pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Tue Jan 27 02:59:50 2026
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-01-27_040000.log
Parsed 2,163,504 log entries in 49s
Log start from 2026-01-27 04:00:00 to 2026-01-27 04:59:48

Global Stats

297 Number of unique normalized queries
236,635 Number of queries
1h59m42s Total query duration
2026-01-27 04:00:00 First query
2026-01-27 04:59:48 Last query
1,894 queries/s at 2026-01-27 04:03:26 Query peak

1h59m42s Total query duration
13s731ms Prepare/parse total duration
1m6s Bind total duration
1h58m21s Execute total duration

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

42 Total number of automatic vacuums
58 Total number of automatic analyzes

811 Number temporary file
496.52 MiB Max size of temporary file
7.38 MiB Average size of temporary file

5,319 Total number of sessions
14 sessions at 2026-01-27 04:43:55 Session peak
2d12h59m12s Total duration of sessions
41s277ms Average duration of sessions
44 Average queries per session
1s350ms Average queries duration per session
39s926ms Average idle time per session

5,350 Total number of connections
37 connections/s at 2026-01-27 04:30:28 Connection peak
3 Total number of databases

SQL Traffic

Key values

1,894 queries/s Query Peak
2026-01-27 04:03:26 Date

SELECT Traffic

Key values

846 queries/s Query Peak
2026-01-27 04:02:08 Date

INSERT/UPDATE/DELETE Traffic

Key values

937 queries/s Query Peak
2026-01-27 04:03:26 Date

Queries duration

Key values

1h59m42s 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 27	04	236,635	0ms	37s126ms	30ms	3m23s	3m50s	4m28s

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Jan 27	04	61,678	27	0ms	0ms	0ms	0ms

Day	Hour	INSERT	UPDATE	DELETE	COPY FROM	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Jan 27	04	34,750	3,627	16	96	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Jan 27	04	34,138	78,267	2.29	31.27%

Day	Hour	Count	Average / Second
Jan 27	04	5,350	1.49/s

Day	Hour	Count	Average Duration	Average idle time
Jan 27	04	5,319	41s277ms	39s941ms

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Established Connections

Key values

37 connections Connection Peak
2026-01-27 04:30:28 Date

Connections per database

Key values

acaweb_fx Main Database
5,350 connections Total

Chart
Table

Database	User	Count
acaweb_fx		5,254
	postgres	4,863
	psql	391
socialmedia		96
	postgres	96

Connections per user

Key values

postgres Main User
5,350 connections Total

Chart
Table

User	Count
postgres	4,959
psql	391

Connections per host

Key values

192.168.1.15 Main host with 2358 connections
5,350 Total connections

Chart
Table

Host	Count
127.0.0.1	145
192.168.0.114	8
192.168.0.216	101
192.168.0.74	467
192.168.1.145	110
192.168.1.15	2,358
192.168.1.20	125
192.168.1.231	20
192.168.1.239	10
192.168.1.90	76
192.168.2.126	62
192.168.2.182	12
192.168.2.82	48
192.168.3.199	36
192.168.4.108	6
192.168.4.140	4
192.168.4.142	1,032
192.168.4.150	10
192.168.4.238	16
192.168.4.33	90
192.168.4.54	6
192.168.4.91	1
192.168.4.98	330
[local]	277

Simultaneous sessions

Key values

14 sessions Session Peak
2026-01-27 04:43:55 Date

Histogram of session times

Key values

4,421 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	4,421	83.12%
500ms-1s	147	2.76%
1s-30s	494	9.29%
30s-1m	104	1.96%
1m-10m	93	1.75%
10m-30m	46	0.86%
30m-1h	0	0.00%
1h-8h	14	0.26%
> 8h	0	0.00%

Sessions per database

Key values

acaweb_fx Main Database
5,319 sessions Total

Chart
Table

Database	User	Count	Total Duration	Average Duration
acaweb_fx	5,223	2d12h27m5s	41s666ms
socialmedia	96	32m7s	20s76ms

Sessions per user

Key values

postgres Main User
5,319 sessions Total

Chart
Table

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

Sessions per host

Key values

192.168.1.15 Main Host
5,319 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
127.0.0.1	114	13s285ms	116ms
192.168.0.114	8	42m46s	5m20s
192.168.0.216	101	1m2s	617ms
192.168.0.74	467	2h6m7s	16s204ms
192.168.1.145	110	2h2m33s	1m6s
192.168.1.15	2,358	14h1m34s	21s413ms
192.168.1.20	125	11h45m39s	5m38s
192.168.1.231	20	9h50m54s	29m32s
192.168.1.239	10	283ms	28ms
192.168.1.90	76	37s213ms	489ms
192.168.2.126	62	6s433ms	103ms
192.168.2.182	12	1s74ms	89ms
192.168.2.82	48	11s94ms	231ms
192.168.3.199	36	1s738ms	48ms
192.168.4.108	6	75ms	12ms
192.168.4.140	4	23s542ms	5s885ms
192.168.4.142	1,032	10m27s	607ms
192.168.4.150	10	20h10m41s	2h1m4s
192.168.4.238	16	15s804ms	987ms
192.168.4.33	90	2m6s	1s409ms
192.168.4.54	6	79ms	13ms
192.168.4.91	1	242ms	242ms
192.168.4.98	330	15s534ms	47ms
[local]	277	3m13s	697ms

Sessions per application

Key values

unknown Main Host
5,319 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	5,319	2d12h59m12s	41s277ms

Checkpoints Buffers

Key values

13,080 buffers Checkpoint Peak
2026-01-27 04:07:50 Date
210.042 seconds Highest write time
0.010 seconds Sync time

Checkpoints Wal files

Key values

7 files Wal files usage Peak
2026-01-27 04:07:50 Date

Checkpoints distance

Key values

230.24 Mo Distance Peak
2026-01-27 04:07:50 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Jan 27	04	45,463	1,736.983s	0.056s	1,737.346s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Jan 27	04	0	0	24	2,020	0.005s	0s

Day	Hour	Count	Avg time (sec)
Jan 27	04	0	0s

Day	Hour	Mean distance	Mean estimate
Jan 27	04	33,789.83 kB	80,383.92 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

496.52 MiB Temp Files size Peak
2026-01-27 04:05:09 Date

Number of temporary files

Key values

62 per second Temp Files Peak
2026-01-27 04:17:15 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Jan 27	04	811	5.85 GiB	7.38 MiB

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Queries generating the most temporary files (N)

