	06	48

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

5

3

Details

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

Times Reported Most Frequent Error / Event #5

Day	Hour	Count
Feb 22	06	3

LOG: process 8771 still waiting for AccessExclusiveLock on relation 5883477 of database 5881926 after 1000.045 ms
LOG: process 11991 still waiting for AccessExclusiveLock on relation 5894441 of database 5881926 after 1000.051 ms
LOG: process 11991 still waiting for AccessExclusiveLock on relation 5894441 of database 5881926 after 60994.126 ms

Global information

Overview

Global Stats

SQL Traffic

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SELECT Traffic

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INSERT/UPDATE/DELETE Traffic

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Queries duration

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Prepared queries ratio

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General Activity

Connections

Established Connections

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Connections per host

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Simultaneous sessions

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Histogram of session times

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Sessions per application

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Temporary Files

Size of temporary files

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Temporary Files Activity

Queries generating the most temporary files (N)

Queries generating the largest temporary files

Vacuums

Vacuums / Analyzes Distribution

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Analyzes per table

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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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Most frequent waiting queries (N)

Queries that waited the most

Queries

Queries by type

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Queries by database

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Queries by user

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Duration by user