pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Mon Jan 5 07:59:56 2026
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-01-05_090000.log
Parsed 2,398,399 log entries in 55s
Log start from 2026-01-05 09:00:00 to 2026-01-05 09:59:54

Global Stats

322 Number of unique normalized queries
266,902 Number of queries
1h18m58s Total query duration
2026-01-05 09:00:00 First query
2026-01-05 09:59:54 Last query
5,284 queries/s at 2026-01-05 09:00:04 Query peak

1h18m58s Total query duration
6s83ms Prepare/parse total duration
46s745ms Bind total duration
1h18m5s Execute total duration

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

37 Total number of automatic vacuums
52 Total number of automatic analyzes

861 Number temporary file
586.35 MiB Max size of temporary file
6.46 MiB Average size of temporary file

2,872 Total number of sessions
14 sessions at 2026-01-05 09:51:53 Session peak
13d20h19m59s Total duration of sessions
6m56s Average duration of sessions
92 Average queries per session
1s649ms Average queries duration per session
6m54s Average idle time per session

2,878 Total number of connections
31 connections/s at 2026-01-05 09:56:39 Connection peak
3 Total number of databases

SQL Traffic

Key values

5,284 queries/s Query Peak
2026-01-05 09:00:04 Date

SELECT Traffic

Key values

2,591 queries/s Query Peak
2026-01-05 09:00:04 Date

INSERT/UPDATE/DELETE Traffic

Key values

173 queries/s Query Peak
2026-01-05 09:01:52 Date

Queries duration

Key values

1h18m58s 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 05	09	266,902	0ms	27s596ms	17ms	3m6s	3m55s	4m20s

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Jan 05	09	85,822	26	0ms	0ms	0ms	0ms

Day	Hour	INSERT	UPDATE	DELETE	COPY FROM	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Jan 05	09	30,631	2,607	16	96	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Jan 05	09	20,014	97,456	4.87	15.49%

Day	Hour	Count	Average / Second
Jan 05	09	2,878	0.80/s

Day	Hour	Count	Average Duration	Average idle time
Jan 05	09	2,872	6m56s	6m54s

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Established Connections

Key values

31 connections Connection Peak
2026-01-05 09:56:39 Date

Connections per database

Key values

acaweb_fx Main Database
2,878 connections Total

Chart
Table

Database	User	Count
acaweb_fx		2,736
	postgres	2,349
	psql	387
socialmedia		142
	postgres	142

Connections per user

Key values

postgres Main User
2,878 connections Total

Chart
Table

User	Count
postgres	2,491
psql	387

Connections per host

Key values

192.168.4.142 Main host with 1039 connections
2,878 Total connections

Chart
Table

Host	Count
127.0.0.1	113
182.165.1.54	2
192.168.0.114	6
192.168.0.216	101
192.168.0.236	3
192.168.0.74	308
192.168.0.84	2
192.168.1.127	40
192.168.1.131	2
192.168.1.145	76
192.168.1.15	126
192.168.1.20	92
192.168.1.238	2
192.168.1.239	2
192.168.1.90	55
192.168.1.97	4
192.168.2.126	72
192.168.2.182	12
192.168.2.82	48
192.168.3.199	36
192.168.4.108	4
192.168.4.112	4
192.168.4.125	4
192.168.4.142	1,039
192.168.4.150	10
192.168.4.222	1
192.168.4.238	12
192.168.4.249	1
192.168.4.33	97
192.168.4.98	330
[local]	274

Simultaneous sessions

Key values

14 sessions Session Peak
2026-01-05 09:51:53 Date

Histogram of session times

Key values

2,271 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	2,271	79.07%
500ms-1s	128	4.46%
1s-30s	352	12.26%
30s-1m	14	0.49%
1m-10m	22	0.77%
10m-30m	45	1.57%
30m-1h	12	0.42%
1h-8h	17	0.59%
> 8h	11	0.38%

