pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Fri Jan 23 23:59:40 2026
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-01-24_010000.log
Parsed 1,876,654 log entries in 38s
Log start from 2026-01-24 01:00:00 to 2026-01-24 01:59:33

Global Stats

186 Number of unique normalized queries
170,427 Number of queries
1h53m20s Total query duration
2026-01-24 01:00:00 First query
2026-01-24 01:59:33 Last query
2,565 queries/s at 2026-01-24 01:00:04 Query peak

1h53m20s Total query duration
14s518ms Prepare/parse total duration
1m3s Bind total duration
1h52m2s Execute total duration

34 Number of events
1 Number of unique normalized events
34 Max number of times the same event was reported
0 Number of cancellation

29 Total number of automatic vacuums
43 Total number of automatic analyzes

558 Number temporary file
133.85 MiB Max size of temporary file
6.55 MiB Average size of temporary file

5,687 Total number of sessions
13 sessions at 2026-01-24 01:59:11 Session peak
2d1h40m41s Total duration of sessions
31s447ms Average duration of sessions
29 Average queries per session
1s195ms Average queries duration per session
30s251ms Average idle time per session

5,687 Total number of connections
48 connections/s at 2026-01-24 01:11:51 Connection peak
3 Total number of databases

SQL Traffic

Key values

2,565 queries/s Query Peak
2026-01-24 01:00:04 Date

SELECT Traffic

Key values

1,276 queries/s Query Peak
2026-01-24 01:00:04 Date

INSERT/UPDATE/DELETE Traffic

Key values

160 queries/s Query Peak
2026-01-24 01:02:51 Date

Queries duration

Key values

1h53m20s 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)
Jan 24	01	170,427	0ms	32s506ms	39ms	3m6s	3m28s	4m24s

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Jan 24	01	49,736	26	0ms	0ms	0ms	0ms

Day	Hour	INSERT	UPDATE	DELETE	COPY FROM	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Jan 24	01	17,108	660	16	96	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Jan 24	01	34,287	65,880	1.92	45.56%

Day	Hour	Count	Average / Second
Jan 24	01	5,687	1.58/s

Day	Hour	Count	Average Duration	Average idle time
Jan 24	01	5,687	31s447ms	30s265ms

↑ Back to the top of the General Activity table

Established Connections

Key values

48 connections Connection Peak
2026-01-24 01:11:51 Date

Connections per database

Key values

acaweb_fx Main Database
5,687 connections Total

Chart
Table

Database	User	Count
acaweb_fx		5,591
	postgres	5,207
	psql	384
socialmedia		96
	postgres	96

Connections per user

Key values

postgres Main User
5,687 connections Total

Chart
Table

User	Count
postgres	5,303
psql	384

Connections per host

Key values

192.168.1.15 Main host with 2823 connections
5,687 Total connections

Chart
Table

Host	Count
127.0.0.1	110
192.168.0.114	5
192.168.0.216	114
192.168.0.74	700
192.168.1.145	94
192.168.1.15	2,823
192.168.1.20	101
192.168.1.231	20
192.168.1.239	43
192.168.1.90	6
192.168.2.126	18
192.168.2.82	36
192.168.3.199	39
192.168.4.142	854
192.168.4.150	10
192.168.4.167	1
192.168.4.238	16
192.168.4.33	93
192.168.4.98	330
[local]	274

Simultaneous sessions

Key values

13 sessions Session Peak
2026-01-24 01:59:11 Date

Histogram of session times

Key values

4,865 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	4,865	85.55%
500ms-1s	175	3.08%
1s-30s	379	6.66%
30s-1m	166	2.92%
1m-10m	36	0.63%
10m-30m	54	0.95%
30m-1h	1	0.02%
1h-8h	11	0.19%
> 8h	0	0.00%

Sessions per database

Key values

acaweb_fx Main Database
5,687 sessions Total

Chart
Table

Database	User	Count	Total Duration	Average Duration
acaweb_fx	5,591	2d1h24m21s	31s812ms
socialmedia	96	16m20s	10s214ms

Sessions per user

Key values

postgres Main User
5,687 sessions Total

Chart
Table

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

Sessions per host

Key values

192.168.1.15 Main Host
5,687 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
127.0.0.1	110	3s596ms	32ms
192.168.0.114	5	25m	5m
192.168.0.216	114	5m45s	3s34ms
192.168.0.74	700	1h56m23s	9s976ms
192.168.1.145	94	2h1m20s	1m17s
192.168.1.15	2,823	2h2m13s	2s597ms
192.168.1.20	101	12h53m	7m39s
192.168.1.231	20	9h52m42s	29m38s
192.168.1.239	43	196ms	4ms
192.168.1.90	6	44ms	7ms
192.168.2.126	18	5s216ms	289ms
192.168.2.82	36	13s265ms	368ms
192.168.3.199	39	31s757ms	814ms
192.168.4.142	854	8m56s	628ms
192.168.4.150	10	20h9m38s	2h57s
192.168.4.167	1	157ms	157ms
192.168.4.238	16	20s993ms	1s312ms
192.168.4.33	93	1m20s	863ms
192.168.4.98	330	13s925ms	42ms
[local]	274	2m51s	624ms

Sessions per application

Key values

unknown Main Host
5,687 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	5,687	2d1h40m41s	31s447ms

Checkpoints Buffers

Key values

4,877 buffers Checkpoint Peak
2026-01-24 01:07:02 Date
210.030 seconds Highest write time
0.007 seconds Sync time

Checkpoints Wal files

Key values

2 files Wal files usage Peak
2026-01-24 01:52:03 Date

Checkpoints distance

Key values

65.96 Mo Distance Peak
2026-01-24 01:07:02 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Jan 24	01	20,991	1,673.643s	0.036s	1,673.956s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Jan 24	01	0	0	12	1,421	0.007s	0s

