pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Fri Jan 23 07:59:57 2026
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-01-23_090000.log
Parsed 2,342,204 log entries in 56s
Log start from 2026-01-23 09:00:00 to 2026-01-23 09:59:55

Global Stats

270 Number of unique normalized queries
260,935 Number of queries
1h24m28s Total query duration
2026-01-23 09:00:00 First query
2026-01-23 09:59:55 Last query
4,196 queries/s at 2026-01-23 09:11:02 Query peak

1h24m28s Total query duration
6s228ms Prepare/parse total duration
41s872ms Bind total duration
1h23m40s Execute total duration

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

40 Total number of automatic vacuums
52 Total number of automatic analyzes

877 Number temporary file
594.98 MiB Max size of temporary file
6.70 MiB Average size of temporary file

2,856 Total number of sessions
13 sessions at 2026-01-23 09:58:48 Session peak
17d22h29m58s Total duration of sessions
9m2s Average duration of sessions
91 Average queries per session
1s774ms Average queries duration per session
9m Average idle time per session

2,850 Total number of connections
34 connections/s at 2026-01-23 09:06:01 Connection peak
4 Total number of databases

SQL Traffic

Key values

4,196 queries/s Query Peak
2026-01-23 09:11:02 Date

SELECT Traffic

Key values

2,095 queries/s Query Peak
2026-01-23 09:11:02 Date

INSERT/UPDATE/DELETE Traffic

Key values

158 queries/s Query Peak
2026-01-23 09:23:50 Date

Queries duration

Key values

1h24m28s 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 23	09	260,935	0ms	31s661ms	19ms	3m11s	3m39s	4m39s

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Jan 23	09	83,582	26	0ms	0ms	0ms	0ms

Day	Hour	INSERT	UPDATE	DELETE	COPY FROM	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Jan 23	09	30,485	3,119	16	96	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Jan 23	09	19,654	100,242	5.10	15.56%

Day	Hour	Count	Average / Second
Jan 23	09	2,850	0.79/s

Day	Hour	Count	Average Duration	Average idle time
Jan 23	09	2,856	9m2s	9m

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Established Connections

Key values

34 connections Connection Peak
2026-01-23 09:06:01 Date

Connections per database

Key values

acaweb_fx Main Database
2,850 connections Total

Chart
Table

Database	User	Count
acaweb_fx		2,755
	postgres	2,367
	psql	388
postgres		1
	pgAdmin 4 - DB:postgres	1
socialmedia		94
	postgres	94

Connections per user

Key values

postgres Main User
2,850 connections Total

Chart
Table

User	Count
pgAdmin 4 - DB:postgres	1
postgres	2,461
psql	388

Connections per host

Key values

192.168.4.142 Main host with 1192 connections
2,850 Total connections

Chart
Table

Host	Count
104.30.164.187	1
127.0.0.1	114
182.165.1.54	2
192.168.0.114	4
192.168.0.216	101
192.168.0.74	106
192.168.0.84	2
192.168.1.131	2
192.168.1.145	112
192.168.1.15	94
192.168.1.20	129
192.168.1.238	4
192.168.1.239	2
192.168.1.90	90
192.168.2.126	72
192.168.2.182	12
192.168.2.82	48
192.168.3.199	36
192.168.4.142	1,192
192.168.4.150	10
192.168.4.222	1
192.168.4.238	12
192.168.4.33	91
192.168.4.39	4
192.168.4.59	1
192.168.4.68	4
192.168.4.98	330
[local]	274

Simultaneous sessions

Key values

13 sessions Session Peak
2026-01-23 09:58:48 Date

Histogram of session times

Key values

2,245 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	2,245	78.61%
500ms-1s	173	6.06%
1s-30s	306	10.71%
30s-1m	6	0.21%
1m-10m	36	1.26%
10m-30m	56	1.96%
30m-1h	5	0.18%
1h-8h	10	0.35%
> 8h	19	0.67%

Sessions per database

Key values

acaweb_fx Main Database
2,856 sessions Total

Chart
Table

Database	User	Count	Total Duration
acaweb_fx	2,759	17d21h16m26s	9m20s
postgres	2	40m56s	20m28s
socialmedia	95	32m35s	20s580ms

Sessions per user

Key values

postgres Main User
2,856 sessions Total

Chart
Table

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

Sessions per host

Key values

192.168.4.142 Main Host
2,856 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
104.30.164.187	2	40m56s	20m28s
127.0.0.1	114	13s260ms	116ms
182.165.1.54	2	23h16m54s	11h38m27s
192.168.0.114	5	26m17s	5m15s
192.168.0.171	3	2d16h21m45s	21h27m15s
192.168.0.216	101	1m2s	614ms
192.168.0.74	102	1d1h53m55s	15m14s
192.168.0.84	2	23h59m18s	11h59m39s
192.168.1.131	2	23h59m17s	11h59m38s
192.168.1.145	113	3d17m54s	38m23s
192.168.1.15	94	5h21m48s	3m25s
192.168.1.154	3	2d16h22m2s	21h27m20s
192.168.1.20	130	3d15h22m39s	40m19s
192.168.1.238	4	17h39m39s	4h24m54s
192.168.1.239	2	12ms	6ms
192.168.1.90	90	33s944ms	377ms
192.168.2.126	72	18s239ms	253ms
192.168.2.182	12	968ms	80ms
192.168.2.82	48	30s67ms	626ms
192.168.3.199	36	1s275ms	35ms
192.168.4.142	1,192	9m1s	454ms
192.168.4.150	10	20h19m35s	2h1m57s
192.168.4.222	1	45s659ms	45s659ms
192.168.4.238	12	15s539ms	1s294ms
192.168.4.33	91	11m17s	7s449ms
192.168.4.39	4	34ms	8ms
192.168.4.59	1	152ms	152ms
192.168.4.68	4	25s491ms	6s372ms
192.168.4.98	330	17s534ms	53ms
[local]	274	3m8s	687ms

Sessions per application

Key values

unknown Main Host
2,856 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	2,856	17d22h29m58s	9m2s

Checkpoints Buffers

Key values

12,556 buffers Checkpoint Peak
2026-01-23 09:06:55 Date
209.911 seconds Highest write time
0.134 seconds Sync time

Checkpoints Wal files

Key values

6 files Wal files usage Peak
2026-01-23 09:06:55 Date

Checkpoints distance

Key values

205.21 Mo Distance Peak
2026-01-23 09:06:55 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Jan 23	09	43,297	1,819.963s	0.183s	1,820.441s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Jan 23	09	0	0	24	1,871	0.120s	0.001s

Day	Hour	Count	Avg time (sec)
Jan 23	09	0	0s

Day	Hour	Mean distance	Mean estimate
Jan 23	09	33,189.25 kB	75,980.92 kB

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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

594.98 MiB Temp Files size Peak
2026-01-23 09:14:20 Date

Number of temporary files

Key values

62 per second Temp Files Peak
2026-01-23 09:02:16 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Jan 23	09	877	5.74 GiB	6.70 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	27	1.67 GiB	3.95 MiB	127.95 MiB	63.17 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = ? ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?; with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; Date: 2026-01-23 09:00:08 Duration: 0ms
2	16	737.25 MiB	46.08 MiB	46.08 MiB	46.08 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: 2026-01-23 09:01:13 Duration: 0ms
3	16	1.22 GiB	78.19 MiB	78.19 MiB	78.19 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: 2026-01-23 09:01:16 Duration: 0ms
4	8	1.04 GiB	132.92 MiB	132.97 MiB	132.94 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2026-01-23 09:02:23 Duration: 0ms
5	8	24.35 MiB	3.04 MiB	3.05 MiB	3.04 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: 2026-01-23 09:06:58 Duration: 0ms
6	4	373.56 MiB	93.34 MiB	93.44 MiB	93.39 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2026-01-23 09:02:06 Duration: 0ms
7	3	22.44 MiB	7.46 MiB	7.49 MiB	7.48 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: 2026-01-23 09:01:00 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	132.97 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-23 09:02:23 ]
2	132.96 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-23 09:47:19 ]
3	132.95 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-23 09:32:18 ]
4	132.95 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-23 09:50:32 ]
5	132.94 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-23 09:35:32 ]
6	132.93 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-23 09:17:17 ]
7	132.93 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-23 09:05:32 ]
8	132.92 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-23 09:20:34 ]
9	127.95 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-23 09:30:05 ]
10	109.55 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-23 09:00:05 ]
11	101.11 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-23 09:40:04 ]
12	100.02 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-23 09:10:04 ]
13	98.32 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-23 09:10:05 ]
14	93.44 MiB	select updateageforrelevantresults (); [ Date: 2026-01-23 09:02:06 ]
15	93.40 MiB	select updateageforrelevantresults (); [ Date: 2026-01-23 09:32:06 ]
16	93.38 MiB	select updateageforrelevantresults (); [ Date: 2026-01-23 09:47:07 ]
17	93.34 MiB	select updateageforrelevantresults (); [ Date: 2026-01-23 09:17:05 ]
18	89.30 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-23 09:20:04 ]
19	89.03 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-23 09:50:04 ]
20	87.39 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-23 09:30:05 ]

