pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Tue Jan 27 04:59:42 2026
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-01-27_060000.log
Parsed 1,714,055 log entries in 41s
Log start from 2026-01-27 06:00:00 to 2026-01-27 06:59:40

Global Stats

1,042 Number of unique normalized queries
202,197 Number of queries
3h6m49s Total query duration
2026-01-27 06:00:00 First query
2026-01-27 06:59:40 Last query
4,963 queries/s at 2026-01-27 06:19:25 Query peak

3h6m49s Total query duration
1m24s Prepare/parse total duration
52s107ms Bind total duration
3h4m33s Execute total duration

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

37 Total number of automatic vacuums
50 Total number of automatic analyzes

628 Number temporary file
174.48 MiB Max size of temporary file
8.13 MiB Average size of temporary file

3,081 Total number of sessions
12 sessions at 2026-01-27 06:59:11 Session peak
3d11h24m46s Total duration of sessions
1m37s Average duration of sessions
65 Average queries per session
3s638ms Average queries duration per session
1m33s Average idle time per session

3,081 Total number of connections
34 connections/s at 2026-01-27 06:06:01 Connection peak
6 Total number of databases

SQL Traffic

Key values

4,963 queries/s Query Peak
2026-01-27 06:19:25 Date

SELECT Traffic

Key values

2,464 queries/s Query Peak
2026-01-27 06:19:25 Date

INSERT/UPDATE/DELETE Traffic

Key values

175 queries/s Query Peak
2026-01-27 06:30:50 Date

Queries duration

Key values

3h6m49s 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	06	202,197	0ms	14m13s	54ms	4m48s	6m22s	18m43s

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Jan 27	06	53,670	601	0ms	0ms	0ms	0ms

Day	Hour	INSERT	UPDATE	DELETE	COPY FROM	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Jan 27	06	30,848	2,317	13	78	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Jan 27	06	20,181	62,065	3.08	21.06%

Day	Hour	Count	Average / Second
Jan 27	06	3,081	0.86/s

Day	Hour	Count	Average Duration	Average idle time
Jan 27	06	3,081	1m37s	1m33s

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Established Connections

Key values

34 connections Connection Peak
2026-01-27 06:06:01 Date

Connections per database

Key values

acaweb_fx Main Database
3,081 connections Total

Chart
Table

Database	User	Count
acaweb_fx		2,982
	pg_dump	1
	postgres	2,634
	psql	347
acaweb_fx_integer		1
	pg_dump	1
postgres		3
	pg_dump	1
	psql	2
socialmedia		94
	pg_dump	1
	postgres	93
translations		1
	pg_dump	1

Connections per user

Key values

postgres Main User
3,081 connections Total

Chart
Table

User	Count
pg_dump	5
postgres	2,727
psql	349

Connections per host

Key values

192.168.4.142 Main host with 1081 connections
3,081 Total connections

Chart
Table

Host	Count
127.0.0.1	116
192.168.0.114	3
192.168.0.216	101
192.168.0.74	266
192.168.1.145	119
192.168.1.15	320
192.168.1.20	142
192.168.1.231	20
192.168.1.239	2
192.168.1.90	64
192.168.2.126	62
192.168.2.182	12
192.168.2.82	48
192.168.3.199	36
192.168.4.142	1,081
192.168.4.150	10
192.168.4.207	7
192.168.4.238	12
192.168.4.244	1
192.168.4.33	91
192.168.4.98	330
[local]	238

Simultaneous sessions

Key values

12 sessions Session Peak
2026-01-27 06:59:11 Date

Histogram of session times

Key values

2,432 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	2,432	78.94%
500ms-1s	150	4.87%
1s-30s	334	10.84%
30s-1m	24	0.78%
1m-10m	63	2.04%
10m-30m	62	2.01%
30m-1h	2	0.06%
1h-8h	13	0.42%
> 8h	1	0.03%

Sessions per database

Key values

acaweb_fx Main Database
3,081 sessions Total

Chart
Table

Database	User	Count	Total Duration
acaweb_fx	2,982	3d10h50m26s	1m40s
acaweb_fx_integer	1	19m44s	19m44s
postgres	3	276ms	92ms
socialmedia	94	14m35s	9s309ms
translations	1	186ms	186ms

Sessions per user

Key values

postgres Main User
3,081 sessions Total

Chart
Table

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

Sessions per host

Key values

192.168.4.142 Main Host
3,081 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
127.0.0.1	116	36m19s	18s791ms
192.168.0.114	3	15m1s	5m
192.168.0.216	101	52s436ms	519ms
192.168.0.74	266	3h3m11s	41s320ms
192.168.1.145	119	8h5s	4m2s
192.168.1.15	320	7h9m2s	1m20s
192.168.1.20	142	1d9h37m43s	14m12s
192.168.1.231	20	9h53m50s	29m41s
192.168.1.239	2	27ms	13ms
192.168.1.90	64	2m30s	2s355ms
192.168.2.126	62	6s567ms	105ms
192.168.2.182	12	878ms	73ms
192.168.2.82	48	13s931ms	290ms
192.168.3.199	36	1s338ms	37ms
192.168.4.142	1,081	8m19s	462ms
192.168.4.150	10	20h12m35s	2h1m15s
192.168.4.207	7	36s50ms	5s150ms
192.168.4.238	12	15s707ms	1s308ms
192.168.4.244	1	290ms	290ms
192.168.4.33	91	2m29s	1s643ms
192.168.4.98	330	33s95ms	100ms
[local]	238	20m56s	5s280ms

Sessions per application

Key values

unknown Main Host
3,081 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	3,081	3d11h24m46s	1m37s

Checkpoints Buffers

Key values

12,472 buffers Checkpoint Peak
2026-01-27 06:07:51 Date
209.872 seconds Highest write time
0.015 seconds Sync time