Rank	Count	Total size	Min size	Max size	Avg size	Query
1	37	141.90 MiB	3.81 MiB	3.85 MiB	3.84 MiB	select resultuid from relevance_fibonacci_results order by resultuid desc limit ?), fr as ( select a., rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp)))), results as ( select distinct on (symbolid) from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc; SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1), fr AS ( SELECT a., rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4, $5, $6, $7, $8, $9, $10)) AND ($11 = 0 OR s.exchange in ($12)) AND ($13 = 0 OR coalesce(bim.code, s.symbol) in ($14)) AND ($15 = 0 OR fr.pattern in ($16)) AND ($17 = 0 OR fr.patternlengthbars <= $18) AND ($19 = 0 OR ($20 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($21 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) FROM all_results WHERE (FALSE = $22 OR relevant = 1) AND ($23 = 0 OR age <= $24) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-01-27 04:00:55 Duration: 0ms
2	30	1.65 GiB	5.47 MiB	157.52 MiB	56.40 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: 2026-01-27 04:00:06 Duration: 0ms
3	22	163.96 MiB	7.42 MiB	7.46 MiB	7.45 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: 2026-01-27 04:00:20 Duration: 0ms
4	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: 2026-01-27 04:01:12 Duration: 0ms
5	16	1.22 GiB	78.20 MiB	78.20 MiB	78.20 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: 2026-01-27 04:01:15 Duration: 0ms
6	8	899.50 MiB	112.34 MiB	112.48 MiB	112.44 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2026-01-27 04:02:16 Duration: 0ms
7	4	350.83 MiB	87.65 MiB	87.78 MiB	87.71 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2026-01-27 04:02:06 Duration: 0ms
8	1	113.46 MiB	113.46 MiB	113.46 MiB	113.46 MiB	with a as ( select , row_number() over (partition by symbolid, direction order by datetime desc) r from sa_hist_consecutivecandles ) select distinct a.symbolid, a.qty, a.percentile, a.direction from a inner join symbols s on a.symbolid = s.symbolid inner join autochartist_stocklist aus on s.symbolid = aus.symbolid where aus.enabled = ? and a.r = ? and aus.recognitionengine ilike ?; WITH a AS ( SELECT , row_number() OVER (PARTITION BY symbolid, direction ORDER BY datetime DESC) r FROM sa_hist_consecutivecandles ) SELECT DISTINCT a.symbolid, a.qty, a.percentile, a.direction FROM a INNER JOIN symbols s on a.symbolid = s.symbolid INNER JOIN autochartist_stocklist aus on s.symbolid = aus.symbolid WHERE aus.Enabled = 1 AND a.r = 1 AND aus.RecognitionEngine ILIKE 'DXFEED_FX - 1'; Date: 2026-01-27 04:05:19 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	157.52 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: 2026-01-27 04:40:08 ]
2	124.66 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: 2026-01-27 04:20:04 ]
3	115.25 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: 2026-01-27 04:50:04 ]
4	113.46 MiB	WITH a AS ( SELECT , row_number() OVER (PARTITION BY symbolid, direction ORDER BY datetime DESC) r FROM sa_hist_consecutivecandles ) SELECT DISTINCT a.symbolid, a.qty, a.percentile, a.direction FROM a INNER JOIN symbols s on a.symbolid = s.symbolid INNER JOIN autochartist_stocklist aus on s.symbolid = aus.symbolid WHERE aus.Enabled = 1 AND a.r = 1 AND aus.RecognitionEngine ILIKE 'DXFEED_FX - 1'; [ Date:* 2026-01-27 04:05:19 ]
5	112.48 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 04:47:24 ]
6	112.48 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 04:50:33 ]
7	112.48 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 04:32:22 ]
8	112.47 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 04:35:32 ]
9	112.43 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 04:20:33 ]
10	112.41 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 04:17:25 ]
11	112.39 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 04:05:35 ]
12	112.34 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 04:02:16 ]
13	103.63 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: 2026-01-27 04:30:04 ]
14	101.73 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-27 04:50:05 ]
15	89.26 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: 2026-01-27 04:00:05 ]
16	87.78 MiB	select updateageforrelevantresults (); [ Date: 2026-01-27 04:32:07 ]
17	87.75 MiB	select updateageforrelevantresults (); [ Date: 2026-01-27 04:47:06 ]
18	87.65 MiB	select updateageforrelevantresults (); [ Date: 2026-01-27 04:02:06 ]
19	87.65 MiB	select updateageforrelevantresults (); [ Date: 2026-01-27 04:17:07 ]
20	87.11 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: 2026-01-27 04:10:05 ]

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)
58 analyzes Total

Chart
Table

Table	Number of analyzes
acaweb_fx.public.solr_relevance_old	16
acaweb_fx.pg_catalog.pg_attribute	5
acaweb_fx.public.relevance_fibonacci_results	5
acaweb_fx.public.relevance_autochartist_results	5
acaweb_fx.public.datafeeds_latestrun	4
acaweb_fx.public.relevance_keylevels_results	4
acaweb_fx.pg_catalog.pg_class	4
acaweb_fx.pg_catalog.pg_type	3
acaweb_fx.pg_catalog.pg_index	2
acaweb_fx.public.latest_t15_candle_view	2
acaweb_fx.public.autochartist_symbolupdates	1
acaweb_fx.public.solr_imports	1
acaweb_fx.pg_catalog.pg_depend	1
acaweb_fx.public.latest_candle_datetime_per_receng	1
acaweb_fx.public.sa_hist_bigmove	1
acaweb_fx.public.symbollatestupdatetime	1
acaweb_fx.public.bigmovement_results_underlying	1
acaweb_fx.public.correlating_signals	1
Total	58