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)
52 analyzes Total

Chart
Table

Table	Number of analyzes
acaweb_fx.public.solr_relevance_old	16
acaweb_fx.public.datafeeds_latestrun	4
acaweb_fx.pg_catalog.pg_attribute	4
acaweb_fx.public.relevance_keylevels_results	4
acaweb_fx.pg_catalog.pg_class	4
acaweb_fx.public.relevance_autochartist_results	4
acaweb_fx.public.relevance_fibonacci_results	4
acaweb_fx.pg_catalog.pg_type	3
acaweb_fx.public.latest_t15_candle_view	2
acaweb_fx.pg_catalog.pg_depend	2
acaweb_fx.pg_catalog.pg_index	1
acaweb_fx.public.autochartist_symbolupdates	1
acaweb_fx.public.relevance_consecutivecandles_results	1
acaweb_fx.public.symbollatestupdatetime	1
acaweb_fx.public.latest_candle_datetime_per_receng	1
Total	52

Vacuums per table

Key values

public.solr_relevance_old (18) Main table vacuumed on database acaweb_fx
40 vacuums Total

Chart
Table

		Index	Buffer usage			Skipped		WAL usage
Table	Vacuums	scans	hits	misses	dirtied	pins	frozen	records	full page	bytes
acaweb_fx.public.solr_relevance_old	18	17	12,930	0	62	0	58	8,190	559	3,233,950
acaweb_fx.public.datafeeds_latestrun	4	0	482	0	14	0	0	60	12	58,426
acaweb_fx.pg_toast.pg_toast_2619	2	2	278	0	54	0	0	201	52	195,006
acaweb_fx.pg_catalog.pg_attribute	2	2	1,601	0	330	0	134	735	262	1,598,684
acaweb_fx.public.relevance_keylevels_results	2	2	7,686	0	257	2	214	1,872	241	655,187
acaweb_fx.public.relevance_autochartist_results	2	2	6,882	0	163	0	494	1,396	149	422,523
acaweb_fx.public.relevance_fibonacci_results	2	2	2,523	0	43	0	107	414	28	96,498
acaweb_fx.pg_catalog.pg_index	1	1	91	0	11	0	0	29	10	75,343
acaweb_fx.pg_catalog.pg_type	1	1	135	0	21	0	0	55	13	92,244
acaweb_fx.public.autochartist_symbolupdates	1	1	21,886	0	3,640	1	38,345	6,898	3,583	1,485,655
acaweb_fx.public.solr_imports	1	1	52	0	3	0	0	6	2	14,131
acaweb_fx.pg_catalog.pg_statistic	1	1	1,038	0	156	0	582	497	150	582,180
acaweb_fx.pg_catalog.pg_depend	1	1	371	0	80	0	59	164	66	349,835
acaweb_fx.public.latest_t15_candle_view	1	1	93	0	1	0	0	6	1	9,067
acaweb_fx.pg_catalog.pg_class	1	1	470	0	62	0	0	151	53	292,096
Total	40	35	56,518	47,088	4,897	3	39,993	20,674	5,181	9,160,825

Tuples removed per table

Key values

public.solr_relevance_old (33968) Main table with removed tuples on database acaweb_fx
46507 tuples Total removed

Chart
Table

		Index	Tuples			Pages
Table	Vacuums	scans	removed	remain	not yet removable	removed	remain
acaweb_fx.public.solr_relevance_old	18	17	33,968	102,264	7,156	0	3,230
acaweb_fx.public.autochartist_symbolupdates	1	1	5,290	47,727	15	0	40,691
acaweb_fx.pg_catalog.pg_attribute	2	2	2,721	21,719	137	0	519
acaweb_fx.public.relevance_keylevels_results	2	2	1,321	24,041	0	0	558
acaweb_fx.public.relevance_autochartist_results	2	2	1,145	16,374	0	0	760
acaweb_fx.pg_catalog.pg_statistic	1	1	533	3,711	0	0	1,194
acaweb_fx.pg_catalog.pg_depend	1	1	430	14,650	0	0	135
acaweb_fx.public.relevance_fibonacci_results	2	2	273	2,954	0	0	204
acaweb_fx.public.datafeeds_latestrun	4	0	239	56	0	0	64
acaweb_fx.pg_catalog.pg_type	1	1	158	1,446	0	0	39
acaweb_fx.pg_toast.pg_toast_2619	2	2	151	351	11	0	104
acaweb_fx.pg_catalog.pg_class	1	1	150	1,649	0	0	150
acaweb_fx.public.latest_t15_candle_view	1	1	61	14	0	0	1
acaweb_fx.public.solr_imports	1	1	51	1	0	0	2
acaweb_fx.pg_catalog.pg_index	1	1	16	815	2	0	22
Total	40	35	46,507	237,772	7,321	0	47,673

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	2	2	151
acaweb_fx.pg_catalog.pg_index	1	1	16
acaweb_fx.pg_catalog.pg_type	1	1	158
acaweb_fx.public.autochartist_symbolupdates	1	1	5290
acaweb_fx.public.datafeeds_latestrun	4	0	239
acaweb_fx.public.solr_imports	1	1	51
acaweb_fx.pg_catalog.pg_statistic	1	1	533
acaweb_fx.pg_catalog.pg_attribute	2	2	2721
acaweb_fx.pg_catalog.pg_depend	1	1	430
acaweb_fx.public.latest_t15_candle_view	1	1	61
acaweb_fx.public.relevance_keylevels_results	2	2	1321
acaweb_fx.pg_catalog.pg_class	1	1	150
acaweb_fx.public.solr_relevance_old	18	17	33968
acaweb_fx.public.relevance_autochartist_results	2	2	1145
acaweb_fx.public.relevance_fibonacci_results	2	2	273
Total	40	35	46,507

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Jan 23	09	40	52

↑ 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

83,582 Total read queries
42,768 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	83,582	32.03%
INSERT	30,485	11.68%
UPDATE	3,119	1.20%
DELETE	16	0.01%
COPY FROM	96	0.04%
COPY TO	26	0.01%
CTE	8,308	3.18%
DDL	16	0.01%
TCL	702	0.27%
CURSOR	0	0.00%
OTHERS	134,585	51.58%

Queries by database

Key values

unknown Main database
259,922 Requests
1h23m40s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	918	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	203	0ms
	select	102	0ms
	tcl	331	0ms
	update	40	0ms
postgres	Total	1	0ms
	others	1	0ms
socialmedia	Total	94	0ms
	select	91	0ms
	tcl	3	0ms
unknown	Total	259,922	1h23m40s
	copy from	16	0ms
	cte	8,204	0ms
	insert	30,485	0ms
	others	3,930	0ms
	select	83,389	0ms
	tcl	368	0ms
	update	3,079	0ms

Queries by user

Key values

unknown Main user
259,922 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	1,013	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	204	0ms
	select	193	0ms
	tcl	334	0ms
	update	40	0ms
unknown	Total	259,922	1h23m40s
	copy from	16	0ms
	cte	8,204	0ms
	insert	30,485	0ms
	others	3,930	0ms
	select	83,389	0ms
	tcl	368	0ms
	update	3,079	0ms