Checkpoints Wal files

Key values

6 files Wal files usage Peak
2026-01-27 06:07:51 Date

Checkpoints distance

Key values

188.11 Mo Distance Peak
2026-01-27 06:07:51 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Jan 27	06	33,686	1,779.364s	0.051s	1,779.751s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Jan 27	06	0	0	23	1,853	0.006s	0s

Day	Hour	Count	Avg time (sec)
Jan 27	06	0	0s

Day	Hour	Mean distance	Mean estimate
Jan 27	06	31,771.50 kB	74,487.58 kB

↑ Back to the top of the Checkpoint Activity table

Checkpoint causes

Key values

time (12) Main checkpoint cause
12 checkpoints Total

Chart
Table

Cause	Number of checkpoints
time	12
Total	12

Size of temporary files

Key values

183.85 MiB Temp Files size Peak
2026-01-27 06:40:27 Date

Number of temporary files

Key values

30 per second Temp Files Peak
2026-01-27 06:17:23 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Jan 27	06	628	4.99 GiB	8.13 MiB

↑ Back to the top of the Temporary Files Activity table

Queries generating the most temporary files (N)

Rank	Count	Total size	Min size	Max size	Avg size	Query
1	35	134.66 MiB	3.84 MiB	3.86 MiB	3.85 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 06:00:52 Duration: 0ms
2	28	1.66 GiB	8.41 MiB	174.48 MiB	60.66 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 = ? ), 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 06:00:06 Duration: 0ms
3	21	156.19 MiB	7.43 MiB	7.44 MiB	7.44 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 06:00:28 Duration: 0ms
4	13	599.02 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 06:01:14 Duration: 0ms
5	13	1016.62 MiB	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 06:01:16 Duration: 0ms
6	8	1017.87 MiB	127.22 MiB	127.25 MiB	127.23 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2026-01-27 06:02:19 Duration: 0ms
7	4	333.89 MiB	83.42 MiB	83.52 MiB	83.47 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2026-01-27 06:02:07 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	174.48 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 06:20:09 ]
2	166.14 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 06:40:24 ]
3	163.68 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 06:00:06 ]
4	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 06:10:13 ]
5	156.41 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 06:50:11 ]
6	127.25 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 06:47:35 ]
7	127.25 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 06:32:41 ]
8	127.24 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 06:17:30 ]
9	127.24 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 06:02:19 ]
10	127.23 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 06:35:42 ]
11	127.23 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 06:50:35 ]
12	127.22 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 06:05:34 ]
13	127.22 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-27 06:20:39 ]
14	102.12 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 06:30:07 ]
15	83.52 MiB	select updateageforrelevantresults (); [ Date: 2026-01-27 06:32:25 ]
16	83.52 MiB	select updateageforrelevantresults (); [ Date: 2026-01-27 06:02:07 ]
17	83.43 MiB	select updateageforrelevantresults (); [ Date: 2026-01-27 06:17:16 ]
18	83.42 MiB	select updateageforrelevantresults (); [ Date: 2026-01-27 06:47:23 ]
19	81.11 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 06:30:09 ]
20	78.20 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-01-27 06:19:31 ]

Vacuums / Analyzes Distribution

Key values

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

Analyzes per table

Key values

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

Chart
Table

Table	Number of analyzes
acaweb_fx.public.solr_relevance_old	13
acaweb_fx.pg_catalog.pg_attribute	5
acaweb_fx.public.relevance_keylevels_results	4
acaweb_fx.pg_catalog.pg_class	4
acaweb_fx.public.relevance_fibonacci_results	4
acaweb_fx.public.relevance_autochartist_results	4
acaweb_fx.public.datafeeds_latestrun	3
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.fibonacci_results	1
acaweb_fx.public.symbollatestupdatetime	1
Total	50

Vacuums per table

Key values

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

Chart
Table

		Index	Buffer usage			Skipped		WAL usage
Table	Vacuums	scans	hits	misses	dirtied	pins	frozen	records	full page	bytes
acaweb_fx.public.solr_relevance_old	13	12	10,716	0	39	0	0	7,391	12	1,303,832
acaweb_fx.public.datafeeds_latestrun	5	0	587	0	16	0	0	55	35	71,428
acaweb_fx.public.relevance_autochartist_results	3	3	9,908	0	565	0	705	2,201	1,006	2,973,856
acaweb_fx.pg_toast.pg_toast_2619	2	2	306	0	63	0	0	148	50	187,381
acaweb_fx.pg_catalog.pg_attribute	2	2	1,541	0	373	0	134	771	278	1,662,466
acaweb_fx.public.relevance_keylevels_results	2	2	7,305	0	307	2	179	1,971	223	781,879
acaweb_fx.pg_catalog.pg_class	2	2	924	0	97	0	0	283	93	469,540
acaweb_fx.public.relevance_fibonacci_results	2	2	2,570	0	46	0	103	460	26	103,157
acaweb_fx.pg_catalog.pg_index	1	1	92	0	14	0	0	28	12	88,827
acaweb_fx.pg_catalog.pg_type	1	1	141	0	19	0	0	53	11	70,442
acaweb_fx.public.autochartist_symbolupdates	1	1	24,126	0	758	2	38,253	6,740	641	646,104
acaweb_fx.pg_catalog.pg_statistic	1	1	923	0	209	0	594	570	194	728,229
acaweb_fx.public.relevance_consecutivecandles_results	1	1	72	0	11	1	0	23	7	39,742
acaweb_fx.public.latest_t15_candle_view	1	1	66	0	1	0	0	6	1	9,067
Total	37	31	59,277	48,748	2,518	5	39,968	20,700	2,589	9,135,950

Tuples removed per table

Key values

public.solr_relevance_old (53575) Main table with removed tuples on database acaweb_fx
71960 tuples Total removed