Vacuums per table

Key values

public.solr_relevance_old (18) Main table vacuumed on database acaweb_fx
42 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	12,024	0	60	0	62	7,742	151	1,927,316
acaweb_fx.public.datafeeds_latestrun	4	0	481	0	12	0	0	60	36	70,304
acaweb_fx.pg_toast.pg_toast_2619	2	2	284	0	51	0	0	199	48	209,511
acaweb_fx.pg_catalog.pg_attribute	2	2	1,644	0	344	0	134	765	278	1,655,494
acaweb_fx.pg_catalog.pg_statistic	2	2	1,939	0	355	0	1,174	918	325	1,204,766
acaweb_fx.public.latest_t15_candle_view	2	2	159	0	3	0	0	12	5	21,056
acaweb_fx.public.relevance_keylevels_results	2	2	7,606	0	652	2	182	2,186	641	1,490,785
acaweb_fx.pg_catalog.pg_class	2	2	930	0	120	0	0	300	110	582,490
acaweb_fx.public.relevance_autochartist_results	2	2	6,887	0	272	2	483	1,430	262	503,057
acaweb_fx.public.relevance_fibonacci_results	2	2	2,511	0	49	2	114	385	90	222,857
acaweb_fx.pg_catalog.pg_index	1	1	88	0	11	0	0	27	10	75,064
acaweb_fx.pg_catalog.pg_type	1	1	116	0	22	0	0	55	17	110,939
acaweb_fx.public.autochartist_symbolupdates	1	1	24,359	0	3,431	0	38,111	7,172	3,425	1,303,230
acaweb_fx.public.symbollatestupdatetime	1	1	1,925	0	421	0	503	1,379	363	1,004,237
Total	42	37	60,953	47,636	5,803	6	40,763	22,630	5,761	10,381,106

Tuples removed per table

Key values

public.solr_relevance_old (49729) Main table with removed tuples on database acaweb_fx
81727 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	49,729	96,751	8,148	0	3,003
acaweb_fx.public.symbollatestupdatetime	1	1	18,203	96,886	460	0	1,714
acaweb_fx.public.autochartist_symbolupdates	1	1	4,909	47,096	226	0	40,691
acaweb_fx.pg_catalog.pg_attribute	2	2	3,187	21,617	0	43	480
acaweb_fx.public.relevance_keylevels_results	2	2	2,271	22,385	0	0	558
acaweb_fx.public.relevance_autochartist_results	2	2	1,263	14,665	0	0	760
acaweb_fx.pg_catalog.pg_statistic	2	2	1,125	7,467	0	0	2,388
acaweb_fx.pg_catalog.pg_class	2	2	261	3,298	0	0	300
acaweb_fx.public.datafeeds_latestrun	4	0	247	56	0	0	64
acaweb_fx.public.relevance_fibonacci_results	2	2	151	2,766	0	0	204
acaweb_fx.pg_toast.pg_toast_2619	2	2	142	337	1	0	98
acaweb_fx.public.latest_t15_candle_view	2	2	124	28	0	0	2
acaweb_fx.pg_catalog.pg_type	1	1	106	1,446	0	0	39
acaweb_fx.pg_catalog.pg_index	1	1	9	813	0	0	22
Total	42	37	81,727	315,611	8,835	43	50,323

Pages removed per table

Key values

pg_catalog.pg_attribute (43) Main table with removed pages on database acaweb_fx
43 pages Total removed

Chart
Table

Table	Number of vacuums	Index scans	Tuples removed	Pages removed
acaweb_fx.pg_catalog.pg_attribute	2	2	3187	43
acaweb_fx.pg_catalog.pg_index	1	1	9	0
acaweb_fx.pg_toast.pg_toast_2619	2	2	142	0
acaweb_fx.pg_catalog.pg_type	1	1	106	0
acaweb_fx.public.datafeeds_latestrun	4	0	247	0
acaweb_fx.public.autochartist_symbolupdates	1	1	4909	0
acaweb_fx.pg_catalog.pg_statistic	2	2	1125	0
acaweb_fx.public.symbollatestupdatetime	1	1	18203	0
acaweb_fx.public.latest_t15_candle_view	2	2	124	0
acaweb_fx.public.relevance_keylevels_results	2	2	2271	0
acaweb_fx.pg_catalog.pg_class	2	2	261	0
acaweb_fx.public.solr_relevance_old	18	17	49729	0
acaweb_fx.public.relevance_autochartist_results	2	2	1263	0
acaweb_fx.public.relevance_fibonacci_results	2	2	151	0
Total	42	37	81,727	43

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Jan 27	04	42	58

↑ Back to the top of the Autovacuum Activity table

Locks by types

Key values

unknown Main Lock Type
0 locks Total

Chart
Table

Type of locks

NO DATASET

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

Most frequent waiting queries (N)

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

Queries that waited the most

Rank	Wait time	Query
NO DATASET

Queries by type

Key values

61,678 Total read queries
47,506 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	61,678	26.06%
INSERT	34,750	14.69%
UPDATE	3,627	1.53%
DELETE	16	0.01%
COPY FROM	96	0.04%
COPY TO	27	0.01%
CTE	8,240	3.48%
DDL	16	0.01%
TCL	734	0.31%
CURSOR	0	0.00%
OTHERS	127,451	53.86%

Queries by database

Key values

unknown Main database
235,578 Requests
1h58m21s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	961	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	243	0ms
	select	104	0ms
	tcl	332	0ms
	update	40	0ms
socialmedia	Total	96	0ms
	select	90	0ms
	tcl	6	0ms
unknown	Total	235,578	1h58m21s
	copy from	16	0ms
	copy to	1	0ms
	cte	8,136	0ms
	insert	34,750	0ms
	others	8,908	0ms
	select	61,484	0ms
	tcl	396	0ms
	update	3,587	0ms

Queries by user

Key values

unknown Main user
235,578 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	1,057	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	243	0ms
	select	194	0ms
	tcl	338	0ms
	update	40	0ms
unknown	Total	235,578	1h58m21s
	copy from	16	0ms
	copy to	1	0ms
	cte	8,136	0ms
	insert	34,750	0ms
	others	8,908	0ms
	select	61,484	0ms
	tcl	396	0ms
	update	3,587	0ms

Duration by user

Key values

1h58m21s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	1,057	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	243	0ms
	select	194	0ms
	tcl	338	0ms
	update	40	0ms
unknown	Total	235,578	1h58m21s
	copy from	16	0ms
	copy to	1	0ms
	cte	8,136	0ms
	insert	34,750	0ms
	others	8,908	0ms
	select	61,484	0ms
	tcl	396	0ms
	update	3,587	0ms

Queries by host

Key values

unknown Main host
236,635 Requests
1h58m21s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	236,635	1h58m21s
	copy from	96	0ms
	copy to	27	0ms
	cte	8,240	0ms
	ddl	16	0ms
	delete	16	0ms
	insert	34,750	0ms
	others	9,151	0ms
	select	61,678	0ms
	tcl	734	0ms
	update	3,627	0ms

Queries by application

Key values

unknown Main application
236,244 Requests
1h58m21s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
psql	Total	391	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	5	0ms
	select	104	0ms
	update	40	0ms
unknown	Total	236,244	1h58m21s
	copy from	16	0ms
	copy to	1	0ms
	cte	8,136	0ms
	insert	34,750	0ms
	others	9,146	0ms
	select	61,574	0ms
	tcl	734	0ms
	update	3,587	0ms