Duration by user

Key values

1h23m40s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	1,013	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	204	0ms
	select	193	0ms
	tcl	334	0ms
	update	40	0ms
unknown	Total	259,922	1h23m40s
	copy from	16	0ms
	cte	8,204	0ms
	insert	30,485	0ms
	others	3,930	0ms
	select	83,389	0ms
	tcl	368	0ms
	update	3,079	0ms

Queries by host

Key values

unknown Main host
260,935 Requests
1h23m40s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	260,935	1h23m40s
	copy from	96	0ms
	copy to	26	0ms
	cte	8,308	0ms
	ddl	16	0ms
	delete	16	0ms
	insert	30,485	0ms
	others	4,134	0ms
	select	83,582	0ms
	tcl	702	0ms
	update	3,119	0ms

Queries by application

Key values

unknown Main application
260,546 Requests
1h23m40s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
pgAdmin 4 - DB:postgres	Total	1	0ms
	others	1	0ms
psql	Total	388	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	40	0ms
unknown	Total	260,546	1h23m40s
	copy from	16	0ms
	cte	8,204	0ms
	insert	30,485	0ms
	others	4,129	0ms
	select	83,480	0ms
	tcl	702	0ms
	update	3,079	0ms

Number of cancelled queries

Key values

0 per second Cancelled query Peak
2026-01-23 09:33:21 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

96,676 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	96,676	74.11%
1-5ms	29,552	22.65%
5-10ms	1,865	1.43%
10-25ms	647	0.50%
25-50ms	282	0.22%
50-100ms	201	0.15%
100-500ms	340	0.26%
500-1000ms	116	0.09%
1000-10000ms	611	0.47%
> 10000ms	161	0.12%

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

4

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 #1

Day	Hour	Count	Duration	Avg duration
Jan 23	09	4	0ms	0ms

2

0ms

37

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 #2

Day	Hour	Count	Duration	Avg duration
Jan 23	09	37	0ms	0ms

3

0ms

155

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 23	09	155	0ms	0ms

4

0ms

2,168

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 23	09	2,168	0ms	0ms

5

0ms

48

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Jan 23	09	48	0ms	0ms

6

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Jan 23	09	4	0ms	0ms

7

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 #7

Day	Hour	Count	Duration	Avg duration
Jan 23	09	18	0ms	0ms

8

0ms

351

Details

0ms

commit;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Jan 23	09	351	0ms	0ms

9

0ms

255

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 #9

Day	Hour	Count	Duration	Avg duration
Jan 23	09	255	0ms	0ms

10

0ms

240

Details

0ms

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

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Jan 23	09	240	0ms	0ms

11

0ms

240

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Jan 23	09	240	0ms	0ms

12

0ms

5

Details

0ms

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

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 23	09	5	0ms	0ms

13

0ms

1

Details

0ms

insert into t15 (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 #13

Day	Hour	Count	Duration	Avg duration
Jan 23	09	1	0ms	0ms

14

0ms

8

Details

0ms

select updatedatafeedslatestrun (?);

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Jan 23	09	8	0ms	0ms

15

0ms

2

Details

0ms

insert into t15 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?.?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing; insert into t15 (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 #15

Day	Hour	Count	Duration	Avg duration
Jan 23	09	2	0ms	0ms

16

0ms

6

Details

0ms

insert into t15 (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 #16

Day	Hour	Count	Duration	Avg duration
Jan 23	09	6	0ms	0ms

17

0ms

1

Details

0ms

insert into t15 (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 #17

Day	Hour	Count	Duration	Avg duration
Jan 23	09	1	0ms	0ms

18

0ms

232

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 #18

Day	Hour	Count	Duration	Avg duration
Jan 23	09	232	0ms	0ms

19

0ms

1

Details

0ms

insert into t15 (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 #19

Day	Hour	Count	Duration	Avg duration
Jan 23	09	1	0ms	0ms

20

0ms

37

Details

0ms

select distinct classname, to_char(created_datetime, ?), to_char(cleared_datetime, ?), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = ? or cleared_datetime > current_timestamp - interval ?) order by created_datetime desc;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 23	09	37	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

36,953

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 23	09	36,953	0ms	0ms

2

9,313

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 23	09	9,313	0ms	0ms

3

7,952

Details

0ms

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

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Jan 23	09	7,952	0ms	0ms

4

7,862

Details

0ms

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

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Jan 23	09	7,862	0ms	0ms

5

6,556

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Jan 23	09	6,556	0ms	0ms

6

5,787

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 #6

Day	Hour	Count	Duration	Avg duration
Jan 23	09	5,787	0ms	0ms

7

4,479

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 #7

Day	Hour	Count	Duration	Avg duration
Jan 23	09	4,479	0ms	0ms

8

3,902

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 #8

Day	Hour	Count	Duration	Avg duration
Jan 23	09	3,902	0ms	0ms

9

3,576

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Jan 23	09	3,576	0ms	0ms

10

3,310

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 #10

Day	Hour	Count	Duration	Avg duration
Jan 23	09	3,310	0ms	0ms

11

2,580

Details

0ms

insert into keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errormargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestprice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) values (?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?, ?, ?.?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?.?, ?::timestamp without time zone, ?, ?.?, ?.?, ?, ?, ?.?, ?.?, ?::timestamp without time zone, ?, ?, ?.?, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Jan 23	09	2,580	0ms	0ms

12

2,524

Details

0ms

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

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 23	09	2,524	0ms	0ms

13

2,386

Details

0ms

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

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Jan 23	09	2,386	0ms	0ms

14

2,168

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 #14

Day	Hour	Count	Duration	Avg duration
Jan 23	09	2,168	0ms	0ms

15

1,747

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Jan 23	09	1,747	0ms	0ms

16

1,717

Details

0ms

select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars as length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternstartprice, resy1, supporty1, dtt.timezone, cps.pip, newlevels.profit 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 left join currencypips cps on cps.symbol = s.symbol left join lateral calc_cp_signal (a.resultuid) newlevels on true where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Jan 23	09	1,717	0ms	0ms

17

1,712

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 23	09	1,712	0ms	0ms

18

1,520

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 #18

Day	Hour	Count	Duration	Avg duration
Jan 23	09	1,520	0ms	0ms

19

1,051

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 #19

Day	Hour	Count	Duration	Avg duration
Jan 23	09	1,051	0ms	0ms

20

1,026

Details

0ms

insert into authenticationlog (username, password, brokerid, authclass, attemptdatetime, success, fingerprint, accounttype) values (?, ?, ?, ?, current_timestamp, ?, ?, ?);

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 23	09	1,026	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

4

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 #1

Day	Hour	Count	Duration	Avg duration
Jan 23	09	4	0ms	0ms

2

0ms

37

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 #2

Day	Hour	Count	Duration	Avg duration
Jan 23	09	37	0ms	0ms

3

0ms

155

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 23	09	155	0ms	0ms

4

0ms

2,168

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 23	09	2,168	0ms	0ms

5

0ms

48

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Jan 23	09	48	0ms	0ms

6

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Jan 23	09	4	0ms	0ms

7

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 #7

Day	Hour	Count	Duration	Avg duration
Jan 23	09	18	0ms	0ms

8

0ms

351

Details

0ms

commit;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Jan 23	09	351	0ms	0ms

9

0ms

255

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 #9

Day	Hour	Count	Duration	Avg duration
Jan 23	09	255	0ms	0ms

10

0ms

240

Details

0ms

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

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Jan 23	09	240	0ms	0ms

11

0ms

240

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Jan 23	09	240	0ms	0ms

12

0ms

5

Details

0ms

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

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 23	09	5	0ms	0ms

13

0ms

1

Details

0ms

insert into t15 (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 #13

Day	Hour	Count	Duration	Avg duration
Jan 23	09	1	0ms	0ms

14

0ms

8

Details

0ms

select updatedatafeedslatestrun (?);

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Jan 23	09	8	0ms	0ms

15

0ms

2

Details

0ms

insert into t15 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?.?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing; insert into t15 (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 #15