Day	Hour	Count	Avg time (sec)
Jan 24	01	0	0s

Day	Hour	Mean distance	Mean estimate
Jan 24	01	16,461.75 kB	67,387.83 kB

↑ Back to the top of the Checkpoint Activity table

Checkpoint causes

Key values

time (12) Main checkpoint cause
12 checkpoints Total

Chart
Table

Cause	Number of checkpoints
time	12
Total	12

Size of temporary files

Key values

92.77 MiB Temp Files size Peak
2026-01-24 01:05:36 Date

Number of temporary files

Key values

30 per second Temp Files Peak
2026-01-24 01:47:10 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Jan 24	01	558	3.57 GiB	6.55 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	22	167.06 MiB	7.59 MiB	7.59 MiB	7.59 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: 2026-01-24 01:03:17 Duration: 0ms
2	18	55.51 MiB	3.08 MiB	3.08 MiB	3.08 MiB	select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ?), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?)), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc; SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ($2 = 0 OR s.timegranularity in ($3, $4, $5, $6, $7, $8, $9)) AND ($10 = 0 OR s.exchange in ($11)) AND ($12 = 0 OR coalesce(bim.code, s.symbol) in ($13, $14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226, $227, $228, $229, $230, $231, $232, $233, $234, $235, $236, $237, $238, $239, $240, $241, $242, $243, $244, $245, $246, $247, $248, $249, $250, $251, $252, $253, $254, $255, $256, $257, $258, $259, $260, $261, $262, $263, $264, $265, $266, $267, $268, $269, $270, $271, $272, $273, $274, $275, $276, $277, $278, $279, $280, $281, $282, $283, $284, $285, $286, $287, $288, $289, $290, $291, $292, $293, $294, $295, $296, $297, $298, $299, $300, $301, $302, $303, $304, $305, $306, $307, $308, $309, $310, $311, $312, $313, $314, $315, $316, $317, $318, $319, $320, $321, $322)) AND ($323 = 0 OR ccr.patternlengthbars <= $324)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $325 OR relevant = 1) AND ($326 = 0 OR age <= $327) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-01-24 01:02:43 Duration: 0ms
3	16	737.50 MiB	46.09 MiB	46.09 MiB	46.09 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: 2026-01-24 01:01:12 Duration: 0ms
4	16	1.22 GiB	78.24 MiB	78.24 MiB	78.24 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: 2026-01-24 01:01:15 Duration: 0ms
5	8	1.05 GiB	133.84 MiB	133.85 MiB	133.85 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2026-01-24 01:02:21 Duration: 0ms
6	4	355.59 MiB	88.89 MiB	88.91 MiB	88.90 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2026-01-24 01:02:05 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	133.85 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-24 01:02:21 ]
2	133.85 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-24 01:32:16 ]
3	133.85 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-24 01:47:16 ]
4	133.85 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-24 01:50:32 ]
5	133.85 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-24 01:17:16 ]
6	133.85 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-24 01:35:32 ]
7	133.85 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-24 01:20:32 ]
8	133.84 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-24 01:05:32 ]
9	88.91 MiB	select updateageforrelevantresults (); [ Date: 2026-01-24 01:02:05 ]
10	88.90 MiB	select updateageforrelevantresults (); [ Date: 2026-01-24 01:32:05 ]
11	88.89 MiB	select updateageforrelevantresults (); [ Date: 2026-01-24 01:47:05 ]
12	88.89 MiB	select updateageforrelevantresults (); [ Date: 2026-01-24 01:17:05 ]
13	78.24 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: 2026-01-24 01:01:15 ]
14	78.24 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: 2026-01-24 01:03:15 ]
15	78.24 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: 2026-01-24 01:05:15 ]
16	78.24 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: 2026-01-24 01:11:17 ]
17	78.24 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: 2026-01-24 01:16:16 ]
18	78.24 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: 2026-01-24 01:18:15 ]
19	78.24 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: 2026-01-24 01:20:15 ]
20	78.24 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: 2026-01-24 01:26:15 ]

Vacuums / Analyzes Distribution

Key values

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

Analyzes per table

Key values

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

Chart
Table

Table	Number of analyzes
acaweb_fx.public.solr_relevance_old	16
acaweb_fx.pg_catalog.pg_attribute	6
acaweb_fx.public.datafeeds_latestrun	4
acaweb_fx.pg_catalog.pg_class	4
acaweb_fx.pg_catalog.pg_type	3
acaweb_fx.pg_catalog.pg_index	2
acaweb_fx.public.latest_t15_candle_view	2
acaweb_fx.public.solr_imports	1
acaweb_fx.pg_catalog.pg_depend	1
acaweb_fx.public.relevance_keylevels_results	1
acaweb_fx.public.relevance_autochartist_results	1
acaweb_fx.public.latest_candle_datetime_per_receng	1
acaweb_fx.public.relevance_fibonacci_results	1
Total	43

Vacuums per table

Key values

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

Chart
Table

		Index	Buffer usage			Skipped		WAL usage
Table	Vacuums	scans	hits	misses	dirtied	pins	frozen	records	full page	bytes
acaweb_fx.public.solr_relevance_old	16	16	11,485	0	60	0	0	7,498	972	4,968,619
acaweb_fx.public.datafeeds_latestrun	4	0	492	0	10	0	0	48	11	55,015
acaweb_fx.pg_catalog.pg_attribute	2	2	1,917	0	262	0	134	752	270	1,615,569
acaweb_fx.pg_toast.pg_toast_2619	1	1	166	0	31	0	0	100	30	119,133
acaweb_fx.pg_catalog.pg_type	1	1	163	0	21	0	0	54	21	123,904
acaweb_fx.pg_catalog.pg_statistic	1	1	1,085	0	163	0	582	448	159	594,398
acaweb_fx.public.latest_t15_candle_view	1	1	67	0	1	0	0	6	1	9,067
acaweb_fx.public.relevance_keylevels_results	1	1	3,829	0	497	2	80	1,046	489	1,305,087
acaweb_fx.pg_catalog.pg_class	1	1	502	0	46	0	0	157	45	270,846
acaweb_fx.public.relevance_fibonacci_results	1	1	1,242	0	93	1	53	200	84	230,803
Total	29	25	20,948	5,816	1,184	3	849	10,309	2,082	9,292,441