Chart
Table

		Index	Tuples			Pages
Table	Vacuums	scans	removed	remain	not yet removable	removed	remain
acaweb_fx.public.solr_relevance_old	13	12	53,575	84,692	8,632	0	2,705
acaweb_fx.public.autochartist_symbolupdates	1	1	5,447	48,666	24	0	40,691
acaweb_fx.public.relevance_keylevels_results	2	2	3,826	25,488	0	0	558
acaweb_fx.pg_catalog.pg_attribute	2	2	3,521	21,714	0	40	480
acaweb_fx.public.relevance_autochartist_results	3	3	3,128	26,280	181	0	1,140
acaweb_fx.pg_catalog.pg_statistic	1	1	748	3,766	0	0	1,194
acaweb_fx.public.relevance_fibonacci_results	2	2	686	3,128	0	0	204
acaweb_fx.pg_catalog.pg_class	2	2	462	3,433	135	0	300
acaweb_fx.public.datafeeds_latestrun	5	0	230	146	76	0	80
acaweb_fx.pg_catalog.pg_type	1	1	135	1,446	0	2	38
acaweb_fx.pg_toast.pg_toast_2619	2	2	116	381	45	0	100
acaweb_fx.public.latest_t15_candle_view	1	1	61	14	0	0	1
acaweb_fx.public.relevance_consecutivecandles_results	1	1	22	259	0	0	7
acaweb_fx.pg_catalog.pg_index	1	1	3	825	12	0	22
Total	37	31	71,960	220,238	9,105	42	47,520

Pages removed per table

Key values

pg_catalog.pg_attribute (40) Main table with removed pages on database acaweb_fx
42 pages Total removed

Chart
Table

Table	Number of vacuums	Index scans	Tuples removed	Pages removed
acaweb_fx.pg_catalog.pg_attribute	2	2	3521	40
acaweb_fx.pg_catalog.pg_type	1	1	135	2
acaweb_fx.pg_toast.pg_toast_2619	2	2	116	0
acaweb_fx.pg_catalog.pg_index	1	1	3	0
acaweb_fx.public.datafeeds_latestrun	5	0	230	0
acaweb_fx.public.autochartist_symbolupdates	1	1	5447	0
acaweb_fx.pg_catalog.pg_statistic	1	1	748	0
acaweb_fx.public.relevance_consecutivecandles_results	1	1	22	0
acaweb_fx.public.latest_t15_candle_view	1	1	61	0
acaweb_fx.public.relevance_keylevels_results	2	2	3826	0
acaweb_fx.pg_catalog.pg_class	2	2	462	0
acaweb_fx.public.solr_relevance_old	13	12	53575	0
acaweb_fx.public.relevance_autochartist_results	3	3	3128	0
acaweb_fx.public.relevance_fibonacci_results	2	2	686	0
Total	37	31	71,960	42

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Jan 27	06	37	50

↑ Back to the top of the Autovacuum Activity table

Locks by types

Key values

AccessExclusiveLock Main Lock Type
3 locks Total

Chart
Table

Type	Object	Count	Total Duration	Average Duration (s)
AccessExclusiveLock		2	16m35s	8m17s
	relation	2	16m35s	8m17s
AccessShareLock		1	1m16s	1m16s
	relation	1	1m16s	1m16s
	Total	3	17m52s	5m57s

Most frequent waiting queries (N)

Rank	Count	Total time	Min time	Max time	Avg duration	Query
1	1	14m13s	14m13s	14m13s	14m13s	truncate table solr_relevance_old; TRUNCATE TABLE solr_relevance_old; Date: 2026-01-27 06:19:24
2	1	2m22s	2m22s	2m22s	2m22s	refresh materialized view latest_candle_datetime_per_receng; refresh materialized view latest_candle_datetime_per_receng; Date: 2026-01-27 06:19:24
3	1	1m16s	1m16s	1m16s	1m16s	select recognitionengine, to_char(datetimeupdate, ?) from latest_candle_datetime_per_receng; select recognitionengine, to_char(datetimeupdate, 'yyyy-mm-dd HH24:MI') from latest_candle_datetime_per_receng; Date: 2026-01-27 06:19:25

Queries that waited the most

Rank	Wait time	Query
1	14m13s	TRUNCATE TABLE solr_relevance_old; [ Date: 2026-01-27 06:19:24 ]
2	2m22s	refresh materialized view latest_candle_datetime_per_receng; [ Date: 2026-01-27 06:19:24 ]
3	1m16s	select recognitionengine, to_char(datetimeupdate, 'yyyy-mm-dd HH24:MI') from latest_candle_datetime_per_receng; [ Date: 2026-01-27 06:19:25 ]

Queries by type

Key values

53,670 Total read queries
42,155 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	53,670	26.54%
INSERT	30,848	15.26%
UPDATE	2,317	1.15%
DELETE	13	0.01%
COPY FROM	78	0.04%
COPY TO	601	0.30%
CTE	7,602	3.76%
DDL	13	0.01%
TCL	683	0.34%
CURSOR	0	0.00%
OTHERS	106,372	52.61%

Queries by database

Key values

unknown Main database
201,220 Requests
3h4m33s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	878	0ms
	copy from	65	0ms
	copy to	26	0ms
	cte	85	0ms
	ddl	13	0ms
	delete	13	0ms
	others	203	0ms
	select	103	0ms
	tcl	331	0ms
	update	39	0ms
acaweb_fx_integer	Total	1	0ms
	select	1	0ms
postgres	Total	3	0ms
	select	3	0ms
socialmedia	Total	94	0ms
	select	92	0ms
	tcl	2	0ms
translations	Total	1	0ms
	select	1	0ms
unknown	Total	201,220	3h4m33s
	copy from	13	0ms
	copy to	575	0ms
	cte	7,517	0ms
	insert	30,848	0ms
	others	5,087	0ms
	select	53,470	0ms
	tcl	350	0ms
	update	2,278	0ms