Day	Hour	Count	Duration	Avg duration
Jan 23	09	2	0ms	0ms

16

0ms

6

Details

0ms

insert into t15 (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 #16

Day	Hour	Count	Duration	Avg duration
Jan 23	09	6	0ms	0ms

17

0ms

1

Details

0ms

insert into t15 (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 #17

Day	Hour	Count	Duration	Avg duration
Jan 23	09	1	0ms	0ms

18

0ms

232

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 #18

Day	Hour	Count	Duration	Avg duration
Jan 23	09	232	0ms	0ms

19

0ms

1

Details

0ms

insert into t15 (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 #19

Day	Hour	Count	Duration	Avg duration
Jan 23	09	1	0ms	0ms

20

0ms

37

Details

0ms

select distinct classname, to_char(created_datetime, ?), to_char(cleared_datetime, ?), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = ? or cleared_datetime > current_timestamp - interval ?) order by created_datetime desc;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 23	09	37	0ms	0ms

Time consuming prepare


Date: 2026-01-23 09:46:16
Duration: 14ms
Database: postgres
Date: 2026-01-23 09:02:10
Duration: 3ms
Database: postgres
Date: 2026-01-23 09:32:47
Duration: 7ms
Database: postgres
Date: 2026-01-23 09:15:53
Duration: 1ms
Database: postgres
Date: 2026-01-23 09:41:10
Duration: 0ms
Database: postgres
Date: 2026-01-23 09:02:05
Duration: 3ms
Database: postgres
Date: 2026-01-23 09:02:58
Duration: 0ms
Database: postgres
Date: 2026-01-23 09:30:56
Duration: 0ms
Database: postgres
Date: 2026-01-23 09:10:57
Duration: 0ms
Database: postgres
Date: 2026-01-23 09:12:00
Duration: 5ms
Database: postgres
Date: 2026-01-23 09:21:39
Duration: 5ms
Database: postgres
Date: 2026-01-23 09:40:00
Duration: 1ms
Database: postgres
Date: 2026-01-23 09:51:01
Duration: 3ms
Database: postgres
Date: 2026-01-23 09:56:32
Duration: 1ms
Database: postgres
Date: 2026-01-23 09:00:56
Duration: 6ms
Database: postgres
Date: 2026-01-23 09:10:57
Duration: 2ms
Database: postgres
Date: 2026-01-23 09:56:32
Duration: 1ms
Database: postgres
Date: 2026-01-23 09:13:39
Duration: 0ms
Database: postgres
Date: 2026-01-23 09:15:57
Duration: 0ms
Database: postgres
Date: 2026-01-23 09:16:04
Duration: 2ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

24s46ms

7,276

Details

0ms

43ms

3ms

WITH rar_max as ( ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Jan 23	09	7,276	24s46ms	3ms

WITH rar_max as ( ;

Date: 2026-01-23 09:46:17 Duration: 43ms Database: postgres parameters: $1 = 't', $2 = '627', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '213', $14 = '#ADBE', $15 = '#ALVG', $16 = '#AMZN', $17 = '#APPL', $18 = '#BA', $19 = '#BABA', $20 = '#BAYGn', $21 = '#BMWG', $22 = '#BNPP', $23 = '#CAT', $24 = '#CBKG', $25 = '#DAIGn', $26 = '#DIS', $27 = '#EA', $28 = '#FB', $29 = '#FDX', $30 = '#GE', $31 = '#GM', $32 = '#GOOGL', $33 = '#GS', $34 = '#INTC', $35 = '#JPM', $36 = '#KO', $37 = '#META', $38 = '#MSFT', $39 = '#NFLX', $40 = '#TSLA', $41 = '#VOWG', $42 = '#WMT', $43 = '#XOM', $44 = 'AUDCAD', $45 = 'AUDCHF', $46 = 'AUDJPY', $47 = 'AUDNZD', $48 = 'AUDUSD', $49 = 'AUS_200', $50 = 'BTCEUR', $51 = 'BTCGBP', $52 = 'BTCUSD', $53 = 'CADCHF', $54 = 'CADJPY', $55 = 'CHFJPY', $56 = 'CL_BRENT', $57 = 'DASHUSD', $58 = 'EOSUSD', $59 = 'ESP_35', $60 = 'ETHEUR', $61 = 'ETHGBP', $62 = 'ETHUSD', $63 = 'EURAUD', $64 = 'EURCAD', $65 = 'EURCHF', $66 = 'EURGBP', $67 = 'EURJPY', $68 = 'EURMXN', $69 = 'EURNOK', $70 = 'EURNZD', $71 = 'EURPLN', $72 = 'EURSEK', $73 = 'EURTRY', $74 = 'EURUSD', $75 = 'EUR_50', $76 = 'FRA_40', $77 = 'GBPAUD', $78 = 'GBPCAD', $79 = 'GBPCHF', $80 = 'GBPJPY', $81 = 'GBPNZD', $82 = 'GBPUSD', $83 = 'GBPZAR', $84 = 'GBR_100', $85 = 'HKDJPY', $86 = 'HKG_50', $87 = 'IOTAUSD', $88 = 'LTCEUR', $89 = 'LTCUSD', $90 = 'NAS100', $91 = 'NEOUSD', $92 = 'NOKJPY', $93 = 'NZDCAD', $94 = 'NZDCHF', $95 = 'NZDJPY', $96 = 'NZDUSD', $97 = 'OMGUSD', $98 = 'SPX500', $99 = 'TRXUSD', $100 = 'US30', $101 = 'USDCAD', $102 = 'USDCHF', $103 = 'USDCNH', $104 = 'USDDKK', $105 = 'USDJPY', $106 = 'USDMXN', $107 = 'USDNOK', $108 = 'USDPLN', $109 = 'USDSEK', $110 = 'USDSGD', $111 = 'USDZAR', $112 = 'USOIL', $113 = 'XAGUSD', $114 = 'XAUEUR', $115 = 'XAUUSD', $116 = 'XMRUSD', $117 = 'XPTUSD', $118 = 'XRPUSD', $119 = 'ZARJPY', $120 = 'ZECUSD', $121 = 'AUDCAD', $122 = 'AUDCHF', $123 = 'AUDJPY', $124 = 'AUDNZD', $125 = 'AUDUSD', $126 = 'CADCHF', $127 = 'CADJPY', $128 = 'CHFJPY', $129 = 'EURAUD', $130 = 'EURCAD', $131 = 'EURCHF', $132 = 'EURGBP', $133 = 'EURJPY', $134 = 'EURMXN', $135 = 'EURNOK', $136 = 'EURNZD', $137 = 'EURPLN', $138 = 'EURSEK', $139 = 'EURTRY', $140 = 'EURUSD', $141 = 'GBPAUD', $142 = 'GBPCAD', $143 = 'GBPCHF', $144 = 'GBPJPY', $145 = 'GBPNZD', $146 = 'GBPUSD', $147 = 'GBPZAR', $148 = 'HKDJPY', $149 = 'NOKJPY', $150 = 'NZDCAD', $151 = 'NZDCHF', $152 = 'NZDJPY', $153 = 'NZDUSD', $154 = 'USDCAD', $155 = 'USDCHF', $156 = 'USDCNH', $157 = 'USDDKK', $158 = 'USDJPY', $159 = 'USDMXN', $160 = 'USDNOK', $161 = 'USDPLN', $162 = 'USDSEK', $163 = 'USDSGD', $164 = 'USDZAR', $165 = 'ZARJPY', $166 = 'BTCEUR', $167 = 'BTCGBP', $168 = 'BTCUSD', $169 = 'DASHUSD', $170 = 'EOSUSD', $171 = 'ETHEUR', $172 = 'ETHGBP', $173 = 'ETHUSD', $174 = 'IOTAUSD', $175 = 'LTCEUR', $176 = 'LTCUSD', $177 = 'NEOUSD', $178 = 'OMGUSD', $179 = 'TRXUSD', $180 = 'XMRUSD', $181 = 'XRPUSD', $182 = 'ZECUSD', $183 = 'XAGUSD', $184 = 'XAUEUR', $185 = 'XAUUSD', $186 = 'XPTUSD', $187 = 'CL_BRENT', $188 = 'USOIL', $189 = '#ALVG', $190 = '#BAYGn', $191 = '#BMWG', $192 = '#BNPP', $193 = '#CBKG', $194 = '#DAIGn', $195 = '#VOWG', $196 = 'AUS_200', $197 = 'ESP_35', $198 = 'EUR_50', $199 = 'FRA_40', $200 = 'GBR_100', $201 = 'HKG_50', $202 = 'NAS100', $203 = 'SPX500', $204 = 'US30', $205 = '#ADBE', $206 = '#AMZN', $207 = '#APPL', $208 = '#BA', $209 = '#BABA', $210 = '#CAT', $211 = '#DIS', $212 = '#EA', $213 = '#FB', $214 = '#FDX', $215 = '#GE', $216 = '#GM', $217 = '#GOOGL', $218 = '#GS', $219 = '#INTC', $220 = '#JPM', $221 = '#KO', $222 = '#MSFT', $223 = '#NFLX', $224 = '#TSLA', $225 = '#WMT', $226 = '#XOM', $227 = '0', $228 = '', $229 = '500', $230 = '500', $231 = '0', $232 = '0', $233 = '0', $234 = 't', $235 = '10', $236 = '10'
WITH rar_max as ( ;