Sessions per database

Key values

acaweb_fx Main Database
2,872 sessions Total

Chart
Table

Database	User	Count	Total Duration	Average Duration
acaweb_fx	2,730	13d19h24m52s	7m17s
socialmedia	142	55m6s	23s285ms

Sessions per user

Key values

postgres Main User
2,872 sessions Total

Chart
Table

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

Sessions per host

Key values

192.168.4.142 Main Host
2,872 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
127.0.0.1	113	7s178ms	63ms
182.165.1.54	2	23h17m24s	11h38m42s
192.168.0.114	7	47m15s	6m45s
192.168.0.216	101	1m2s	615ms
192.168.0.236	1	4ms	4ms
192.168.0.74	308	1d8h24m59s	6m18s
192.168.0.84	2	23h59m33s	11h59m46s
192.168.1.127	40	43s621ms	1s90ms
192.168.1.131	2	23h59m33s	11h59m46s
192.168.1.145	75	2d11h3m34s	47m14s
192.168.1.15	126	2d6h49m27s	26m6s
192.168.1.20	92	2d21h27m20s	45m17s
192.168.1.238	2	23h59m26s	11h59m43s
192.168.1.239	2	14ms	7ms
192.168.1.90	55	33s152ms	602ms
192.168.1.97	1	3ms	3ms
192.168.2.126	72	17s103ms	237ms
192.168.2.182	12	788ms	65ms
192.168.2.82	48	11s418ms	237ms
192.168.3.199	36	1s295ms	35ms
192.168.4.108	4	34ms	8ms
192.168.4.112	4	33ms	8ms
192.168.4.125	4	26s169ms	6s542ms
192.168.4.142	1,039	8m15s	476ms
192.168.4.150	10	20h3m	2h18s
192.168.4.222	1	52s918ms	52s918ms
192.168.4.238	12	14s935ms	1s244ms
192.168.4.249	1	161ms	161ms
192.168.4.33	96	12m7s	7s580ms
192.168.4.98	330	16s212ms	49ms
[local]	274	3m12s	703ms

Sessions per application

Key values

unknown Main Host
2,872 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	2,872	13d20h19m59s	6m56s

Checkpoints Buffers

Key values

10,061 buffers Checkpoint Peak
2026-01-05 09:08:55 Date
209.956 seconds Highest write time
0.017 seconds Sync time

Checkpoints Wal files

Key values

6 files Wal files usage Peak
2026-01-05 09:08:55 Date

Checkpoints distance

Key values

204.04 Mo Distance Peak
2026-01-05 09:08:55 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Jan 05	09	37,022	2,068.475s	0.054s	2,068.841s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Jan 05	09	0	0	24	1,988	0.005s	0s

Day	Hour	Count	Avg time (sec)
Jan 05	09	0	0s

Day	Hour	Mean distance	Mean estimate
Jan 05	09	32,985.08 kB	75,384.50 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