Number of cancelled queries

Key values

0 per second Cancelled query Peak
2026-01-27 04:37:44 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

79,745 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	79,745	67.41%
1-5ms	32,363	27.36%
5-10ms	2,922	2.47%
10-25ms	1,042	0.88%
25-50ms	351	0.30%
50-100ms	130	0.11%
100-500ms	459	0.39%
500-1000ms	167	0.14%
1000-10000ms	894	0.76%
> 10000ms	227	0.19%

Slowest individual queries

Rank	Duration	Query
NO DATASET

Time consuming queries

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

0ms

1

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1	0ms	0ms

2

0ms

32

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 27	04	32	0ms	0ms

3

0ms

4

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 27	04	4	0ms	0ms

4

0ms

1

Details

0ms

select distinct a.resultuid, a.breakoutbars, a.patternid, cast(a.x0 as timestamp) as x0, cast(a.x1 as timestamp) as x1, cast(x2 as timestamp) as x2, case when (x3 != ? and x3 != ?) then cast(x3 as timestamp) else cast(? as timestamp) end as x3, case when (x4 != ? and x4 != ?) then cast(x4 as timestamp) else cast(? as timestamp) end as x4, case when (x5 != ? and x5 != ?) then cast(x5 as timestamp) else cast(? as timestamp) end as x5, case when (x6 != ? and x6 != ?) then cast(x6 as timestamp) else cast(? as timestamp) end as x6, case when (x7 != ? and x7 != ?) then cast(x7 as timestamp) else cast(? as timestamp) end as x7, case when (x8 != ? and x8 != ?) then cast(x8 as timestamp) else cast(? as timestamp) end as x8, case when (x9 != ? and x9 != ?) then cast(x9 as timestamp) else cast(? as timestamp) end as x9, cast(a.atbaridentified as timestamp) as atbaridentified, cast(a.patternstarttime as timestamp) as patternstarttime, a.breakoutprice, a.symbolid, a.approachingregion, a.patternprice, a.errormargin, a.bandwidth, a.qtytp, a.patternlengthbars, a.symbolid, a.uniquepointsvalue, a.predictionpricefrom, a.predictionpriceto, a.breakout, a.direction, a.furthestprice, a.approachingtimestamp, a.atpriceidentified from keylevels_results a inner join symbols s on a.symbolid = s.symbolid inner join autochartist_stocklist aus on s.symbolid = aus.symbolid left outer join relevance_keylevels_results rkl on a.resultuid = rkl.resultuid where aus.enabled = ? and (rkl.relevant = ? or a.resultuid > ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?)) and aus.recognitionengine ilike ?;

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1	0ms	0ms

5

0ms

2,092

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Jan 27	04	2,092	0ms	0ms

6

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 #6

Day	Hour	Count	Duration	Avg duration
Jan 27	04	48	0ms	0ms

7

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Jan 27	04	4	0ms	0ms

8

0ms

31

Details

0ms

set client_encoding to ?;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Jan 27	04	31	0ms	0ms

9

0ms

1,012

Details

0ms

select pricedatetime, open, high, low, close, volume, bsf from t60 where symbolid = ? and pricedatetime > ? order by pricedatetime asc;

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1,012	0ms	0ms

10

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 #10

Day	Hour	Count	Duration	Avg duration
Jan 27	04	18	0ms	0ms

11

0ms

1

Details

0ms

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

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1	0ms	0ms

12

0ms

367

Details

0ms

commit;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 27	04	367	0ms	0ms

13

0ms

400

Details

0ms

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

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Jan 27	04	400	0ms	0ms

14

0ms

240

Details

0ms

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

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Jan 27	04	240	0ms	0ms

15

0ms

1

Details

0ms

listen "ATFX - ?";

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1	0ms	0ms

16

0ms

240

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Jan 27	04	240	0ms	0ms

17

0ms

31

Details

0ms

set session characteristics as transaction isolation level read uncommitted;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 27	04	31	0ms	0ms

18

0ms

5

Details

0ms

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

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Jan 27	04	5	0ms	0ms

19

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;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Jan 27	04	2	0ms	0ms

20

0ms

1

Details

0ms

with a as ( select *, row_number() over (partition by symbolid, direction order by datetime desc) r from sa_hist_consecutivecandles ) select distinct a.symbolid, a.qty, a.percentile, a.direction from a inner join symbols s on a.symbolid = s.symbolid inner join autochartist_stocklist aus on s.symbolid = aus.symbolid where aus.enabled = ? and a.r = ? and aus.recognitionengine ilike ?;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1	0ms	0ms

WITH a AS ( SELECT *, row_number() OVER (PARTITION BY symbolid, direction ORDER BY datetime DESC) r FROM sa_hist_consecutivecandles ) SELECT DISTINCT a.symbolid, a.qty, a.percentile, a.direction FROM a INNER JOIN symbols s on a.symbolid = s.symbolid INNER JOIN autochartist_stocklist aus on s.symbolid = aus.symbolid WHERE aus.Enabled = 1 AND a.r = 1 AND aus.RecognitionEngine ILIKE 'DXFEED_FX - 1';

Date: 2026-01-27 04:05:19 Duration: 0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

25,726

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 27	04	25,726	0ms	0ms

2

14,707

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 27	04	14,707	0ms	0ms

3

7,791

Details

0ms

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

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Jan 27	04	7,791	0ms	0ms

4

6,251

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 #4

Day	Hour	Count	Duration	Avg duration
Jan 27	04	6,251	0ms	0ms

5

5,500

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 #5

Day	Hour	Count	Duration	Avg duration
Jan 27	04	5,500	0ms	0ms

6

4,205

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Jan 27	04	4,205	0ms	0ms

7

4,179

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Jan 27	04	4,179	0ms	0ms

8

4,094

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 #8

Day	Hour	Count	Duration	Avg duration
Jan 27	04	4,094	0ms	0ms

9

3,562

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 #9

Day	Hour	Count	Duration	Avg duration
Jan 27	04	3,562	0ms	0ms

10

3,396

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 #10

Day	Hour	Count	Duration	Avg duration
Jan 27	04	3,396	0ms	0ms

11

3,200

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 #11

Day	Hour	Count	Duration	Avg duration
Jan 27	04	3,200	0ms	0ms

12

3,118

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 #12

Day	Hour	Count	Duration	Avg duration
Jan 27	04	3,118	0ms	0ms

13

3,014

Details

0ms

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

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Jan 27	04	3,014	0ms	0ms

14

2,092

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 27	04	2,092	0ms	0ms

15

1,557

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 #15

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1,557	0ms	0ms

16

1,187

Details

0ms

insert into t240 (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 #16

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1,187	0ms	0ms

17

1,012

Details

0ms

select pricedatetime, open, high, low, close, volume, bsf from t60 where symbolid = ? and pricedatetime > ? order by pricedatetime asc;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1,012	0ms	0ms