Queries by user

Key values

unknown Main user
201,220 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	977	0ms
	copy from	65	0ms
	copy to	26	0ms
	cte	85	0ms
	ddl	13	0ms
	delete	13	0ms
	others	203	0ms
	select	200	0ms
	tcl	333	0ms
	update	39	0ms
unknown	Total	201,220	3h4m33s
	copy from	13	0ms
	copy to	575	0ms
	cte	7,517	0ms
	insert	30,848	0ms
	others	5,087	0ms
	select	53,470	0ms
	tcl	350	0ms
	update	2,278	0ms

Duration by user

Key values

3h4m33s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	977	0ms
	copy from	65	0ms
	copy to	26	0ms
	cte	85	0ms
	ddl	13	0ms
	delete	13	0ms
	others	203	0ms
	select	200	0ms
	tcl	333	0ms
	update	39	0ms
unknown	Total	201,220	3h4m33s
	copy from	13	0ms
	copy to	575	0ms
	cte	7,517	0ms
	insert	30,848	0ms
	others	5,087	0ms
	select	53,470	0ms
	tcl	350	0ms
	update	2,278	0ms

Queries by host

Key values

unknown Main host
202,197 Requests
3h4m33s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	202,197	3h4m33s
	copy from	78	0ms
	copy to	601	0ms
	cte	7,602	0ms
	ddl	13	0ms
	delete	13	0ms
	insert	30,848	0ms
	others	5,290	0ms
	select	53,670	0ms
	tcl	683	0ms
	update	2,317	0ms

Queries by application

Key values

unknown Main application
201,843 Requests
3h4m33s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
pg_dump	Total	5	0ms
	select	5	0ms
psql	Total	349	0ms
	copy from	65	0ms
	copy to	26	0ms
	cte	85	0ms
	ddl	13	0ms
	delete	13	0ms
	others	4	0ms
	select	104	0ms
	update	39	0ms
unknown	Total	201,843	3h4m33s
	copy from	13	0ms
	copy to	575	0ms
	cte	7,517	0ms
	insert	30,848	0ms
	others	5,286	0ms
	select	53,561	0ms
	tcl	683	0ms
	update	2,278	0ms

Number of cancelled queries

Key values

0 per second Cancelled query Peak
2026-01-27 06:12:36 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

64,733 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	64,733	64.04%
1-5ms	29,623	29.31%
5-10ms	2,438	2.41%
10-25ms	1,267	1.25%
25-50ms	527	0.52%
50-100ms	338	0.33%
100-500ms	673	0.67%
500-1000ms	236	0.23%
1000-10000ms	970	0.96%
> 10000ms	277	0.27%

Slowest individual queries

Rank	Duration	Query
NO DATASET

Time consuming queries

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

0ms

1

Details

0ms

lock table public.stats_hrs_summary_by_groups in access share mode;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 27	06	1	0ms	0ms

2

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 #2

Day	Hour	Count	Duration	Avg duration
Jan 27	06	1	0ms	0ms

3

0ms

2

Details

0ms

lock table public.timezones_korean in access share mode;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

4

0ms

34

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 #4

Day	Hour	Count	Duration	Avg duration
Jan 27	06	34	0ms	0ms

5

0ms

2

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

6

0ms

1

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Jan 27	06	1	0ms	0ms

7

0ms

2,107

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 #7

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2,107	0ms	0ms

8

0ms

975

Details

0ms

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

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Jan 27	06	975	0ms	0ms

9

0ms

2

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

10

0ms

2

Details

0ms

lock table public.futures_symbols in access share mode;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

11

0ms

2

Details

0ms

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

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

12

0ms

2

Details

0ms

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

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

13

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 #13

Day	Hour	Count	Duration	Avg duration
Jan 27	06	18	0ms	0ms

14

0ms

5

Details

0ms

select s.tableoid, s.oid, s.subname, ( select rolname from pg_catalog.pg_roles where oid = s.subowner) as rolname, s.subconninfo, s.subslotname, s.subsynccommit, s.subpublications from pg_subscription s where s.subdbid = ( select oid from pg_database where datname = current_database());

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Jan 27	06	5	0ms	0ms

15

0ms

1

Details

0ms

select usename, array_to_string(array ( select quote_ident(option_name) || ? || quote_literal(option_value) from pg_options_to_table(umoptions) order by option_name), e ?) as umoptions from pg_user_mappings where srvid = ? order by usename;

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Jan 27	06	1	0ms	0ms

16

0ms

2

Details

0ms

copy archive.sa_hist_consecutivecandles (id, symbolid, datetime, image, qty, percentile, direction, lastupdated, height) to stdout;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

17

0ms

1

Details

0ms

copy public.commoncontenttypeparams (id, name, required, description, "default", type) to stdout;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 27	06	1	0ms	0ms

18

0ms

412

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 #18

Day	Hour	Count	Duration	Avg duration
Jan 27	06	412	0ms	0ms

19

0ms

2

Details

0ms

lock table public.powerstats in access share mode;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

20

0ms

4

Details

0ms

select oid, enumlabel from pg_catalog.pg_enum where enumtypid = ? order by enumsortorder;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 27	06	4	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