Tuples removed per table

Key values

public.solr_relevance_old (33276) Main table with removed tuples on database acaweb_fx
38669 tuples Total removed

Chart
Table

		Index	Tuples			Pages
Table	Vacuums	scans	removed	remain	not yet removable	removed	remain
acaweb_fx.public.solr_relevance_old	16	16	33,276	83,081	0	0	2,763
acaweb_fx.pg_catalog.pg_attribute	2	2	3,104	21,560	0	0	520
acaweb_fx.public.relevance_keylevels_results	1	1	950	11,405	0	0	279
acaweb_fx.pg_catalog.pg_statistic	1	1	587	3,736	0	0	1,194
acaweb_fx.public.datafeeds_latestrun	4	0	196	82	26	0	64
acaweb_fx.pg_catalog.pg_class	1	1	159	1,649	0	0	150
acaweb_fx.pg_catalog.pg_type	1	1	136	1,446	0	0	39
acaweb_fx.public.relevance_fibonacci_results	1	1	131	1,151	0	0	102
acaweb_fx.pg_toast.pg_toast_2619	1	1	69	172	2	0	51
acaweb_fx.public.latest_t15_candle_view	1	1	61	14	0	0	1
Total	29	25	38,669	124,296	28	0	5,163

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	69
acaweb_fx.pg_catalog.pg_type	1	1	136
acaweb_fx.public.datafeeds_latestrun	4	0	196
acaweb_fx.pg_catalog.pg_statistic	1	1	587
acaweb_fx.pg_catalog.pg_attribute	2	2	3104
acaweb_fx.public.latest_t15_candle_view	1	1	61
acaweb_fx.public.relevance_keylevels_results	1	1	950
acaweb_fx.public.solr_relevance_old	16	16	33276
acaweb_fx.pg_catalog.pg_class	1	1	159
acaweb_fx.public.relevance_fibonacci_results	1	1	131
Total	29	25	38,669

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Jan 24	01	29	43

↑ Back to the top of the Autovacuum Activity table

Locks by types

Key values

unknown Main Lock Type
0 locks Total

Chart
Table

Type of locks

NO DATASET

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

Most frequent waiting queries (N)

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

Queries that waited the most

Rank	Wait time	Query
NO DATASET

Queries by type

Key values

49,736 Total read queries
25,514 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	49,736	29.18%
INSERT	17,108	10.04%
UPDATE	660	0.39%
DELETE	16	0.01%
COPY FROM	96	0.06%
COPY TO	26	0.02%
CTE	6,900	4.05%
DDL	16	0.01%
TCL	692	0.41%
CURSOR	0	0.00%
OTHERS	95,177	55.85%

Queries by database

Key values

unknown Main database
169,383 Requests
1h52m2s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	948	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	236	0ms
	select	102	0ms
	tcl	332	0ms
	update	36	0ms
socialmedia	Total	96	0ms
	select	93	0ms
	tcl	3	0ms
unknown	Total	169,383	1h52m2s
	copy from	16	0ms
	cte	6,796	0ms
	insert	17,108	0ms
	others	9,744	0ms
	select	49,541	0ms
	tcl	357	0ms
	update	624	0ms

Queries by user

Key values

unknown Main user
169,383 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	1,044	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	236	0ms
	select	195	0ms
	tcl	335	0ms
	update	36	0ms
unknown	Total	169,383	1h52m2s
	copy from	16	0ms
	cte	6,796	0ms
	insert	17,108	0ms
	others	9,744	0ms
	select	49,541	0ms
	tcl	357	0ms
	update	624	0ms

Duration by user

Key values

1h52m2s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	1,044	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	236	0ms
	select	195	0ms
	tcl	335	0ms
	update	36	0ms
unknown	Total	169,383	1h52m2s
	copy from	16	0ms
	cte	6,796	0ms
	insert	17,108	0ms
	others	9,744	0ms
	select	49,541	0ms
	tcl	357	0ms
	update	624	0ms

Queries by host

Key values

unknown Main host
170,427 Requests
1h52m2s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	170,427	1h52m2s
	copy from	96	0ms
	copy to	26	0ms
	cte	6,900	0ms
	ddl	16	0ms
	delete	16	0ms
	insert	17,108	0ms
	others	9,980	0ms
	select	49,736	0ms
	tcl	692	0ms
	update	660	0ms

Queries by application

Key values

unknown Main application
170,043 Requests
1h52m2s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
psql	Total	384	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	4	0ms
	select	102	0ms
	update	36	0ms
unknown	Total	170,043	1h52m2s
	copy from	16	0ms
	cte	6,796	0ms
	insert	17,108	0ms
	others	9,976	0ms
	select	49,634	0ms
	tcl	692	0ms
	update	624	0ms

Number of cancelled queries

Key values

0 per second Cancelled query Peak
2026-01-24 01:17:26 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

54,870 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	54,870	64.40%
1-5ms	26,971	31.66%
5-10ms	708	0.83%
10-25ms	547	0.64%
25-50ms	127	0.15%
50-100ms	243	0.29%
100-500ms	460	0.54%
500-1000ms	177	0.21%
1000-10000ms	878	1.03%
> 10000ms	216	0.25%