Date: 2026-01-23 09:15:47 Duration: 38ms Database: postgres parameters: $1 = 't', $2 = '627', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '213', $14 = '#ADBE', $15 = '#ALVG', $16 = '#AMZN', $17 = '#APPL', $18 = '#BA', $19 = '#BABA', $20 = '#BAYGn', $21 = '#BMWG', $22 = '#BNPP', $23 = '#CAT', $24 = '#CBKG', $25 = '#DAIGn', $26 = '#DIS', $27 = '#EA', $28 = '#FB', $29 = '#FDX', $30 = '#GE', $31 = '#GM', $32 = '#GOOGL', $33 = '#GS', $34 = '#INTC', $35 = '#JPM', $36 = '#KO', $37 = '#META', $38 = '#MSFT', $39 = '#NFLX', $40 = '#TSLA', $41 = '#VOWG', $42 = '#WMT', $43 = '#XOM', $44 = 'AUDCAD', $45 = 'AUDCHF', $46 = 'AUDJPY', $47 = 'AUDNZD', $48 = 'AUDUSD', $49 = 'AUS_200', $50 = 'BTCEUR', $51 = 'BTCGBP', $52 = 'BTCUSD', $53 = 'CADCHF', $54 = 'CADJPY', $55 = 'CHFJPY', $56 = 'CL_BRENT', $57 = 'DASHUSD', $58 = 'EOSUSD', $59 = 'ESP_35', $60 = 'ETHEUR', $61 = 'ETHGBP', $62 = 'ETHUSD', $63 = 'EURAUD', $64 = 'EURCAD', $65 = 'EURCHF', $66 = 'EURGBP', $67 = 'EURJPY', $68 = 'EURMXN', $69 = 'EURNOK', $70 = 'EURNZD', $71 = 'EURPLN', $72 = 'EURSEK', $73 = 'EURTRY', $74 = 'EURUSD', $75 = 'EUR_50', $76 = 'FRA_40', $77 = 'GBPAUD', $78 = 'GBPCAD', $79 = 'GBPCHF', $80 = 'GBPJPY', $81 = 'GBPNZD', $82 = 'GBPUSD', $83 = 'GBPZAR', $84 = 'GBR_100', $85 = 'HKDJPY', $86 = 'HKG_50', $87 = 'IOTAUSD', $88 = 'LTCEUR', $89 = 'LTCUSD', $90 = 'NAS100', $91 = 'NEOUSD', $92 = 'NOKJPY', $93 = 'NZDCAD', $94 = 'NZDCHF', $95 = 'NZDJPY', $96 = 'NZDUSD', $97 = 'OMGUSD', $98 = 'SPX500', $99 = 'TRXUSD', $100 = 'US30', $101 = 'USDCAD', $102 = 'USDCHF', $103 = 'USDCNH', $104 = 'USDDKK', $105 = 'USDJPY', $106 = 'USDMXN', $107 = 'USDNOK', $108 = 'USDPLN', $109 = 'USDSEK', $110 = 'USDSGD', $111 = 'USDZAR', $112 = 'USOIL', $113 = 'XAGUSD', $114 = 'XAUEUR', $115 = 'XAUUSD', $116 = 'XMRUSD', $117 = 'XPTUSD', $118 = 'XRPUSD', $119 = 'ZARJPY', $120 = 'ZECUSD', $121 = 'AUDCAD', $122 = 'AUDCHF', $123 = 'AUDJPY', $124 = 'AUDNZD', $125 = 'AUDUSD', $126 = 'CADCHF', $127 = 'CADJPY', $128 = 'CHFJPY', $129 = 'EURAUD', $130 = 'EURCAD', $131 = 'EURCHF', $132 = 'EURGBP', $133 = 'EURJPY', $134 = 'EURMXN', $135 = 'EURNOK', $136 = 'EURNZD', $137 = 'EURPLN', $138 = 'EURSEK', $139 = 'EURTRY', $140 = 'EURUSD', $141 = 'GBPAUD', $142 = 'GBPCAD', $143 = 'GBPCHF', $144 = 'GBPJPY', $145 = 'GBPNZD', $146 = 'GBPUSD', $147 = 'GBPZAR', $148 = 'HKDJPY', $149 = 'NOKJPY', $150 = 'NZDCAD', $151 = 'NZDCHF', $152 = 'NZDJPY', $153 = 'NZDUSD', $154 = 'USDCAD', $155 = 'USDCHF', $156 = 'USDCNH', $157 = 'USDDKK', $158 = 'USDJPY', $159 = 'USDMXN', $160 = 'USDNOK', $161 = 'USDPLN', $162 = 'USDSEK', $163 = 'USDSGD', $164 = 'USDZAR', $165 = 'ZARJPY', $166 = 'BTCEUR', $167 = 'BTCGBP', $168 = 'BTCUSD', $169 = 'DASHUSD', $170 = 'EOSUSD', $171 = 'ETHEUR', $172 = 'ETHGBP', $173 = 'ETHUSD', $174 = 'IOTAUSD', $175 = 'LTCEUR', $176 = 'LTCUSD', $177 = 'NEOUSD', $178 = 'OMGUSD', $179 = 'TRXUSD', $180 = 'XMRUSD', $181 = 'XRPUSD', $182 = 'ZECUSD', $183 = 'XAGUSD', $184 = 'XAUEUR', $185 = 'XAUUSD', $186 = 'XPTUSD', $187 = 'CL_BRENT', $188 = 'USOIL', $189 = '#ALVG', $190 = '#BAYGn', $191 = '#BMWG', $192 = '#BNPP', $193 = '#CBKG', $194 = '#DAIGn', $195 = '#VOWG', $196 = 'AUS_200', $197 = 'ESP_35', $198 = 'EUR_50', $199 = 'FRA_40', $200 = 'GBR_100', $201 = 'HKG_50', $202 = 'NAS100', $203 = 'SPX500', $204 = 'US30', $205 = '#ADBE', $206 = '#AMZN', $207 = '#APPL', $208 = '#BA', $209 = '#BABA', $210 = '#CAT', $211 = '#DIS', $212 = '#EA', $213 = '#FB', $214 = '#FDX', $215 = '#GE', $216 = '#GM', $217 = '#GOOGL', $218 = '#GS', $219 = '#INTC', $220 = '#JPM', $221 = '#KO', $222 = '#MSFT', $223 = '#NFLX', $224 = '#TSLA', $225 = '#WMT', $226 = '#XOM', $227 = '0', $228 = '', $229 = '500', $230 = '500', $231 = '0', $232 = '0', $233 = '0', $234 = 't', $235 = '10', $236 = '10'
WITH rar_max as ( ;

Date: 2026-01-23 09:01:58 Duration: 37ms Database: postgres parameters: $1 = 't', $2 = '627', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '0', $14 = '', $15 = '0', $16 = '', $17 = '0', $18 = '0', $19 = '0', $20 = '0', $21 = '0', $22 = 't', $23 = '10', $24 = '10'