19,953

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 27	06	19,953	0ms	0ms

2

10,196

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	06	10,196	0ms	0ms

3

7,793

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	06	7,793	0ms	0ms

4

5,759

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	06	5,759	0ms	0ms

5

5,676

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	06	5,676	0ms	0ms

6

4,011

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 #6

Day	Hour	Count	Duration	Avg duration
Jan 27	06	4,011	0ms	0ms

7

3,284

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Jan 27	06	3,284	0ms	0ms

8

2,921

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 #8

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2,921	0ms	0ms

9

2,744

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	06	2,744	0ms	0ms

10

2,107

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 #10

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2,107	0ms	0ms

11

2,085

Details

0ms

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

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2,085	0ms	0ms

12

2,016

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2,016	0ms	0ms

13

1,990

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Jan 27	06	1,990	0ms	0ms

14

1,733

Details

0ms

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

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Jan 27	06	1,733	0ms	0ms

15

1,656

Details

0ms

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

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Jan 27	06	1,656	0ms	0ms

16

1,339

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 #16

Day	Hour	Count	Duration	Avg duration
Jan 27	06	1,339	0ms	0ms

17

975

Details

0ms

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

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 27	06	975	0ms	0ms

18

952

Details

0ms

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

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Jan 27	06	952	0ms	0ms

19

785

Details

0ms

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

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Jan 27	06	785	0ms	0ms

20

679

Details

0ms

select at.attname, ( select pg_catalog.array_agg(acl order by row_n) from ( select acl, row_n from pg_catalog.unnest(coalesce(at.attacl, pg_catalog.acldefault(?, c.relowner))) with ordinality as perm (acl, row_n) where not exists ( select ? from pg_catalog.unnest(coalesce(pip.initprivs, pg_catalog.acldefault(?, c.relowner))) as init (init_acl) where acl = init_acl)) as foo) as attacl, ( select pg_catalog.array_agg(acl order by row_n) from ( select acl, row_n from pg_catalog.unnest(coalesce(pip.initprivs, pg_catalog.acldefault(?, c.relowner))) with ordinality as initp (acl, row_n) where not exists ( select ? from pg_catalog.unnest(coalesce(at.attacl, pg_catalog.acldefault(?, c.relowner))) as permp (orig_acl) where acl = orig_acl)) as foo) as rattacl, null as initattacl, null as initrattacl from pg_catalog.pg_attribute at join pg_catalog.pg_class c on (at.attrelid = c.oid) left join pg_catalog.pg_init_privs pip on (at.attrelid = pip.objoid and pip.classoid = ?::pg_catalog.regclass and at.attnum = pip.objsubid) where at.attrelid = ?::pg_catalog.oid and not at.attisdropped and (( select pg_catalog.array_agg(acl order by row_n) from ( select acl, row_n from pg_catalog.unnest(coalesce(at.attacl, pg_catalog.acldefault(?, c.relowner))) with ordinality as perm (acl, row_n) where not exists ( select ? from pg_catalog.unnest(coalesce(pip.initprivs, pg_catalog.acldefault(?, c.relowner))) as init (init_acl) where acl = init_acl)) as foo) is not null or ( select pg_catalog.array_agg(acl order by row_n) from ( select acl, row_n from pg_catalog.unnest(coalesce(pip.initprivs, pg_catalog.acldefault(?, c.relowner))) with ordinality as initp (acl, row_n) where not exists ( select ? from pg_catalog.unnest(coalesce(at.attacl, pg_catalog.acldefault(?, c.relowner))) as permp (orig_acl) where acl = orig_acl)) as foo) is not null or null is not null or null is not null) order by at.attnum;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 27	06	679	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

1

Details

0ms

lock table public.stats_hrs_summary_by_groups in access share mode;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 27	06	1	0ms	0ms

2

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 #2

Day	Hour	Count	Duration	Avg duration
Jan 27	06	1	0ms	0ms

3

0ms

2

Details

0ms

lock table public.timezones_korean in access share mode;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

4

0ms

34

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 #4

Day	Hour	Count	Duration	Avg duration
Jan 27	06	34	0ms	0ms

5

0ms

2

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

6

0ms

1

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Jan 27	06	1	0ms	0ms

7

0ms

2,107

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 #7

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2,107	0ms	0ms

8

0ms

975

Details

0ms

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

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Jan 27	06	975	0ms	0ms

9

0ms

2

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

10

0ms

2

Details

0ms

lock table public.futures_symbols in access share mode;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

11

0ms

2

Details

0ms

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

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

12

0ms

2

Details

0ms

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

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

13

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 #13

Day	Hour	Count	Duration	Avg duration
Jan 27	06	18	0ms	0ms

14

0ms

5

Details

0ms

select s.tableoid, s.oid, s.subname, ( select rolname from pg_catalog.pg_roles where oid = s.subowner) as rolname, s.subconninfo, s.subslotname, s.subsynccommit, s.subpublications from pg_subscription s where s.subdbid = ( select oid from pg_database where datname = current_database());

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Jan 27	06	5	0ms	0ms

15

0ms

1

Details

0ms

select usename, array_to_string(array ( select quote_ident(option_name) || ? || quote_literal(option_value) from pg_options_to_table(umoptions) order by option_name), e ?) as umoptions from pg_user_mappings where srvid = ? order by usename;

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Jan 27	06	1	0ms	0ms

16

0ms

2

Details

0ms

copy archive.sa_hist_consecutivecandles (id, symbolid, datetime, image, qty, percentile, direction, lastupdated, height) to stdout;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

17

0ms

1

Details

0ms

copy public.commoncontenttypeparams (id, name, required, description, "default", type) to stdout;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 27	06	1	0ms	0ms

18

0ms

412

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 #18

Day	Hour	Count	Duration	Avg duration
Jan 27	06	412	0ms	0ms

19

0ms

2

Details

0ms

lock table public.powerstats in access share mode;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Jan 27	06	2	0ms	0ms

20

0ms

4

Details

0ms

select oid, enumlabel from pg_catalog.pg_enum where enumtypid = ? order by enumsortorder;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 27	06	4	0ms	0ms