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

46

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 24	01	46	0ms	0ms

2

0ms

272

Details

0ms

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

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Jan 24	01	272	0ms	0ms

3

0ms

6

Details

0ms

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

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Jan 24	01	6	0ms	0ms

4

0ms

2,404

Details

0ms

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

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Jan 24	01	2,404	0ms	0ms

5

0ms

39

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Jan 24	01	39	0ms	0ms

6

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Jan 24	01	4	0ms	0ms

7

0ms

128

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Jan 24	01	128	0ms	0ms

8

0ms

239

Details

0ms

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

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Jan 24	01	239	0ms	0ms

9

0ms

18

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Jan 24	01	18	0ms	0ms

10

0ms

19

Details

0ms

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

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Jan 24	01	19	0ms	0ms

11

0ms

346

Details

0ms

commit;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Jan 24	01	346	0ms	0ms

12

0ms

9

Details

0ms

select psd.symbolid, psd.hourlysymbolid as intervalsymbolid, s.symbol, dtt.timezone, dtt.absolutetimezoneoffset, psh.hour as index, psh.ave, psh.stddev, ((psh.ave - psh.stddev) / ?.?) as low, ((psh.ave + psh.stddev) / ?.?) as high, ee.timezone as exchangetimezone, ee.mon_t1start as exchangestart, ee.mon_t1end as exchangeend from powerstats_symboldata psd inner join powerstats_hourly psh on psd.hourlysymbolid = psh.symbolid inner join symbols s on psh.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join mat_ps_hourly_symbolid_max_enddate e on psh.enddate = e.enddate and psh.symbolid = e.symbolid inner join exchanges ee on ee.exchange = s.exchange where psd.symbolid = ? and dtt.dayofweek = ? order by hour asc;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 24	01	9	0ms	0ms

13

0ms

399

Details

0ms

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

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Jan 24	01	399	0ms	0ms

14

0ms

239

Details

0ms

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

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Jan 24	01	239	0ms	0ms

15

0ms

18

Details

0ms

select * from ( select pricedatetime, open, high, low, close, volume, bsf from t30 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Jan 24	01	18	0ms	0ms

16

0ms

6

Details

0ms

select pid, datname, client_addr from pg_stat_activity where query ilike ? and pid <> pg_backend_pid() and state = ? and datname = ?;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Jan 24	01	6	0ms	0ms

17

0ms

2

Details

0ms

select name, value from systemsettings limit ? offset ?;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 24	01	2	0ms	0ms

18

0ms

34

Details

0ms

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

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Jan 24	01	34	0ms	0ms

19

0ms

239

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Jan 24	01	239	0ms	0ms

20

0ms

1

Details

0ms

insert into t30 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?.?, ?.?, ?, ?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 24	01	1	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

21,267

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 24	01	21,267	0ms	0ms

2

13,739

Details

0ms

select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Jan 24	01	13,739	0ms	0ms

3

7,738

Details

0ms

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

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Jan 24	01	7,738	0ms	0ms

4

4,861

Details

0ms

select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Jan 24	01	4,861	0ms	0ms

5

4,631

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Jan 24	01	4,631	0ms	0ms

6

4,619

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Jan 24	01	4,619	0ms	0ms

7

2,877

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 #7

Day	Hour	Count	Duration	Avg duration
Jan 24	01	2,877	0ms	0ms

8

2,465

Details

0ms

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

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Jan 24	01	2,465	0ms	0ms

9

2,404

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Jan 24	01	2,404	0ms	0ms

10

2,365

Details

0ms

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

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Jan 24	01	2,365	0ms	0ms

11

1,718

Details

0ms

with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ) select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as ruid, s.symbolid as sid, s.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 ? end as x3, case when (x4 != ?) then x4 else ? end as x4, case when (x5 != ?) then x5 else ? end as x5, case when (x6 != ?) then x6 else ? end as x6, case when (x7 != ?) then x7 else ? end as x7, case when (x8 != ?) then x8 else ? end as x8, errormargin as erm, breakoutprice as pe, breakoutbars as be, breakout, atbaridentified as atbar, atpriceidentified as atprice, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzos, dtt.timezone as timezone, approachingtimestamp as apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, furthestprice as fp, newlevels.filtered, a.uniquepointsvalue as upv, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from 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 inner join rar_max rm on ? = ? left outer join relevance_keylevels_results rar on a.resultuid = rar.resultuid left join lateral calc_kl_signal_filter (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Jan 24	01	1,718	0ms	0ms

12

761

Details

0ms

select datetimeupdate from latest_candle_datetime_per_receng where recognitionengine ilike ?;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 24	01	761	0ms	0ms

13

702

Details

0ms

select symbolid, pricedatetime, classname, downloadfrequency, downloadersymbol, open, high, low, close, volume, bsf, sastdatetimereceived from ( select pricedatetime, dss.classname, dss.downloadfrequency, dss.symbolid, dss.downloadersymbol, t.open, t.high, t.low, t.close, t.volume, t.bsf, t.sastdatetimereceived, row_number() over (partition by t.symbolid order by t.pricedatetime desc) as rn from t15 t, downloadersymbolsettings dss, symbols s where dss.classname = ? and dss.downloadfrequency = ? and dss.symbolid = t.symbolid and s.symbolid = dss.symbolid and dss.enabled = ? and s.deleted = ? and dss.downloadersymbol in (...) and t.pricedatetime > now() - interval ?) as ranked_candles_table where rn = ?;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Jan 24	01	702	0ms	0ms

14

448

Details

0ms

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

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Jan 24	01	448	0ms	0ms

15

399

Details

0ms

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

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Jan 24	01	399	0ms	0ms

16

399

Details

0ms

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

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Jan 24	01	399	0ms	0ms

17

352

Details

0ms

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

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 24	01	352	0ms	0ms

18

346

Details

0ms

commit;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Jan 24	01	346	0ms	0ms