2

7s918ms

22,166

Details

0ms

9ms

0ms

SELECT ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	09	22,166	7s918ms	0ms

SELECT ;

Date: 2026-01-23 09:02:12 Duration: 9ms Database: postgres parameters: $1 = '515840233926223300'
SELECT ;

Date: 2026-01-23 09:45:04 Duration: 8ms Database: postgres parameters: $1 = '515840243265160300'
SELECT ;

Date: 2026-01-23 09:55:12 Duration: 7ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '515840243231237300'

3

2s593ms

1,168

Details

0ms

10ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	09	1,168	2s593ms	2ms

SELECT symbolid, ;

Date: 2026-01-23 09:46:13 Duration: 10ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'GBPJPY', $4 = 'GBPUSD'
SELECT symbolid, ;

Date: 2026-01-23 09:46:05 Duration: 7ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'ETHJPY', $4 = 'ETHUSD'
SELECT symbolid, ;

Date: 2026-01-23 09:46:16 Duration: 5ms Database: postgres parameters: $1 = 'AXIORY', $2 = '15', $3 = 'NGAS'

4

1s471ms

242

Details

0ms

21ms

6ms

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

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	09	242	1s471ms	6ms

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

Date: 2026-01-23 09:10:57 Duration: 21ms Database: postgres parameters: $1 = '489', $2 = '489'
select distinct s.statsid as statsid, sy.exchange as name;

Date: 2026-01-23 09:10:57 Duration: 21ms Database: postgres parameters: $1 = '489', $2 = '489'
select distinct s.statsid as statsid, sy.exchange as name;

Date: 2026-01-23 09:10:57 Duration: 21ms Database: postgres parameters: $1 = '489', $2 = '489'

5

1s14ms

594

Details

1ms

11ms

1ms

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

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	09	594	1s14ms	1ms

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

Date: 2026-01-23 09:30:52 Duration: 11ms Database: postgres parameters: $1 = 'PEPPERSTONE'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-01-23 09:02:10 Duration: 2ms Database: postgres parameters: $1 = 'BDSWISS'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-01-23 09:46:03 Duration: 2ms Database: postgres parameters: $1 = 'GLOBALGTMT5'

6

779ms

11,324

Details

0ms

1ms

0ms

select category, ;

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	09	11,324	779ms	0ms

select category, ;

Date: 2026-01-23 09:51:22 Duration: 1ms Database: postgres parameters: $1 = '515852059313898307', $2 = 'symbol', $3 = 'BTCUSD', $4 = 'AUDJPY', $5 = 'USDMXN', $6 = 'USDZAR', $7 = 'USDTHB', $8 = 'GBPJPY', $9 = 'USDJPY', $10 = 'CADJPY', $11 = 'USDHUF', $12 = 'NZDJPY', $13 = 'EURZAR', $14 = 'CHFJPY', $15 = 'EURJPY', $16 = 'SGDJPY', $17 = 'SEKJPY', $18 = 'EURHKD', $19 = 'EURTRY', $20 = 'USDSEK', $21 = 'USDDKK', $22 = 'NOKJPY', $23 = 'USDCZK', $24 = 'USDNOK', $25 = 'GBPSEK', $26 = 'EURNOK', $27 = 'GBPNOK', $28 = 'USDPLN', $29 = 'EURSEK', $30 = 'GBPDKK', $31 = 'BTCUSD', $32 = 'GBPAUD', $33 = 'EURPLN', $34 = 'GBPNZD', $35 = 'EURAUD', $36 = 'USDCNH', $37 = 'EURNZD', $38 = 'USDTRY', $39 = 'GBPCAD', $40 = 'EURGBP', $41 = 'GBPNOK', $42 = 'SEKJPY', $43 = 'GBPSGD', $44 = 'USDZAR', $45 = 'USDHUF', $46 = 'EURCAD', $47 = 'USDCAD', $48 = 'GBPCAD', $49 = 'GBPUSD', $50 = 'NOKJPY', $51 = 'EURDKK', $52 = 'GBPDKK', $53 = '515852059313898307', $54 = 'symbol', $55 = 'BTCUSD', $56 = 'AUDJPY', $57 = 'USDMXN', $58 = 'USDZAR', $59 = 'USDTHB', $60 = 'GBPJPY', $61 = 'USDJPY', $62 = 'CADJPY', $63 = 'USDHUF', $64 = 'NZDJPY', $65 = 'EURZAR', $66 = 'CHFJPY', $67 = 'EURJPY', $68 = 'SGDJPY', $69 = 'SEKJPY', $70 = 'EURHKD', $71 = 'EURTRY', $72 = 'USDSEK', $73 = 'USDDKK', $74 = 'NOKJPY', $75 = 'USDCZK', $76 = 'USDNOK', $77 = 'GBPSEK', $78 = 'EURNOK', $79 = 'GBPNOK', $80 = 'USDPLN', $81 = 'EURSEK', $82 = 'GBPDKK', $83 = 'BTCUSD', $84 = 'GBPAUD', $85 = 'EURPLN', $86 = 'GBPNZD', $87 = 'EURAUD', $88 = 'USDCNH', $89 = 'EURNZD', $90 = 'USDTRY', $91 = 'GBPCAD', $92 = 'EURGBP', $93 = 'GBPNOK', $94 = 'SEKJPY', $95 = 'GBPSGD', $96 = 'USDZAR', $97 = 'USDHUF', $98 = 'EURCAD', $99 = 'USDCAD', $100 = 'GBPCAD', $101 = 'GBPUSD', $102 = 'NOKJPY', $103 = 'EURDKK', $104 = 'GBPDKK'
select category, ;

Date: 2026-01-23 09:11:01 Duration: 1ms Database: postgres parameters: $1 = '515852059324736307', $2 = 'symbol', $3 = 'USDMXN', $4 = 'CHFZAR', $5 = 'AUDJPY', $6 = 'CADJPY', $7 = 'USDZAR', $8 = 'ZARJPY', $9 = 'USDJPY', $10 = 'CHFJPY', $11 = 'AUDZAR', $12 = 'USDHUF', $13 = 'NZDJPY', $14 = 'TRYJPY', $15 = 'GBPJPY', $16 = 'EURCNH', $17 = 'GBPZAR', $18 = 'EURMXN', $19 = 'USDCZK', $20 = 'USDNOK', $21 = 'SGDJPY', $22 = 'EURZAR', $23 = 'CHFHUF', $24 = 'EURHKD', $25 = 'EURNOK', $26 = 'USDDKK', $27 = 'EURJPY', $28 = 'NZDSEK', $29 = 'EURSEK', $30 = 'USDSEK', $31 = 'EURTRY', $32 = 'EURHUF', $33 = 'USDPLN', $34 = 'USDCNH', $35 = 'EURCZK', $36 = 'GBPNZD', $37 = 'EURPLN', $38 = 'USDILS', $39 = 'TRYJPY', $40 = 'EURGBP', $41 = 'GBPAUD', $42 = 'EURCZK', $43 = 'EURNZD', $44 = 'EURHUF', $45 = 'CHFHUF', $46 = 'EURAUD', $47 = 'GBPCAD', $48 = 'ZARJPY', $49 = 'USDZAR', $50 = 'USDCAD', $51 = 'EURCAD', $52 = 'USDTRY', $53 = '515852059324736307', $54 = 'symbol', $55 = 'USDMXN', $56 = 'CHFZAR', $57 = 'AUDJPY', $58 = 'CADJPY', $59 = 'USDZAR', $60 = 'ZARJPY', $61 = 'USDJPY', $62 = 'CHFJPY', $63 = 'AUDZAR', $64 = 'USDHUF', $65 = 'NZDJPY', $66 = 'TRYJPY', $67 = 'GBPJPY', $68 = 'EURCNH', $69 = 'GBPZAR', $70 = 'EURMXN', $71 = 'USDCZK', $72 = 'USDNOK', $73 = 'SGDJPY', $74 = 'EURZAR', $75 = 'CHFHUF', $76 = 'EURHKD', $77 = 'EURNOK', $78 = 'USDDKK', $79 = 'EURJPY', $80 = 'NZDSEK', $81 = 'EURSEK', $82 = 'USDSEK', $83 = 'EURTRY', $84 = 'EURHUF', $85 = 'USDPLN', $86 = 'USDCNH', $87 = 'EURCZK', $88 = 'GBPNZD', $89 = 'EURPLN', $90 = 'USDILS', $91 = 'TRYJPY', $92 = 'EURGBP', $93 = 'GBPAUD', $94 = 'EURCZK', $95 = 'EURNZD', $96 = 'EURHUF', $97 = 'CHFHUF', $98 = 'EURAUD', $99 = 'GBPCAD', $100 = 'ZARJPY', $101 = 'USDZAR', $102 = 'USDCAD', $103 = 'EURCAD', $104 = 'USDTRY'
select category, ;