18

1,012

Details

0ms

select pricedatetime, open, high, low, close, volume, bsf from t1440 where symbolid = ? and pricedatetime > ? order by pricedatetime asc;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1,012	0ms	0ms

19

1,012

Details

0ms

select pricedatetime, open, high, low, close, volume, bsf from t240 where symbolid = ? and pricedatetime > ? order by pricedatetime asc;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1,012	0ms	0ms

20

1,006

Details

0ms

select pricedatetime, open, high, low, close, volume, bsf from t15 where symbolid = ? and pricedatetime > ? order by pricedatetime asc;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1,006	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

1

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1	0ms	0ms

2

0ms

32

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 27	04	32	0ms	0ms

3

0ms

4

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 27	04	4	0ms	0ms

4

0ms

1

Details

0ms

select distinct a.resultuid, a.breakoutbars, a.patternid, cast(a.x0 as timestamp) as x0, cast(a.x1 as timestamp) as x1, cast(x2 as timestamp) as x2, case when (x3 != ? and x3 != ?) then cast(x3 as timestamp) else cast(? as timestamp) end as x3, case when (x4 != ? and x4 != ?) then cast(x4 as timestamp) else cast(? as timestamp) end as x4, case when (x5 != ? and x5 != ?) then cast(x5 as timestamp) else cast(? as timestamp) end as x5, case when (x6 != ? and x6 != ?) then cast(x6 as timestamp) else cast(? as timestamp) end as x6, case when (x7 != ? and x7 != ?) then cast(x7 as timestamp) else cast(? as timestamp) end as x7, case when (x8 != ? and x8 != ?) then cast(x8 as timestamp) else cast(? as timestamp) end as x8, case when (x9 != ? and x9 != ?) then cast(x9 as timestamp) else cast(? as timestamp) end as x9, cast(a.atbaridentified as timestamp) as atbaridentified, cast(a.patternstarttime as timestamp) as patternstarttime, a.breakoutprice, a.symbolid, a.approachingregion, a.patternprice, a.errormargin, a.bandwidth, a.qtytp, a.patternlengthbars, a.symbolid, a.uniquepointsvalue, a.predictionpricefrom, a.predictionpriceto, a.breakout, a.direction, a.furthestprice, a.approachingtimestamp, a.atpriceidentified from keylevels_results a inner join symbols s on a.symbolid = s.symbolid inner join autochartist_stocklist aus on s.symbolid = aus.symbolid left outer join relevance_keylevels_results rkl on a.resultuid = rkl.resultuid where aus.enabled = ? and (rkl.relevant = ? or a.resultuid > ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?)) and aus.recognitionengine ilike ?;

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1	0ms	0ms

5

0ms

2,092

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Jan 27	04	2,092	0ms	0ms

6

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 #6

Day	Hour	Count	Duration	Avg duration
Jan 27	04	48	0ms	0ms

7

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Jan 27	04	4	0ms	0ms

8

0ms

31

Details

0ms

set client_encoding to ?;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Jan 27	04	31	0ms	0ms

9

0ms

1,012

Details

0ms

select pricedatetime, open, high, low, close, volume, bsf from t60 where symbolid = ? and pricedatetime > ? order by pricedatetime asc;

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1,012	0ms	0ms

10

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 #10

Day	Hour	Count	Duration	Avg duration
Jan 27	04	18	0ms	0ms

11

0ms

1

Details

0ms

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

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1	0ms	0ms

12

0ms

367

Details

0ms

commit;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 27	04	367	0ms	0ms

13

0ms

400

Details

0ms

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

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Jan 27	04	400	0ms	0ms

14

0ms

240

Details

0ms

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

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Jan 27	04	240	0ms	0ms

15

0ms

1

Details

0ms

listen "ATFX - ?";

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1	0ms	0ms

16

0ms

240

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Jan 27	04	240	0ms	0ms

17

0ms

31

Details

0ms

set session characteristics as transaction isolation level read uncommitted;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 27	04	31	0ms	0ms

18

0ms

5

Details

0ms

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

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Jan 27	04	5	0ms	0ms

19

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;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Jan 27	04	2	0ms	0ms

20

0ms

1

Details

0ms

with a as ( select *, row_number() over (partition by symbolid, direction order by datetime desc) r from sa_hist_consecutivecandles ) select distinct a.symbolid, a.qty, a.percentile, a.direction from a inner join symbols s on a.symbolid = s.symbolid inner join autochartist_stocklist aus on s.symbolid = aus.symbolid where aus.enabled = ? and a.r = ? and aus.recognitionengine ilike ?;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 27	04	1	0ms	0ms

WITH a AS ( SELECT *, row_number() OVER (PARTITION BY symbolid, direction ORDER BY datetime DESC) r FROM sa_hist_consecutivecandles ) SELECT DISTINCT a.symbolid, a.qty, a.percentile, a.direction FROM a INNER JOIN symbols s on a.symbolid = s.symbolid INNER JOIN autochartist_stocklist aus on s.symbolid = aus.symbolid WHERE aus.Enabled = 1 AND a.r = 1 AND aus.RecognitionEngine ILIKE 'DXFEED_FX - 1';