Time consuming prepare


Date: 2026-01-27 06:19:25
Duration: 1m16s
Database: postgres
Date: 2026-01-27 06:56:10
Duration: 12ms
Database: postgres
Date: 2026-01-27 06:30:50
Duration: 10ms
Database: postgres
Date: 2026-01-27 06:31:05
Duration: 12ms
Database: postgres
Date: 2026-01-27 06:32:08
Duration: 9ms
Database: postgres
Date: 2026-01-27 06:56:13
Duration: 30ms
Database: postgres
Date: 2026-01-27 06:11:50
Duration: 0ms
Database: postgres
Date: 2026-01-27 06:15:55
Duration: 0ms
Database: postgres
Date: 2026-01-27 06:02:33
Duration: 0ms
Database: postgres
Date: 2026-01-27 06:01:33
Duration: 2ms
Database: postgres
Date: 2026-01-27 06:21:45
Duration: 11ms
Database: postgres
Date: 2026-01-27 06:40:02
Duration: 23ms
Database: postgres
Date: 2026-01-27 06:40:02
Duration: 7ms
Database: postgres
Date: 2026-01-27 06:30:59
Duration: 0ms
Database: postgres
Date: 2026-01-27 06:44:01
Duration: 8ms
Database: postgres
Date: 2026-01-27 06:13:12
Duration: 1ms
Database: postgres
Date: 2026-01-27 06:10:05
Duration: 3ms
Database: postgres
Date: 2026-01-27 06:00:03
Duration: 0ms
Database: postgres
Date: 2026-01-27 06:19:50
Duration: 1ms
Database: postgres
Date: 2026-01-27 06:17:24
Duration: 0ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

38s27ms

6,546

Details

0ms

61ms

5ms

WITH rar_max as ( ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Jan 27	06	6,546	38s27ms	5ms

WITH rar_max as ( ;

Date: 2026-01-27 06:27:15 Duration: 61ms Database: postgres parameters: $1 = '607569618510632303', $2 = '607569618510632303', $3 = '607569618510632303'
WITH rar_max as ( ;

Date: 2026-01-27 06:56:13 Duration: 52ms Database: postgres parameters: $1 = '607572677399957303', $2 = '607572677399957303', $3 = '607572677399957303'
WITH rar_max as ( ;

Date: 2026-01-27 06:27:15 Duration: 49ms Database: postgres parameters: $1 = '607567015913854301', $2 = '607567015913854301', $3 = '607567015913854301'

2

6s734ms

16,789

Details

0ms

18ms

0ms

SELECT ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	06	16,789	6s734ms	0ms

SELECT ;

Date: 2026-01-27 06:22:54 Duration: 18ms Database: postgres parameters: $1 = '515840233927091300'
SELECT ;

Date: 2026-01-27 06:56:21 Duration: 17ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '515840243244451300'
SELECT ;

Date: 2026-01-27 06:00:47 Duration: 16ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840232462312300'

3

2s634ms

1,058

Details

1ms

11ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	06	1,058	2s634ms	2ms

SELECT symbolid, ;

Date: 2026-01-27 06:32:01 Duration: 11ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'LTCUSD', $4 = 'MATUSD'
SELECT symbolid, ;

Date: 2026-01-27 06:40:39 Duration: 10ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '15', $3 = 'AUS_200'
SELECT symbolid, ;

Date: 2026-01-27 06:30:50 Duration: 8ms Database: postgres parameters: $1 = 'AXIORY', $2 = '15', $3 = 'NZDUSD', $4 = 'SGDJPY', $5 = 'SP', $6 = 'USDCAD'

4

864ms

479

Details

1ms

2ms

1ms

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

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	06	479	864ms	1ms

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

Date: 2026-01-27 06:30:58 Duration: 2ms Database: postgres parameters: $1 = 'GLOBALGTMT5'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-01-27 06:32:27 Duration: 2ms Database: postgres parameters: $1 = 'MILLENNIUMPF'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-01-27 06:30:54 Duration: 2ms Database: postgres parameters: $1 = 'AXIORY'

5

690ms

90

Details

4ms

20ms

7ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	06	90	690ms	7ms

WITH last_candle AS ( ;

Date: 2026-01-27 06:36:00 Duration: 20ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-01-27 06:20:00 Duration: 18ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-01-27 06:44:01 Duration: 14ms Database: postgres parameters: $1 = '538', $2 = '538'

6

490ms

20

Details

0ms

66ms

24ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	06	20	490ms	24ms

with wh_patitioned as ( ;

Date: 2026-01-27 06:40:01 Duration: 66ms 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 06:20:58 Duration: 46ms 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 06:22:51 Duration: 40ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'

7

458ms

12

Details

27ms

70ms

38ms

with sym_info as ( ;

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	06	12	458ms	38ms

with sym_info as ( ;

Date: 2026-01-27 06:21:45 Duration: 70ms 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 06:36:44 Duration: 47ms 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 06:21:56 Duration: 46ms Database: postgres parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'

8

410ms

66

Details

0ms

21ms

6ms

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

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	06	66	410ms	6ms

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

Date: 2026-01-27 06:05:59 Duration: 21ms 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 06:05:56 Duration: 20ms 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 06:58:00 Duration: 20ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

9

410ms

19,840

Details

0ms

2ms

0ms

select 1;

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	06	19,840	410ms	0ms

select 1;

Date: 2026-01-27 06:21:02 Duration: 2ms Database: postgres
select 1;

Date: 2026-01-27 06:02:17 Duration: 1ms Database: postgres
select 1;