Date: 2026-01-23 09:11:01 Duration: 1ms Database: postgres parameters: $1 = '515852059324253307', $2 = 'symbol', $3 = 'USDMXN', $4 = 'CHFZAR', $5 = 'AUDJPY', $6 = 'CADJPY', $7 = 'USDZAR', $8 = 'ZARJPY', $9 = 'USDJPY', $10 = 'CHFJPY', $11 = 'AUDZAR', $12 = 'USDHUF', $13 = 'NZDJPY', $14 = 'TRYJPY', $15 = 'GBPJPY', $16 = 'EURCNH', $17 = 'GBPZAR', $18 = 'EURMXN', $19 = 'USDCZK', $20 = 'USDNOK', $21 = 'SGDJPY', $22 = 'EURZAR', $23 = 'CHFHUF', $24 = 'EURHKD', $25 = 'EURNOK', $26 = 'USDDKK', $27 = 'EURJPY', $28 = 'NZDSEK', $29 = 'EURSEK', $30 = 'USDSEK', $31 = 'EURTRY', $32 = 'EURHUF', $33 = 'USDPLN', $34 = 'USDCNH', $35 = 'EURCZK', $36 = 'GBPNZD', $37 = 'EURPLN', $38 = 'USDILS', $39 = 'TRYJPY', $40 = 'EURGBP', $41 = 'GBPAUD', $42 = 'EURCZK', $43 = 'EURNZD', $44 = 'EURHUF', $45 = 'CHFHUF', $46 = 'EURAUD', $47 = 'GBPCAD', $48 = 'ZARJPY', $49 = 'USDZAR', $50 = 'USDCAD', $51 = 'EURCAD', $52 = 'USDTRY', $53 = '515852059324253307', $54 = 'symbol', $55 = 'USDMXN', $56 = 'CHFZAR', $57 = 'AUDJPY', $58 = 'CADJPY', $59 = 'USDZAR', $60 = 'ZARJPY', $61 = 'USDJPY', $62 = 'CHFJPY', $63 = 'AUDZAR', $64 = 'USDHUF', $65 = 'NZDJPY', $66 = 'TRYJPY', $67 = 'GBPJPY', $68 = 'EURCNH', $69 = 'GBPZAR', $70 = 'EURMXN', $71 = 'USDCZK', $72 = 'USDNOK', $73 = 'SGDJPY', $74 = 'EURZAR', $75 = 'CHFHUF', $76 = 'EURHKD', $77 = 'EURNOK', $78 = 'USDDKK', $79 = 'EURJPY', $80 = 'NZDSEK', $81 = 'EURSEK', $82 = 'USDSEK', $83 = 'EURTRY', $84 = 'EURHUF', $85 = 'USDPLN', $86 = 'USDCNH', $87 = 'EURCZK', $88 = 'GBPNZD', $89 = 'EURPLN', $90 = 'USDILS', $91 = 'TRYJPY', $92 = 'EURGBP', $93 = 'GBPAUD', $94 = 'EURCZK', $95 = 'EURNZD', $96 = 'EURHUF', $97 = 'CHFHUF', $98 = 'EURAUD', $99 = 'GBPCAD', $100 = 'ZARJPY', $101 = 'USDZAR', $102 = 'USDCAD', $103 = 'EURCAD', $104 = 'USDTRY'

7

691ms

24

Details

0ms

54ms

28ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	09	24	691ms	28ms

with wh_patitioned as ( ;

Date: 2026-01-23 09:00:56 Duration: 54ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2026-01-23 09:01:57 Duration: 50ms Database: postgres parameters: $1 = '627', $2 = '627', $3 = '627', $4 = '627', $5 = '627', $6 = '627', $7 = '627', $8 = '627', $9 = '627'
with wh_patitioned as ( ;

Date: 2026-01-23 09:36:06 Duration: 43ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'

8

543ms

36,839

Details

0ms

1ms

0ms

select 1;

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	09	36,839	543ms	0ms

select 1;

Date: 2026-01-23 09:44:37 Duration: 1ms Database: postgres
select 1;

Date: 2026-01-23 09:20:34 Duration: 1ms Database: postgres
select 1;

Date: 2026-01-23 09:20:34 Duration: 1ms Database: postgres

9

510ms

71

Details

4ms

14ms

7ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	09	71	510ms	7ms

WITH last_candle AS ( ;

Date: 2026-01-23 09:12:00 Duration: 14ms Database: postgres parameters: $1 = '538', $2 = '538'
WITH last_candle AS ( ;

Date: 2026-01-23 09:52:02 Duration: 13ms Database: postgres parameters: $1 = '538', $2 = '538'
WITH last_candle AS ( ;

Date: 2026-01-23 09:56:06 Duration: 13ms Database: postgres parameters: $1 = '538', $2 = '538'

10

374ms

596

Details

0ms

1ms

0ms

SELECT absolutetimezoneoffset;

Times Reported Time consuming bind #10

Day	Hour	Count	Duration	Avg duration
	09	596	374ms	0ms

SELECT absolutetimezoneoffset;

Date: 2026-01-23 09:11:03 Duration: 1ms Database: postgres parameters: $1 = '689', $2 = 'FOREX'
SELECT absolutetimezoneoffset;

Date: 2026-01-23 09:10:58 Duration: 1ms Database: postgres parameters: $1 = '538', $2 = 'Shares EU'
SELECT absolutetimezoneoffset;

Date: 2026-01-23 09:10:58 Duration: 1ms Database: postgres parameters: $1 = '538', $2 = 'Shares EU'

11

345ms

12

Details

28ms

29ms

28ms

with sym_info as ( ;

Times Reported Time consuming bind #11

Day	Hour	Count	Duration	Avg duration
	09	12	345ms	28ms

with sym_info as ( ;

Date: 2026-01-23 09:06:52 Duration: 29ms 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: 2026-01-23 09:06:44 Duration: 29ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
with sym_info as ( ;

Date: 2026-01-23 09:21:39 Duration: 29ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'

12

263ms

5,787

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
	09	5,787	263ms	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: 2026-01-23 09:15:53 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 09:00:00', $2 = '68.5', $3 = '68.6', $4 = '68.34', $5 = '68.44', $6 = '193', $7 = '515840248628004300', $8 = '0', $9 = '2026-01-23 09:15:53.776', $10 = '2026-01-23 09:15:53.556', $11 = '68.5', $12 = '68.6', $13 = '68.34', $14 = '68.44', $15 = '193', $16 = '0', $17 = '2026-01-23 09:15:53.776', $18 = '2026-01-23 09:15:53.556'
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: 2026-01-23 09:02:58 Duration: 0ms Database: postgres parameters: $1 = '2026-01-22 23:00:00', $2 = '1000.6', $3 = '1000.6', $4 = '998.7', $5 = '1000.3', $6 = '14', $7 = '515840233345549300', $8 = '0', $9 = '2026-01-23 09:02:58.215', $10 = '2026-01-23 09:02:58.118', $11 = '1000.6', $12 = '1000.6', $13 = '998.7', $14 = '1000.3', $15 = '14', $16 = '0', $17 = '2026-01-23 09:02:58.215', $18 = '2026-01-23 09:02:58.118'
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: 2026-01-23 09:46:52 Duration: 0ms Database: postgres parameters: $1 = '2026-01-22 23:45:00', $2 = '248.65', $3 = '248.855', $4 = '248.185', $5 = '248.265', $6 = '443', $7 = '515840216708269300', $8 = '0', $9 = '2026-01-23 09:46:52.369', $10 = '2026-01-23 09:46:52.317', $11 = '248.65', $12 = '248.855', $13 = '248.185', $14 = '248.265', $15 = '443', $16 = '0', $17 = '2026-01-23 09:46:52.37', $18 = '2026-01-23 09:46:52.317'