19

346

Details

0ms

begin;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Jan 24	01	346	0ms	0ms

20

332

Details

0ms

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

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 24	01	332	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

46

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 24	01	46	0ms	0ms

2

0ms

272

Details

0ms

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

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Jan 24	01	272	0ms	0ms

3

0ms

6

Details

0ms

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

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Jan 24	01	6	0ms	0ms

4

0ms

2,404

Details

0ms

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

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Jan 24	01	2,404	0ms	0ms

5

0ms

39

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Jan 24	01	39	0ms	0ms

6

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Jan 24	01	4	0ms	0ms

7

0ms

128

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Jan 24	01	128	0ms	0ms

8

0ms

239

Details

0ms

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

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Jan 24	01	239	0ms	0ms

9

0ms

18

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Jan 24	01	18	0ms	0ms

10

0ms

19

Details

0ms

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

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Jan 24	01	19	0ms	0ms

11

0ms

346

Details

0ms

commit;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Jan 24	01	346	0ms	0ms

12

0ms

9

Details

0ms

select psd.symbolid, psd.hourlysymbolid as intervalsymbolid, s.symbol, dtt.timezone, dtt.absolutetimezoneoffset, psh.hour as index, psh.ave, psh.stddev, ((psh.ave - psh.stddev) / ?.?) as low, ((psh.ave + psh.stddev) / ?.?) as high, ee.timezone as exchangetimezone, ee.mon_t1start as exchangestart, ee.mon_t1end as exchangeend from powerstats_symboldata psd inner join powerstats_hourly psh on psd.hourlysymbolid = psh.symbolid inner join symbols s on psh.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join mat_ps_hourly_symbolid_max_enddate e on psh.enddate = e.enddate and psh.symbolid = e.symbolid inner join exchanges ee on ee.exchange = s.exchange where psd.symbolid = ? and dtt.dayofweek = ? order by hour asc;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 24	01	9	0ms	0ms

13

0ms

399

Details

0ms

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

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Jan 24	01	399	0ms	0ms

14

0ms

239

Details

0ms

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

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Jan 24	01	239	0ms	0ms

15

0ms

18

Details

0ms

select * from ( select pricedatetime, open, high, low, close, volume, bsf from t30 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Jan 24	01	18	0ms	0ms

16

0ms

6

Details

0ms

select pid, datname, client_addr from pg_stat_activity where query ilike ? and pid <> pg_backend_pid() and state = ? and datname = ?;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Jan 24	01	6	0ms	0ms

17

0ms

2

Details

0ms

select name, value from systemsettings limit ? offset ?;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 24	01	2	0ms	0ms

18

0ms

34

Details

0ms

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

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Jan 24	01	34	0ms	0ms

19

0ms

239

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Jan 24	01	239	0ms	0ms

20

0ms

1

Details

0ms

insert into t30 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?.?, ?.?, ?, ?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 24	01	1	0ms	0ms

Time consuming prepare


Date: 2026-01-24 01:56:41
Duration: 15ms
Database: postgres
Date: 2026-01-24 01:48:10
Duration: 16ms
Database: postgres
Date: 2026-01-24 01:11:16
Duration: 2ms
Database: postgres
Date: 2026-01-24 01:11:51
Duration: 4ms
Database: postgres
Date: 2026-01-24 01:21:00
Duration: 9ms
Database: postgres
Date: 2026-01-24 01:47:29
Duration: 5ms
Database: postgres
Date: 2026-01-24 01:11:58
Duration: 0ms
Database: postgres
Date: 2026-01-24 01:11:28
Duration: 0ms
Database: postgres
Date: 2026-01-24 01:02:21
Duration: 0ms
Database: postgres
Date: 2026-01-24 01:21:51
Duration: 6ms
Database: postgres
Date: 2026-01-24 01:27:32
Duration: 3ms
Database: postgres
Date: 2026-01-24 01:11:17
Duration: 3ms
Database: postgres
Date: 2026-01-24 01:10:05
Duration: 2ms
Database: postgres
Date: 2026-01-24 01:35:33
Duration: 0ms
Database: postgres
Date: 2026-01-24 01:46:57
Duration: 0ms
Database: postgres
Date: 2026-01-24 01:16:00
Duration: 2ms
Database: postgres
Date: 2026-01-24 01:13:17
Duration: 3ms
Database: postgres
Date: 2026-01-24 01:10:51
Duration: 0ms
Database: postgres
Date: 2026-01-24 01:21:19
Duration: 1ms
Database: postgres
Date: 2026-01-24 01:17:10
Duration: 1ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

44s638ms

5,885

Details

0ms

71ms

7ms

WITH rar_max as ( ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Jan 24	01	5,885	44s638ms	7ms

WITH rar_max as ( ;

Date: 2026-01-24 01:47:41 Duration: 71ms Database: postgres parameters: $1 = '607554524467165303', $2 = '607554524467165303', $3 = '607554524467165303'
WITH rar_max as ( ;

Date: 2026-01-24 01:47:41 Duration: 63ms Database: postgres parameters: $1 = '607554524432461303', $2 = '607554524432461303', $3 = '607554524432461303'
WITH rar_max as ( ;

Date: 2026-01-24 01:47:41 Duration: 49ms Database: postgres parameters: $1 = '607555352849541301', $2 = '607555352849541301', $3 = '607555352849541301'

2

13s652ms

19,652

Details

0ms

28ms

0ms

SELECT ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	01	19,652	13s652ms	0ms

SELECT ;

Date: 2026-01-24 01:15:55 Duration: 28ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840249418171300'
SELECT ;

Date: 2026-01-24 01:07:03 Duration: 22ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840243154175300'
SELECT ;

Date: 2026-01-24 01:16:32 Duration: 19ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840248627636300'