Date: 2026-01-27 04:05:19 Duration: 0ms

Time consuming prepare


Date: 2026-01-27 04:30:56
Duration: 20ms
Database: postgres
Date: 2026-01-27 04:30:46
Duration: 15ms
Database: postgres
Date: 2026-01-27 04:47:14
Duration: 2ms
Database: postgres
Date: 2026-01-27 04:11:12
Duration: 13ms
Database: postgres
Date: 2026-01-27 04:45:53
Duration: 1ms
Database: postgres
Date: 2026-01-27 04:01:08
Duration: 4ms
Database: postgres
Date: 2026-01-27 04:41:40
Duration: 0ms
Database: postgres
Date: 2026-01-27 04:30:52
Duration: 1ms
Database: postgres
Date: 2026-01-27 04:47:08
Duration: 0ms
Database: postgres
Date: 2026-01-27 04:00:57
Duration: 1ms
Database: postgres
Date: 2026-01-27 04:21:42
Duration: 7ms
Database: postgres
Date: 2026-01-27 04:46:10
Duration: 1ms
Database: postgres
Date: 2026-01-27 04:20:03
Duration: 3ms
Database: postgres
Date: 2026-01-27 04:37:59
Duration: 1ms
Database: postgres
Date: 2026-01-27 04:37:59
Duration: 1ms
Database: postgres
Date: 2026-01-27 04:10:02
Duration: 3ms
Database: postgres
Date: 2026-01-27 04:10:05
Duration: 3ms
Database: postgres
Date: 2026-01-27 04:30:02
Duration: 0ms
Database: postgres
Date: 2026-01-27 04:13:09
Duration: 2ms
Database: postgres
Date: 2026-01-27 04:52:01
Duration: 2ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

45s110ms

7,159

Details

0ms

40ms

6ms

WITH rar_max as ( ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Jan 27	04	7,159	45s110ms	6ms

WITH rar_max as ( ;

Date: 2026-01-27 04:46:10 Duration: 40ms Database: postgres parameters: $1 = '607566780724662301', $2 = '607566780724662301', $3 = '607566780724662301'
WITH rar_max as ( ;

Date: 2026-01-27 04:46:10 Duration: 40ms Database: postgres parameters: $1 = '607572230344747301', $2 = '607572230344747301', $3 = '607572230344747301'
WITH rar_max as ( ;

Date: 2026-01-27 04:20:47 Duration: 40ms Database: postgres parameters: $1 = '607555351846124303', $2 = '607555351846124303', $3 = '607555351846124303'

2

14s295ms

21,116

Details

0ms

28ms

0ms

SELECT ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	04	21,116	14s295ms	0ms

SELECT ;

Date: 2026-01-27 04:12:02 Duration: 28ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840243162686300'
SELECT ;

Date: 2026-01-27 04:21:06 Duration: 26ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840233379186300'
SELECT ;

Date: 2026-01-27 04:12:02 Duration: 25ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840216980948300'

3

2s468ms

1,006

Details

1ms

19ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	04	1,006	2s468ms	2ms

SELECT symbolid, ;

Date: 2026-01-27 04:00:03 Duration: 19ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'NZDUSD', $4 = 'SHBUSD', $5 = 'SOLUSD'
SELECT symbolid, ;

Date: 2026-01-27 04:32:26 Duration: 6ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'USDJPY', $4 = 'USDCHF.ID', $5 = 'USDJPY.ID', $6 = 'XAGUSD', $7 = 'USDCHF.FX', $8 = 'USDJPY.FX'
SELECT symbolid, ;

Date: 2026-01-27 04:00:06 Duration: 5ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'VIX'

4

802ms

455

Details

1ms

2ms

1ms

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

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	04	455	802ms	1ms

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

Date: 2026-01-27 04:31:02 Duration: 2ms Database: postgres parameters: $1 = 'HOTFOREX'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-01-27 04:02:03 Duration: 2ms Database: postgres parameters: $1 = 'FPMARKETS'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-01-27 04:01:00 Duration: 2ms Database: postgres parameters: $1 = 'PEPPERSTONE'

5

593ms

25,594

Details

0ms

2ms

0ms

select 1;

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	04	25,594	593ms	0ms

select 1;

Date: 2026-01-27 04:07:47 Duration: 2ms Database: postgres
select 1;

Date: 2026-01-27 04:30:46 Duration: 1ms Database: postgres
select 1;

Date: 2026-01-27 04:17:37 Duration: 1ms Database: postgres

6

539ms

90

Details

4ms

10ms

5ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	04	90	539ms	5ms

WITH last_candle AS ( ;

Date: 2026-01-27 04:36:01 Duration: 10ms Database: postgres parameters: $1 = '667', $2 = '667'
WITH last_candle AS ( ;

Date: 2026-01-27 04:52:01 Duration: 10ms Database: postgres parameters: $1 = '538', $2 = '538'
WITH last_candle AS ( ;

Date: 2026-01-27 04:16:00 Duration: 9ms Database: postgres parameters: $1 = '558', $2 = '558'

7

457ms

22

Details

0ms

48ms

20ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	04	22	457ms	20ms

with wh_patitioned as ( ;

Date: 2026-01-27 04:00:02 Duration: 48ms 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: 2026-01-27 04:10:02 Duration: 40ms 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: 2026-01-27 04:10:01 Duration: 35ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'

8

421ms

56

Details

0ms

20ms

7ms

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

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	04	56	421ms	7ms

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

Date: 2026-01-27 04:36:18 Duration: 20ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;

Date: 2026-01-27 04:33:34 Duration: 19ms Database: postgres parameters: $1 = '489', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;

Date: 2026-01-27 04:22:29 Duration: 18ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

9

395ms

12

Details

28ms

45ms

32ms

with sym_info as ( ;

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	04	12	395ms	32ms

with sym_info as ( ;

Date: 2026-01-27 04:51:44 Duration: 45ms 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: 2026-01-27 04:51:47 Duration: 45ms Database: postgres parameters: $1 = '617', $2 = 'Forex', $3 = 'Forex', $4 = '617', $5 = 'Forex', $6 = '617', $7 = '617', $8 = 'Forex', $9 = '617'
with sym_info as ( ;

Date: 2026-01-27 04:21:42 Duration: 38ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'

10

239ms

5,500

Details

0ms

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

Times Reported Time consuming bind #10

Day	Hour	Count	Duration	Avg duration
	04	5,500	239ms	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: 2026-01-27 04:47:08 Duration: 0ms Database: postgres parameters: $1 = '2026-01-26 21:00:00', $2 = '45109.99', $3 = '45125.01', $4 = '45104.99', $5 = '45125.01', $6 = '90', $7 = '500991628285199200', $8 = '0', $9 = '2026-01-27 04:47:08.36', $10 = '2026-01-27 04:47:08.296', $11 = '45109.99', $12 = '45125.01', $13 = '45104.99', $14 = '45125.01', $15 = '90', $16 = '0', $17 = '2026-01-27 04:47:08.36', $18 = '2026-01-27 04:47:08.296'
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: 2026-01-27 04:41:52 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 04:15:00', $2 = '6960.28', $3 = '6961.6', $4 = '6959.28', $5 = '6960.53', $6 = '1827', $7 = '515840248032019300', $8 = '0', $9 = '2026-01-27 04:41:52.796', $10 = '2026-01-27 04:41:52.707', $11 = '6960.28', $12 = '6961.6', $13 = '6959.28', $14 = '6960.53', $15 = '1827', $16 = '0', $17 = '2026-01-27 04:41:52.796', $18 = '2026-01-27 04:41:52.707'
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: 2026-01-27 04:56:39 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 04:30:00', $2 = '8946.4', $3 = '8949.4', $4 = '8938.15', $5 = '8939.4', $6 = '1105', $7 = '515840248015086300', $8 = '0', $9 = '2026-01-27 04:56:39.889', $10 = '2026-01-27 04:56:39.812', $11 = '8946.4', $12 = '8949.4', $13 = '8938.15', $14 = '8939.4', $15 = '1105', $16 = '0', $17 = '2026-01-27 04:56:39.889', $18 = '2026-01-27 04:56:39.812'