Date: 2026-01-27 06:17:58 Duration: 1ms Database: postgres

10

263ms

5,676

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
	06	5,676	263ms	0ms

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

Date: 2026-01-27 06:26:52 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 06:00:00', $2 = '25838.28', $3 = '25867.15', $4 = '25837.28', $5 = '25855.9', $6 = '2651', $7 = '515840248038958300', $8 = '0', $9 = '2026-01-27 06:26:52.538', $10 = '2026-01-27 06:26:52.47', $11 = '25838.28', $12 = '25867.15', $13 = '25837.28', $14 = '25855.9', $15 = '2651', $16 = '0', $17 = '2026-01-27 06:26:52.538', $18 = '2026-01-27 06:26:52.47'
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 06:46:30 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 06:30:00', $2 = '109.308', $3 = '109.334', $4 = '107.742', $5 = '108.3135', $6 = '3164', $7 = '515840230624306300', $8 = '0', $9 = '2026-01-27 06:46:30.521', $10 = '2026-01-27 06:46:30.454', $11 = '109.308', $12 = '109.334', $13 = '107.742', $14 = '108.3135', $15 = '3164', $16 = '0', $17 = '2026-01-27 06:46:30.521', $18 = '2026-01-27 06:46:30.454'
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 06:17:36 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 06:00:00', $2 = '5076.705', $3 = '5078.69', $4 = '5068.645', $5 = '5069.475', $6 = '2091', $7 = '515840230628558300', $8 = '0', $9 = '2026-01-27 06:17:36.211', $10 = '2026-01-27 06:17:36.153', $11 = '5076.705', $12 = '5078.69', $13 = '5068.645', $14 = '5069.475', $15 = '2091', $16 = '0', $17 = '2026-01-27 06:17:36.211', $18 = '2026-01-27 06:17:36.153'

11

261ms

3,284

Details

0ms

14ms

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
	06	3,284	261ms	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 06:30:56 Duration: 14ms Database: postgres parameters: $1 = '2026-01-27 06:00:00', $2 = '17.3261', $3 = '17.335', $4 = '17.3225', $5 = '17.3321', $6 = '1395', $7 = '515840248019330300', $8 = '0', $9 = '2026-01-27 06:30:56.27', $10 = '2026-01-27 06:30:56.162', $11 = '17.3261', $12 = '17.335', $13 = '17.3225', $14 = '17.3321', $15 = '1395', $16 = '0', $17 = '2026-01-27 06:30:56.27', $18 = '2026-01-27 06:30:56.162'
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 06:30:45 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 06:00:00', $2 = '8.92852', $3 = '8.93462', $4 = '8.92691', $5 = '8.93412', $6 = '2384', $7 = '515840245901690300', $8 = '0', $9 = '2026-01-27 06:30:45.857', $10 = '2026-01-27 06:30:45.857', $11 = '8.92852', $12 = '8.93462', $13 = '8.92691', $14 = '8.93412', $15 = '2384', $16 = '0', $17 = '2026-01-27 06:30:45.857', $18 = '2026-01-27 06:30:45.857'
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 06:15:53 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 06:30:00', $2 = '1420587.845', $3 = '1422664.945', $4 = '1420087.63', $5 = '1422661.265', $6 = '4373', $7 = '515840249474000300', $8 = '0', $9 = '2026-01-27 06:15:53.33', $10 = '2026-01-27 06:15:53.277', $11 = '1420587.845', $12 = '1422664.945', $13 = '1420087.63', $14 = '1422661.265', $15 = '4373', $16 = '0', $17 = '2026-01-27 06:15:53.33', $18 = '2026-01-27 06:15:53.277'

12

172ms

2,107

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
	06	2,107	172ms	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 06:02:33 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 05:00:00', $2 = '110.451', $3 = '110.6775', $4 = '108.886', $5 = '109.7855', $6 = '18165', $7 = '515840230625682300', $8 = '0', $9 = '2026-01-27 06:02:33.375', $10 = '2026-01-27 06:02:33.375', $11 = '110.451', $12 = '110.6775', $13 = '108.886', $14 = '109.7855', $15 = '18165', $16 = '0', $17 = '2026-01-27 06:02:33.375', $18 = '2026-01-27 06:02:33.375'
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 06:46:21 Duration: 0ms Database: postgres parameters: $1 = '2026-01-26 22:00:00', $2 = '249.08', $3 = '249.425', $4 = '248.22', $5 = '248.73', $6 = '1840', $7 = '515840249438520300', $8 = '0', $9 = '2026-01-27 06:46:21.983', $10 = '2026-01-27 06:46:21.983', $11 = '249.08', $12 = '249.425', $13 = '248.22', $14 = '248.73', $15 = '1840', $16 = '0', $17 = '2026-01-27 06:46:21.983', $18 = '2026-01-27 06:46:21.983'
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 06:02:08 Duration: 0ms Database: postgres parameters: $1 = '2026-01-27 05:00:00', $2 = '10193.9', $3 = '10194.65', $4 = '10185.65', $5 = '10191.4', $6 = '829', $7 = '500991628276360200', $8 = '0', $9 = '2026-01-27 06:02:08.319', $10 = '2026-01-27 06:02:08.318', $11 = '10193.9', $12 = '10194.65', $13 = '10185.65', $14 = '10191.4', $15 = '829', $16 = '0', $17 = '2026-01-27 06:02:08.319', $18 = '2026-01-27 06:02:08.318'

13

99ms

6

Details

3ms

55ms

16ms

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 #13

Day	Hour	Count	Duration	Avg duration
	06	6	99ms	16ms

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 06:40:02 Duration: 55ms 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 06:50:02 Duration: 11ms 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 06:30:02 Duration: 11ms Database: postgres

14

57ms

54

Details

0ms

6ms

1ms

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
	06	54	57ms	1ms

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 06:40:01 Duration: 6ms Database: postgres parameters: $1 = '558', $2 = 'XAUUSD', $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 06:48:21 Duration: 1ms Database: postgres parameters: $1 = '689', $2 = 'XAUUSD', $3 = '689'
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2026-01-27 06:31:21 Duration: 1ms Database: postgres parameters: $1 = '689', $2 = 'XAUUSD', $3 = '689'