3

1s970ms

814

Details

1ms

5ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	01	814	1s970ms	2ms

SELECT symbolid, ;

Date: 2026-01-24 01:17:29 Duration: 5ms Database: postgres parameters: $1 = 'FPMARKETS', $2 = '15', $3 = 'ITA40'
SELECT symbolid, ;

Date: 2026-01-24 01:11:16 Duration: 5ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '60', $3 = 'AUS_200'
SELECT symbolid, ;

Date: 2026-01-24 01:17:29 Duration: 4ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'USDJPY', $4 = 'USDCZK'

4

537ms

16

Details

28ms

44ms

33ms

with sym_info as ( ;

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	01	16	537ms	33ms

with sym_info as ( ;

Date: 2026-01-24 01:21:51 Duration: 44ms Database: postgres parameters: $1 = '627', $2 = 'Forex', $3 = 'Forex', $4 = '627', $5 = 'Forex', $6 = '627', $7 = '627', $8 = 'Forex', $9 = '627'
with sym_info as ( ;

Date: 2026-01-24 01:36:54 Duration: 44ms Database: postgres parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'
with sym_info as ( ;

Date: 2026-01-24 01:21:43 Duration: 44ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'

5

528ms

21,159

Details

0ms

9ms

0ms

select 1;

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	01	21,159	528ms	0ms

select 1;

Date: 2026-01-24 01:38:06 Duration: 9ms Database: postgres
select 1;

Date: 2026-01-24 01:15:55 Duration: 7ms Database: postgres
select 1;

Date: 2026-01-24 01:56:41 Duration: 6ms Database: postgres

6

502ms

296

Details

1ms

10ms

1ms

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

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	01	296	502ms	1ms

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

Date: 2026-01-24 01:47:29 Duration: 10ms Database: postgres parameters: $1 = 'FPMARKETS'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-01-24 01:17:29 Duration: 4ms Database: postgres parameters: $1 = 'FPMARKETS'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-01-24 01:02:25 Duration: 2ms Database: postgres parameters: $1 = 'MILLENNIUMPF'

7

487ms

75

Details

4ms

17ms

6ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	01	75	487ms	6ms

WITH last_candle AS ( ;

Date: 2026-01-24 01:32:01 Duration: 17ms Database: postgres parameters: $1 = '667', $2 = '667'
WITH last_candle AS ( ;

Date: 2026-01-24 01:24:00 Duration: 10ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-01-24 01:52:00 Duration: 10ms Database: postgres parameters: $1 = '558', $2 = '558'

8

354ms

18

Details

0ms

47ms

19ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	01	18	354ms	19ms

with wh_patitioned as ( ;

Date: 2026-01-24 01:31:01 Duration: 47ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2026-01-24 01:25:01 Duration: 30ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2026-01-24 01:10:03 Duration: 30ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'

9

212ms

2,404

Details

0ms

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

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	01	2,404	212ms	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: 2026-01-24 01:11:58 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 21:00:00', $2 = '300.05', $3 = '300.33', $4 = '299.05', $5 = '299.47', $6 = '1793', $7 = '515840247899857300', $8 = '0', $9 = '2026-01-24 01:11:58.586', $10 = '2026-01-24 01:11:58.517', $11 = '300.05', $12 = '300.33', $13 = '299.05', $14 = '299.47', $15 = '1793', $16 = '0', $17 = '2026-01-24 01:11:58.586', $18 = '2026-01-24 01:11:58.517'
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: 2026-01-24 01:02:16 Duration: 0ms Database: postgres parameters: $1 = '2026-01-24 01:00:00', $2 = '32.04785', $3 = '32.263', $4 = '32.0465', $5 = '32.23545', $6 = '9898', $7 = '515840249404859300', $8 = '0', $9 = '2026-01-24 01:02:16.182', $10 = '2026-01-24 01:02:16.181', $11 = '32.04785', $12 = '32.263', $13 = '32.0465', $14 = '32.23545', $15 = '9898', $16 = '0', $17 = '2026-01-24 01:02:16.182', $18 = '2026-01-24 01:02:16.181'
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: 2026-01-24 01:02:19 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 22:00:00', $2 = '113.7445', $3 = '113.818', $4 = '113.658', $5 = '113.7655', $6 = '7401', $7 = '515840230444033300', $8 = '0', $9 = '2026-01-24 01:02:19.468', $10 = '2026-01-24 01:02:19.468', $11 = '113.7445', $12 = '113.818', $13 = '113.658', $14 = '113.7655', $15 = '7401', $16 = '0', $17 = '2026-01-24 01:02:19.468', $18 = '2026-01-24 01:02:19.468'

10

199ms

68

Details

0ms

18ms

2ms

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

Times Reported Time consuming bind #10

Day	Hour	Count	Duration	Avg duration
	01	68	199ms	2ms

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

Date: 2026-01-24 01:36:31 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: 2026-01-24 01:21:11 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: 2026-01-24 01:36:19 Duration: 18ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