11

237ms

3,200

Details

0ms

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

Times Reported Time consuming bind #11

Day	Hour	Count	Duration	Avg duration
	04	3,200	237ms	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: 2026-01-27 04:41:40 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 03:30:00', $2 = '8950.45', $3 = '8961.4', $4 = '8945.4', $5 = '8957.65', $6 = '2272', $7 = '515840248015340300', $8 = '0', $9 = '2026-01-27 04:41:40.698', $10 = '2026-01-27 04:41:40.605', $11 = '8950.45', $12 = '8961.4', $13 = '8945.4', $14 = '8957.65', $15 = '2272', $16 = '0', $17 = '2026-01-27 04:41:40.698', $18 = '2026-01-27 04:41:40.605'
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: 2026-01-27 04:30:26 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 04:00:00', $2 = '0.77702', $3 = '0.77709', $4 = '0.77598', $5 = '0.77605', $6 = '778', $7 = '515840217696921300', $8 = '0', $9 = '2026-01-27 04:30:26.431', $10 = '2026-01-27 04:30:26.431', $11 = '0.77702', $12 = '0.77709', $13 = '0.77598', $14 = '0.77605', $15 = '778', $16 = '0', $17 = '2026-01-27 04:30:26.431', $18 = '2026-01-27 04:30:26.431'
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: 2026-01-27 04:31:22 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 04:00:00', $2 = '0.59678', $3 = '0.59741', $4 = '0.59652', $5 = '0.59728', $6 = '1526', $7 = '515840230542099300', $8 = '0', $9 = '2026-01-27 04:31:22.928', $10 = '2026-01-27 04:31:22.928', $11 = '0.59678', $12 = '0.59741', $13 = '0.59652', $14 = '0.59728', $15 = '1526', $16 = '0', $17 = '2026-01-27 04:31:22.928', $18 = '2026-01-27 04:31:22.928'

12

159ms

2,092

Details

0ms

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

Times Reported Time consuming bind #12

Day	Hour	Count	Duration	Avg duration
	04	2,092	159ms	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: 2026-01-27 04:00:53 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 04:00:00', $2 = '1417873.83', $3 = '1423249.005', $4 = '1415592.225', $5 = '1420655.74', $6 = '5031', $7 = '515840249474180300', $8 = '0', $9 = '2026-01-27 04:00:53.431', $10 = '2026-01-27 04:00:53.431', $11 = '1417873.83', $12 = '1423249.005', $13 = '1415592.225', $14 = '1420655.74', $15 = '5031', $16 = '0', $17 = '2026-01-27 04:00:53.431', $18 = '2026-01-27 04:00:53.431'
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: 2026-01-27 04:11:39 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 02:00:00', $2 = '8962.4', $3 = '8966.45', $4 = '8947.4', $5 = '8950.4', $6 = '6098', $7 = '515840248015562300', $8 = '0', $9 = '2026-01-27 04:11:39.576', $10 = '2026-01-27 04:11:39.464', $11 = '8962.4', $12 = '8966.45', $13 = '8947.4', $14 = '8950.4', $15 = '6098', $16 = '0', $17 = '2026-01-27 04:11:39.576', $18 = '2026-01-27 04:11:39.464'
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: 2026-01-27 04:00:35 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 03:00:00', $2 = '183.242', $3 = '183.349', $4 = '183.199', $5 = '183.337', $6 = '14082', $7 = '515840243882378300', $8 = '0', $9 = '2026-01-27 04:00:35.696', $10 = '2026-01-27 04:00:35.664', $11 = '183.242', $12 = '183.349', $13 = '183.199', $14 = '183.337', $15 = '14082', $16 = '0', $17 = '2026-01-27 04:00:35.696', $18 = '2026-01-27 04:00:35.664'

13

108ms

1,187

Details

0ms

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

Times Reported Time consuming bind #13

Day	Hour	Count	Duration	Avg duration
	04	1,187	108ms	0ms

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

Date: 2026-01-27 04:17:24 Duration: 0ms Database: postgres parameters: $1 = '2026-01-26 16:00:00', $2 = '52620', $3 = '52755', $4 = '52535', $5 = '52625', $6 = '3361', $7 = '515840230561612300', $8 = '0', $9 = '2026-01-27 04:17:24.983', $10 = '2026-01-27 04:17:24.982', $11 = '52620', $12 = '52755', $13 = '52535', $14 = '52625', $15 = '3361', $16 = '0', $17 = '2026-01-27 04:17:24.983', $18 = '2026-01-27 04:17:24.982'
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-01-27 04:10:28 Duration: 0ms Database: postgres parameters: $1 = '2026-01-26 16:00:00', $2 = '302.57', $3 = '306.21', $4 = '301.97', $5 = '304.6', $6 = '7341', $7 = '515840247900029300', $8 = '0', $9 = '2026-01-27 04:10:28.719', $10 = '2026-01-27 04:10:28.634', $11 = '302.57', $12 = '306.21', $13 = '301.97', $14 = '304.6', $15 = '7341', $16 = '0', $17 = '2026-01-27 04:10:28.719', $18 = '2026-01-27 04:10:28.634'
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-01-27 04:17:40 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 00:00:00', $2 = '6942.4', $3 = '6958.8', $4 = '6941.6', $5 = '6958.3', $6 = '4594', $7 = '515840245924751300', $8 = '0', $9 = '2026-01-27 04:17:40.56', $10 = '2026-01-27 04:17:40.559', $11 = '6942.4', $12 = '6958.8', $13 = '6941.6', $14 = '6958.3', $15 = '4594', $16 = '0', $17 = '2026-01-27 04:17:40.56', $18 = '2026-01-27 04:17:40.559'