13

244ms

3,310

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 #13

Day	Hour	Count	Duration	Avg duration
	09	3,310	244ms	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: 2026-01-23 09:41:10 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 09:00:00', $2 = '8862.4', $3 = '8867.9', $4 = '8860.4', $5 = '8862.25', $6 = '1140', $7 = '515840248015340300', $8 = '0', $9 = '2026-01-23 09:41:10.673', $10 = '2026-01-23 09:41:10.58', $11 = '8862.4', $12 = '8867.9', $13 = '8860.4', $14 = '8862.25', $15 = '1140', $16 = '0', $17 = '2026-01-23 09:41:10.673', $18 = '2026-01-23 09:41:10.58'
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: 2026-01-23 09:02:06 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 09:30:00', $2 = '2946.54', $3 = '2956.165', $4 = '2938', $5 = '2940.17', $6 = '2525', $7 = '515840249394341300', $8 = '0', $9 = '2026-01-23 09:02:06.912', $10 = '2026-01-23 09:02:06.808', $11 = '2946.54', $12 = '2956.165', $13 = '2938', $14 = '2940.17', $15 = '2525', $16 = '0', $17 = '2026-01-23 09:02:06.912', $18 = '2026-01-23 09:02:06.808'
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: 2026-01-23 09:41:26 Duration: 0ms Database: postgres parameters: $1 = '2026-01-23 09:00:00', $2 = '49396.69', $3 = '49417.29', $4 = '49391.79', $5 = '49395.54', $6 = '3347', $7 = '515840248000726300', $8 = '0', $9 = '2026-01-23 09:41:26.777', $10 = '2026-01-23 09:41:26.708', $11 = '49396.69', $12 = '49417.29', $13 = '49391.79', $14 = '49395.54', $15 = '3347', $16 = '0', $17 = '2026-01-23 09:41:26.778', $18 = '2026-01-23 09:41:26.708'

14

175ms

2,168

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 #14

Day	Hour	Count	Duration	Avg duration
	09	2,168	175ms	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: 2026-01-23 09:02:58 Duration: 0ms Database: postgres parameters: $1 = '2026-01-22 20:00:00', $2 = '17661.8', $3 = '17663.8', $4 = '17646.4', $5 = '17647.8', $6 = '221', $7 = '515840233506948300', $8 = '0', $9 = '2026-01-23 09:02:58.398', $10 = '2026-01-23 09:02:58.397', $11 = '17661.8', $12 = '17663.8', $13 = '17646.4', $14 = '17647.8', $15 = '221', $16 = '0', $17 = '2026-01-23 09:02:58.398', $18 = '2026-01-23 09:02:58.397'
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: 2026-01-23 09:02:56 Duration: 0ms Database: postgres parameters: $1 = '2026-01-22 22:00:00', $2 = '8134.1', $3 = '8144.1', $4 = '8134.1', $5 = '8137.1', $6 = '764', $7 = '515840222794319300', $8 = '0', $9 = '2026-01-23 09:02:56.498', $10 = '2026-01-23 09:02:56.497', $11 = '8134.1', $12 = '8144.1', $13 = '8134.1', $14 = '8137.1', $15 = '764', $16 = '0', $17 = '2026-01-23 09:02:56.498', $18 = '2026-01-23 09:02:56.497'
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: 2026-01-23 09:02:49 Duration: 0ms Database: postgres parameters: $1 = '2026-01-22 22:00:00', $2 = '8160.2', $3 = '8169.2', $4 = '8159.2', $5 = '8160.7', $6 = '1537', $7 = '515840233386747300', $8 = '0', $9 = '2026-01-23 09:02:49.908', $10 = '2026-01-23 09:02:49.907', $11 = '8160.2', $12 = '8169.2', $13 = '8159.2', $14 = '8160.7', $15 = '1537', $16 = '0', $17 = '2026-01-23 09:02:49.908', $18 = '2026-01-23 09:02:49.907'

15

94ms

18

Details

3ms

9ms

5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #15

Day	Hour	Count	Duration	Avg duration
	09	18	94ms	5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-23 09:11:51 Duration: 9ms Database: postgres parameters: $1 = '627', $2 = '627'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-23 09:01:39 Duration: 6ms Database: postgres parameters: $1 = '538', $2 = '538'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-23 09:45:44 Duration: 6ms Database: postgres parameters: $1 = '689', $2 = '689'

16

68ms

35

Details

1ms

6ms

1ms

WITH rcr_max as ( ;

Times Reported Time consuming bind #16

Day	Hour	Count	Duration	Avg duration
	09	35	68ms	1ms

WITH rcr_max as ( ;

Date: 2026-01-23 09:16:04 Duration: 6ms Database: postgres parameters: $1 = '607551679928443305', $2 = '607551679928443305', $3 = '607551679928443305'
WITH rcr_max as ( ;

Date: 2026-01-23 09:01:01 Duration: 5ms Database: postgres parameters: $1 = '607551679928443305', $2 = '607551679928443305', $3 = '607551679928443305'
WITH rcr_max as ( ;

Date: 2026-01-23 09:40:00 Duration: 5ms Database: postgres parameters: $1 = '607551679928443305', $2 = '607551679928443305', $3 = '607551679928443305'

17

61ms

73

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 #17

Day	Hour	Count	Duration	Avg duration
	09	73	61ms	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: 2026-01-23 09:20:31 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'GBPJPY', $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: 2026-01-23 09:02:02 Duration: 1ms Database: postgres parameters: $1 = '689', $2 = 'XAUUSD', $3 = '689'
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2026-01-23 09:02:07 Duration: 1ms Database: postgres parameters: $1 = '538', $2 = 'EURUSD', $3 = '538'

18

56ms

142

Details

0ms

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

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	09	142	56ms	0ms

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

Date: 2026-01-23 09:13:39 Duration: 0ms Database: postgres
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2026-01-23 09:13:40 Duration: 0ms Database: postgres
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2026-01-23 09:13:40 Duration: 0ms Database: postgres

19

53ms

1,192

Details

0ms

select distinct category;

Times Reported Time consuming bind #19

Day	Hour	Count	Duration	Avg duration
	09	1,192	53ms	0ms

select distinct category;

Date: 2026-01-23 09:10:58 Duration: 0ms Database: postgres parameters: $1 = '601729875347685307', $2 = '601729875347685307'
select distinct category;

Date: 2026-01-23 09:10:58 Duration: 0ms Database: postgres parameters: $1 = '601729875347685307', $2 = '601729875347685307'
select distinct category;

Date: 2026-01-23 09:51:17 Duration: 0ms Database: postgres parameters: $1 = '515852059313898307', $2 = '515852059313898307'

20

52ms

596

Details

0ms

SELECT name;

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	09	596	52ms	0ms

SELECT name;

Date: 2026-01-23 09:10:57 Duration: 0ms Database: postgres parameters: $1 = '515852059317765307', $2 = '515852059317765307'
SELECT name;

Date: 2026-01-23 09:10:57 Duration: 0ms Database: postgres parameters: $1 = '515852059317765307', $2 = '515852059317765307'
SELECT name;

Date: 2026-01-23 09:00:46 Duration: 0ms Database: postgres parameters: $1 = '515852059317765307', $2 = '515852059317765307'

Log levels

Key values

511,134 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	700	0.14%
DETAIL	119,078	23.30%
ERROR	34	0.01%
FATAL	1	0.00%
HINT	34	0.01%
LOG	390,405	76.38%
STATEMENT	882	0.17%

Events distribution

Key values

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

Most Frequent Errors/Events

Key values

34 Max number of times the same event was reported
35 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 23	09	34

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

2

1

Details

FATAL: connection to client lost

Times Reported Most Frequent Error / Event #2

Day	Hour	Count
Jan 23	09	1

FATAL: connection to client lost

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

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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