11

189ms

2,465

Details

0ms

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

Times Reported Time consuming bind #11

Day	Hour	Count	Duration	Avg duration
	01	2,465	189ms	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: 2026-01-24 01:11:28 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 18:00:00', $2 = '26715.9', $3 = '26755.8', $4 = '26699.9', $5 = '26748.5', $6 = '5683', $7 = '515840247933633300', $8 = '0', $9 = '2026-01-24 01:11:28.421', $10 = '2026-01-24 01:11:28.34', $11 = '26715.9', $12 = '26755.8', $13 = '26699.9', $14 = '26748.5', $15 = '5683', $16 = '0', $17 = '2026-01-24 01:11:28.421', $18 = '2026-01-24 01:11:28.34'
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: 2026-01-24 01:02:31 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 23:00:00', $2 = '49029.9', $3 = '49030.55', $4 = '48975.4', $5 = '48987.55', $6 = '5634', $7 = '515840248000726300', $8 = '0', $9 = '2026-01-24 01:02:31.987', $10 = '2026-01-24 01:02:31.731', $11 = '49029.9', $12 = '49030.55', $13 = '48975.4', $14 = '48987.55', $15 = '5634', $16 = '0', $17 = '2026-01-24 01:02:31.987', $18 = '2026-01-24 01:02:31.731'
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: 2026-01-24 01:41:27 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 18:00:00', $2 = '26715.9', $3 = '26755.8', $4 = '26699.9', $5 = '26748.5', $6 = '5683', $7 = '515840247933633300', $8 = '0', $9 = '2026-01-24 01:41:27.318', $10 = '2026-01-24 01:41:27.247', $11 = '26715.9', $12 = '26755.8', $13 = '26699.9', $14 = '26748.5', $15 = '5683', $16 = '0', $17 = '2026-01-24 01:41:27.318', $18 = '2026-01-24 01:41:27.247'

12

133ms

2,877

Details

0ms

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

Times Reported Time consuming bind #12

Day	Hour	Count	Duration	Avg duration
	01	2,877	133ms	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: 2026-01-24 01:16:58 Duration: 0ms Database: postgres parameters: $1 = '2026-01-24 00:45:00', $2 = '1459.307', $3 = '1459.899', $4 = '1456.194', $5 = '1456.2755', $6 = '620', $7 = '515840249472960300', $8 = '0', $9 = '2026-01-24 01:16:58.914', $10 = '2026-01-24 01:16:58.722', $11 = '1459.307', $12 = '1459.899', $13 = '1456.194', $14 = '1456.2755', $15 = '620', $16 = '0', $17 = '2026-01-24 01:16:58.914', $18 = '2026-01-24 01:16:58.722'
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: 2026-01-24 01:32:19 Duration: 0ms Database: postgres parameters: $1 = '2026-01-24 02:15:00', $2 = '67.9745', $3 = '68.0125', $4 = '67.9005', $5 = '67.9645', $6 = '204', $7 = '515840249395930300', $8 = '0', $9 = '2026-01-24 01:32:19.987', $10 = '2026-01-24 01:32:19.769', $11 = '67.9745', $12 = '68.0125', $13 = '67.9005', $14 = '67.9645', $15 = '204', $16 = '0', $17 = '2026-01-24 01:32:19.987', $18 = '2026-01-24 01:32:19.769'
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: 2026-01-24 01:02:21 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 23:30:00', $2 = '49013.4', $3 = '49023.9', $4 = '49001.4', $5 = '49012.9', $6 = '323', $7 = '515840245922195300', $8 = '0', $9 = '2026-01-24 01:02:21.497', $10 = '2026-01-24 01:02:21.235', $11 = '49013.4', $12 = '49023.9', $13 = '49001.4', $14 = '49012.9', $15 = '323', $16 = '0', $17 = '2026-01-24 01:02:21.497', $18 = '2026-01-24 01:02:21.235'

13

43ms

8

Details

3ms

7ms

5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #13

Day	Hour	Count	Duration	Avg duration
	01	8	43ms	5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-24 01:00:53 Duration: 7ms Database: postgres parameters: $1 = '958', $2 = '958'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-24 01:10:51 Duration: 6ms Database: postgres parameters: $1 = '627', $2 = '627'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-24 01:01:24 Duration: 6ms Database: postgres parameters: $1 = '958', $2 = '958'

14

31ms

1

Details

31ms

with maxwhid as ( ;

Times Reported Time consuming bind #14

Day	Hour	Count	Duration	Avg duration
	01	1	31ms	31ms

with maxwhid as ( ;

Date: 2026-01-24 01:13:17 Duration: 31ms Database: postgres parameters: $1 = '335', $2 = '621', $3 = '637', $4 = '642', $5 = '660', $6 = '666', $7 = '643', $8 = '630', $9 = '680', $10 = '641', $11 = '431', $12 = '622', $13 = '489', $14 = '529', $15 = '576', $16 = '665', $17 = '667', $18 = '558', $19 = '620', $20 = '125', $21 = '488', $22 = '567', $23 = '689', $24 = '700', $25 = '758', $26 = '763', $27 = '765', $28 = '817', $29 = '914', $30 = '972'

15

22ms

4,631

Details

0ms

1ms

0ms

SET extra_float_digits = 3;

Times Reported Time consuming bind #15

Day	Hour	Count	Duration	Avg duration
	01	4,631	22ms	0ms

SET extra_float_digits = 3;

Date: 2026-01-24 01:01:25 Duration: 1ms Database: postgres
SET extra_float_digits = 3;

Date: 2026-01-24 01:52:10 Duration: 0ms Database: postgres
SET extra_float_digits = 3;

Date: 2026-01-24 01:56:11 Duration: 0ms Database: postgres

16

18ms

4,619

Details

0ms

SET application_name = 'PostgreSQL JDBC Driver';

Times Reported Time consuming bind #16

Day	Hour	Count	Duration	Avg duration
	01	4,619	18ms	0ms

SET application_name = 'PostgreSQL JDBC Driver';

Date: 2026-01-24 01:17:50 Duration: 0ms Database: postgres
SET application_name = 'PostgreSQL JDBC Driver';

Date: 2026-01-24 01:56:11 Duration: 0ms Database: postgres
SET application_name = 'PostgreSQL JDBC Driver';

Date: 2026-01-24 01:00:15 Duration: 0ms Database: postgres

17

12ms

18

Details

0ms

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

Times Reported Time consuming bind #17

Day	Hour	Count	Duration	Avg duration
	01	18	12ms	0ms

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

Date: 2026-01-24 01:31:34 Duration: 0ms Database: postgres
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;

Date: 2026-01-24 01:01:28 Duration: 0ms Database: postgres
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;