14

67ms

79

Details

0ms

1ms

0ms

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

Times Reported Time consuming bind #14

Day	Hour	Count	Duration	Avg duration
	04	79	67ms	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: 2026-01-27 04:47:05 Duration: 1ms Database: postgres parameters: $1 = '538', $2 = 'GBPUSD', $3 = '538'
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: 2026-01-27 04:15:20 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'EURJPY', $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: 2026-01-27 04:31:09 Duration: 1ms Database: postgres parameters: $1 = '632', $2 = 'GBPUSD', $3 = '632'

15

52ms

11

Details

3ms

7ms

4ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #15

Day	Hour	Count	Duration	Avg duration
	04	11	52ms	4ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-27 04:12:32 Duration: 7ms Database: postgres parameters: $1 = '958', $2 = '958'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-27 04:46:04 Duration: 6ms Database: postgres parameters: $1 = '627', $2 = '627'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-27 04:51:00 Duration: 6ms Database: postgres parameters: $1 = '627', $2 = '627'

16

35ms

1

Details

35ms

with maxwhid as ( ;

Times Reported Time consuming bind #16

Day	Hour	Count	Duration	Avg duration
	04	1	35ms	35ms

with maxwhid as ( ;

Date: 2026-01-27 04:12:46 Duration: 35ms Database: postgres parameters: $1 = '335', $2 = '621', $3 = '637', $4 = '642', $5 = '666', $6 = '660', $7 = '643', $8 = '630', $9 = '680', $10 = '641', $11 = '431', $12 = '622', $13 = '489', $14 = '529', $15 = '576', $16 = '665', $17 = '667', $18 = '558', $19 = '620', $20 = '125', $21 = '488', $22 = '567', $23 = '689', $24 = '700', $25 = '758', $26 = '763', $27 = '765', $28 = '817', $29 = '914', $30 = '972'

17

30ms

8

Details

2ms

7ms

3ms

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

Times Reported Time consuming bind #17

Day	Hour	Count	Duration	Avg duration
	04	8	30ms	3ms

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

Date: 2026-01-27 04:13:09 Duration: 7ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'
WITH pre_symbols AS ( /* find relevant symbols */ ;

Date: 2026-01-27 04:13:09 Duration: 5ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD'
WITH pre_symbols AS ( /* find relevant symbols */ ;

Date: 2026-01-27 04:13:10 Duration: 3ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'

18

28ms

4,205

Details

0ms

2ms

0ms

SET extra_float_digits = 3;

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	04	4,205	28ms	0ms

SET extra_float_digits = 3;

Date: 2026-01-27 04:47:26 Duration: 2ms Database: postgres
SET extra_float_digits = 3;

Date: 2026-01-27 04:46:10 Duration: 2ms Database: postgres
SET extra_float_digits = 3;

Date: 2026-01-27 04:43:41 Duration: 2ms Database: postgres

19

27ms

6

Details

3ms

5ms

4ms

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;

Times Reported Time consuming bind #19

Day	Hour	Count	Duration	Avg duration
	04	6	27ms	4ms

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: 2026-01-27 04:50:02 Duration: 5ms Database: postgres
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: 2026-01-27 04:10:02 Duration: 5ms Database: postgres
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: 2026-01-27 04:30:02 Duration: 4ms Database: postgres

20

22ms

39

Details

0ms

2ms

0ms

WITH tr_max AS ( ;

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	04	39	22ms	0ms

WITH tr_max AS ( ;

Date: 2026-01-27 04:13:10 Duration: 2ms Database: postgres parameters: $1 = '606715250232663300', $2 = '606715250232663300', $3 = '606715250232663300', $4 = '1', $5 = '1', $6 = '1320', $7 = 't', $8 = '1320'
WITH tr_max AS ( ;

Date: 2026-01-27 04:13:10 Duration: 1ms Database: postgres parameters: $1 = '606715250644110300', $2 = '606715250644110300', $3 = '606715250644110300', $4 = '1', $5 = '1', $6 = '1320', $7 = 't', $8 = '1320'
WITH tr_max AS ( ;

Date: 2026-01-27 04:13:12 Duration: 1ms Database: postgres parameters: $1 = '606715251031835300', $2 = '606715251031835300', $3 = '606715251031835300', $4 = '1', $5 = '1', $6 = '1320', $7 = 't', $8 = '1320'

Log levels

Key values

455,498 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	589	0.13%
DETAIL	88,059	19.33%
ERROR	36	0.01%
HINT	34	0.01%
LOG	366,017	80.36%
STATEMENT	763	0.17%

Events distribution

Key values

0 PANIC entries
0 FATAL entries
36 ERROR entries
0 WARNING entries

Most Frequent Errors/Events

Key values

34 Max number of times the same event was reported
36 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 27	04	34

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

2

1

Details

ERROR: column "..." does not exist

Times Reported Most Frequent Error / Event #2

Day	Hour	Count
Jan 27	04	1

ERROR: column c.relhasoids does not exist at character 245

3

1

Details

ERROR: duplicate key value violates unique constraint "..."

Times Reported Most Frequent Error / Event #3

Day	Hour	Count
Jan 27	04	1

ERROR: duplicate key value violates unique constraint "ar_idx_sa_hist_conscandles_symbolid_datetime_direction"

Global information

Overview

Global Stats

SQL Traffic

Key values

SELECT Traffic

Key values

INSERT/UPDATE/DELETE Traffic

Key values

Queries duration

Key values

Prepared queries ratio

Key values

General Activity

Connections

Established Connections

Key values

Connections per database

Key values

Connections per user

Key values

Connections per host

Key values

Sessions

Simultaneous sessions

Key values

Histogram of session times

Key values

Sessions per database

Key values

Sessions per user

Key values

Sessions per host

Key values

Sessions per application

Key values

Checkpoints / Restartpoints

Checkpoints Buffers

Key values

Checkpoints Wal files

Key values

Checkpoints distance

Key values

Checkpoints Activity

Checkpoint causes

Key values

Temporary Files

Size of temporary files

Key values

Number of temporary files

Key values

Temporary Files Activity

Queries generating the most temporary files (N)

Queries generating the largest temporary files

Vacuums

Vacuums / Analyzes Distribution

Key values

Analyzes per table

Key values

Vacuums per table

Key values

Tuples removed per table

Key values

Pages removed per table

Key values

Autovacuum Activity

Locks

Locks by types

Key values

Type of locks

Most frequent waiting queries (N)

Queries that waited the most

Queries

Queries by type

Key values

Queries by database

Key values

Queries by user

Key values

Duration by user