15

53ms

1

Details

53ms

with maxwhid as ( ;

Times Reported Time consuming bind #15

Day	Hour	Count	Duration	Avg duration
	06	1	53ms	53ms

with maxwhid as ( ;

Date: 2026-01-27 06:12:15 Duration: 53ms Database: postgres parameters: $1 = '335', $2 = '621', $3 = '637', $4 = '642', $5 = '660', $6 = '666', $7 = '643', $8 = '630', $9 = '680', $10 = '641', $11 = '431', $12 = '622', $13 = '489', $14 = '529', $15 = '576', $16 = '665', $17 = '667', $18 = '558', $19 = '620', $20 = '125', $21 = '488', $22 = '567', $23 = '689', $24 = '700', $25 = '758', $26 = '763', $27 = '765', $28 = '817', $29 = '914', $30 = '972'

16

46ms

96

Details

0ms

2ms

0ms

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

Times Reported Time consuming bind #16

Day	Hour	Count	Duration	Avg duration
	06	96	46ms	0ms

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

Date: 2026-01-27 06:13:12 Duration: 2ms Database: postgres
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2026-01-27 06:13:13 Duration: 1ms Database: postgres
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2026-01-27 06:13:13 Duration: 0ms Database: postgres

17

36ms

7

Details

3ms

6ms

5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #17

Day	Hour	Count	Duration	Avg duration
	06	7	36ms	5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-27 06:51:02 Duration: 6ms Database: postgres parameters: $1 = '627', $2 = '627'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-27 06:42:31 Duration: 6ms Database: postgres parameters: $1 = '667', $2 = '667'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-27 06:56:00 Duration: 5ms Database: postgres parameters: $1 = '627', $2 = '627'

18

32ms

8

Details

2ms

8ms

4ms

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

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	06	8	32ms	4ms

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

Date: 2026-01-27 06:13:10 Duration: 8ms 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 06:13:11 Duration: 6ms 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 06:13:12 Duration: 4ms 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'

19

28ms

1

Details

28ms

SELECT COUNT(*) AS total_records FROM process_media_view WHERE "process_uuid" = '0aff8a66-2dcc-405a-80b8-9bf344f698d2' AND "resultdate" <= '2026-01-26 22:02:03+00:00';

Times Reported Time consuming bind #19

Day	Hour	Count	Duration	Avg duration
	06	1	28ms	28ms

SELECT COUNT(*) AS total_records FROM process_media_view WHERE "process_uuid" = '0aff8a66-2dcc-405a-80b8-9bf344f698d2' AND "resultdate" <= '2026-01-26 22:02:03+00:00';

Date: 2026-01-27 06:40:41 Duration: 28ms Database: postgres

20

28ms

29

Details

0ms

4ms

0ms

WITH tr_max AS ( ;

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	06	29	28ms	0ms

WITH tr_max AS ( ;

Date: 2026-01-27 06:13:11 Duration: 4ms 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 06:13:14 Duration: 2ms Database: postgres parameters: $1 = '606715251031835300', $2 = '606715251031835300', $3 = '606715251031835300', $4 = '1', $5 = '1', $6 = '1320', $7 = 't', $8 = '1320'
WITH tr_max AS ( ;

Date: 2026-01-27 06:13:13 Duration: 1ms Database: postgres parameters: $1 = '606715250664862300', $2 = '606715250664862300', $3 = '606715250664862300', $4 = '2', $5 = '2', $6 = '300', $7 = 't', $8 = '300'

Log levels

Key values

371,447 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	418	0.11%
DETAIL	75,915	20.44%
ERROR	35	0.01%
HINT	34	0.01%
LOG	294,455	79.27%
STATEMENT	590	0.16%

Events distribution

Key values

0 PANIC entries
0 FATAL entries
39 ERROR entries
0 WARNING entries

Most Frequent Errors/Events

Key values

34 Max number of times the same event was reported
39 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	06	34

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

2

4

Details

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

Times Reported Most Frequent Error / Event #2

Day	Hour	Count
Jan 27	06	4

LOG: process 1418 still waiting for AccessExclusiveLock on relation 5883477 of database 5881926 after 1000.056 ms
LOG: process 1418 still waiting for AccessExclusiveLock on relation 5883477 of database 5881926 after 51241.042 ms
LOG: process 5236 still waiting for AccessExclusiveLock on relation 5894441 of database 5881926 after 1000.055 ms

3

1

Details

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

Times Reported Most Frequent Error / Event #3

Day	Hour	Count
Jan 27	06	1

LOG: process 5688 still waiting for AccessShareLock on relation 5894441 of database 5881926 after 1000.050 ms at character 77

Global information

Overview

Global Stats

SQL Traffic

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SELECT Traffic

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INSERT/UPDATE/DELETE Traffic

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Queries duration

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Prepared queries ratio

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General Activity

Connections

Established Connections

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Connections per database

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Connections per user

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Connections per host

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Sessions

Simultaneous sessions

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Histogram of session times

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Sessions per database

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Sessions per user

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Sessions per host

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Sessions per application

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Checkpoints / Restartpoints

Checkpoints Buffers

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Checkpoints Wal files

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Checkpoints distance

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Checkpoints Activity

Checkpoint causes

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Temporary Files

Size of temporary files

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Number of temporary files

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Temporary Files Activity

Queries generating the most temporary files (N)

Queries generating the largest temporary files

Vacuums

Vacuums / Analyzes Distribution

Key values

Analyzes per table

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Vacuums per table

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Tuples removed per table

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Pages removed per table

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Autovacuum Activity

Locks

Locks by types

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Most frequent waiting queries (N)

Queries that waited the most

Queries

Queries by type

Key values

Queries by database

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Queries by user

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Duration by user

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