Date: 2026-01-24 01:22:23 Duration: 0ms Database: postgres

18

10ms

92

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 #18

Day	Hour	Count	Duration	Avg duration
	01	92	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: 2026-01-24 01:46:53 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 00:00:00', $2 = '247.375', $3 = '249.405', $4 = '244.7', $5 = '247.985', $6 = '10739', $7 = '515840249386902300', $8 = '0', $9 = '2026-01-24 01:46:53.355', $10 = '2026-01-24 01:46:53.355', $11 = '247.375', $12 = '249.405', $13 = '244.7', $14 = '247.985', $15 = '10739', $16 = '0', $17 = '2026-01-24 01:46:53.355', $18 = '2026-01-24 01:46:53.355'
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: 2026-01-24 01:31:58 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 00:00:00', $2 = '362.5415', $3 = '367.2305', $4 = '358.719', $5 = '360.964', $6 = '65567', $7 = '515840249404368300', $8 = '0', $9 = '2026-01-24 01:31:58.428', $10 = '2026-01-24 01:31:58.427', $11 = '362.5415', $12 = '367.2305', $13 = '358.719', $14 = '360.964', $15 = '65567', $16 = '0', $17 = '2026-01-24 01:31:58.428', $18 = '2026-01-24 01:31:58.427'
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: 2026-01-24 01:46:57 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 00:00:00', $2 = '362.5415', $3 = '367.2305', $4 = '358.719', $5 = '360.964', $6 = '65567', $7 = '515840249404368300', $8 = '0', $9 = '2026-01-24 01:46:57.079', $10 = '2026-01-24 01:46:57.078', $11 = '362.5415', $12 = '367.2305', $13 = '358.719', $14 = '360.964', $15 = '65567', $16 = '0', $17 = '2026-01-24 01:46:57.079', $18 = '2026-01-24 01:46:57.078'

19

9ms

67

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 #19

Day	Hour	Count	Duration	Avg duration
	01	67	9ms	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: 2026-01-24 01:35:33 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 16:00:00', $2 = '53330', $3 = '53580', $4 = '52885', $5 = '52915', $6 = '4598', $7 = '515840230561612300', $8 = '0', $9 = '2026-01-24 01:35:33.074', $10 = '2026-01-24 01:35:33.074', $11 = '53330', $12 = '53580', $13 = '52885', $14 = '52915', $15 = '4598', $16 = '0', $17 = '2026-01-24 01:35:33.074', $18 = '2026-01-24 01:35:33.074'
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: 2026-01-24 01:31:24 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 16:00:00', $2 = '53330', $3 = '53580', $4 = '52885', $5 = '52915', $6 = '4598', $7 = '515840230561612300', $8 = '0', $9 = '2026-01-24 01:31:24.638', $10 = '2026-01-24 01:31:24.638', $11 = '53330', $12 = '53580', $13 = '52885', $14 = '52915', $15 = '4598', $16 = '0', $17 = '2026-01-24 01:31:24.638', $18 = '2026-01-24 01:31:24.638'
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: 2026-01-24 01:31:58 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 20:00:00', $2 = '363.0365', $3 = '367.2305', $4 = '358.719', $5 = '360.964', $6 = '35593', $7 = '515840249404204300', $8 = '0', $9 = '2026-01-24 01:31:58.435', $10 = '2026-01-24 01:31:58.22', $11 = '363.0365', $12 = '367.2305', $13 = '358.719', $14 = '360.964', $15 = '35593', $16 = '0', $17 = '2026-01-24 01:31:58.435', $18 = '2026-01-24 01:31:58.22'

20

9ms

10

Details

0ms

1ms

0ms

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

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	01	10	9ms	0ms

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

Date: 2026-01-24 01:13:53 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'ETHUSD', $3 = '558'
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2026-01-24 01:35:46 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'BTCUSD', $3 = '558'
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2026-01-24 01:20:46 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'BTCUSD', $3 = '558'

Log levels

Key values

360,284 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	480	0.13%
DETAIL	70,858	19.67%
ERROR	34	0.01%
HINT	34	0.01%
LOG	288,332	80.03%
STATEMENT	546	0.15%

Events distribution

Key values

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

Most Frequent Errors/Events

Key values

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

Rank

Times reported

Error

1

34

Details

ERROR: function fixcandlegaps(...) is not unique

Times Reported Most Frequent Error / Event #1

Day	Hour	Count
Jan 24	01	34

ERROR: function fixcandlegaps(unknown, boolean) is not unique at character 8

Global information

Overview

Global Stats

SQL Traffic

Key values

SELECT Traffic

Key values

INSERT/UPDATE/DELETE Traffic

Key values

Queries duration

Key values

Prepared queries ratio

Key values

General Activity

Connections

Established Connections

Key values

Connections per database

Key values

Connections per user

Key values

Connections per host

Key values

Sessions

Simultaneous sessions

Key values

Histogram of session times

Key values

Sessions per database

Key values

Sessions per user

Key values

Sessions per host

Key values

Sessions per application

Key values

Checkpoints / Restartpoints

Checkpoints Buffers

Key values

Checkpoints Wal files

Key values

Checkpoints distance

Key values

Checkpoints Activity

Checkpoint causes

Key values

Temporary Files

Size of temporary files

Key values

Number of temporary files

Key values

Temporary Files Activity

Queries generating the most temporary files (N)

Queries generating the largest temporary files

Vacuums

Vacuums / Analyzes Distribution

Key values

Analyzes per table

Key values

Vacuums per table

Key values

Tuples removed per table

Key values

Pages removed per table

Key values

Pages removed per tables

Autovacuum Activity

Locks

Locks by types

Key values

Type of locks

Most frequent waiting queries (N)

Queries that waited the most

Queries

Queries by type

Key values

Queries by database

Key values

Queries by user

Key values