299.82 MiB Temp Files size Peak
2026-01-05 09:14:49 Date

Number of temporary files

Key values

62 per second Temp Files Peak
2026-01-05 09:32:09 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Jan 05	09	861	5.43 GiB	6.46 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	30	1.66 GiB	3.87 MiB	133.75 MiB	56.78 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: 2026-01-05 09:00:06 Duration: 0ms
2	16	616.12 MiB	38.51 MiB	38.51 MiB	38.51 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: 2026-01-05 09:01:13 Duration: 0ms
3	16	1.11 GiB	70.75 MiB	70.76 MiB	70.76 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: 2026-01-05 09:01:18 Duration: 0ms
4	8	1009.06 MiB	126.11 MiB	126.16 MiB	126.13 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2026-01-05 09:02:17 Duration: 0ms
5	5	35.50 MiB	7.10 MiB	7.12 MiB	7.10 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: 2026-01-05 09:00:09 Duration: 0ms
6	4	366.63 MiB	91.59 MiB	91.75 MiB	91.66 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2026-01-05 09:02:06 Duration: 0ms
7	3	9.08 MiB	3.02 MiB	3.03 MiB	3.03 MiB	select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ?), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?)), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc; SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ($2 = 0 OR s.timegranularity in ($3, $4, $5, $6, $7, $8, $9)) AND ($10 = 0 OR s.exchange in ($11)) AND ($12 = 0 OR coalesce(bim.code, s.symbol) in ($13, $14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226, $227, $228, $229, $230, $231, $232, $233, $234, $235, $236, $237, $238, $239, $240, $241, $242, $243, $244, $245, $246, $247, $248, $249, $250, $251, $252, $253, $254, $255, $256, $257, $258, $259, $260, $261, $262, $263, $264, $265, $266, $267, $268, $269, $270, $271, $272, $273, $274, $275, $276, $277, $278, $279, $280, $281, $282, $283, $284, $285, $286, $287, $288, $289, $290, $291, $292, $293, $294, $295, $296, $297, $298, $299, $300, $301, $302, $303, $304, $305, $306, $307, $308, $309, $310, $311, $312, $313, $314, $315, $316, $317, $318, $319, $320, $321, $322)) AND ($323 = 0 OR ccr.patternlengthbars <= $324)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $325 OR relevant = 1) AND ($326 = 0 OR age <= $327) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-01-05 09:02:13 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	133.75 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: 2026-01-05 09:40:04 ]
2	126.16 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-05 09:02:17 ]
3	126.15 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-05 09:17:13 ]
4	126.15 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-05 09:32:14 ]
5	126.14 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-05 09:47:13 ]
6	126.12 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-05 09:50:33 ]
7	126.12 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-05 09:35:33 ]
8	126.11 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-05 09:05:33 ]
9	126.11 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-05 09:20:33 ]
10	117.43 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: 2026-01-05 09:00:05 ]
11	106.59 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: 2026-01-05 09:30:04 ]
12	106.24 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: 2026-01-05 09:40:04 ]
13	100.57 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: 2026-01-05 09:00:05 ]
14	91.75 MiB	select updateageforrelevantresults (); [ Date: 2026-01-05 09:02:06 ]
15	91.66 MiB	select updateageforrelevantresults (); [ Date: 2026-01-05 09:32:05 ]
16	91.62 MiB	select updateageforrelevantresults (); [ Date: 2026-01-05 09:47:04 ]
17	91.59 MiB	select updateageforrelevantresults (); [ Date: 2026-01-05 09:17:05 ]
18	90.32 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-05 09:20:05 ]
19	88.42 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: 2026-01-05 09:10:04 ]
20	87.82 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: 2026-01-05 09:10:04 ]

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 (17) Main table analyzed (database acaweb_fx)
52 analyzes Total

Chart
Table

Table	Number of analyzes
acaweb_fx.public.solr_relevance_old	17
acaweb_fx.public.datafeeds_latestrun	4
acaweb_fx.pg_catalog.pg_attribute	4
acaweb_fx.public.relevance_keylevels_results	4
acaweb_fx.pg_catalog.pg_class	4
acaweb_fx.public.relevance_autochartist_results	4
acaweb_fx.public.relevance_fibonacci_results	4
acaweb_fx.pg_catalog.pg_type	3
acaweb_fx.pg_catalog.pg_index	2
acaweb_fx.public.latest_t15_candle_view	2
acaweb_fx.public.autochartist_symbolupdates	1
acaweb_fx.public.relevance_consecutivecandles_results	1
acaweb_fx.pg_catalog.pg_depend	1
acaweb_fx.public.latest_candle_datetime_per_receng	1
Total	52

Vacuums per table

Key values

public.solr_relevance_old (17) 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	17	17	12,854	0	59	0	46	8,695	1,005	5,212,225
acaweb_fx.public.datafeeds_latestrun	5	0	601	0	27	0	0	73	24	85,689
acaweb_fx.pg_toast.pg_toast_2619	2	2	307	0	55	0	0	230	55	240,751
acaweb_fx.public.relevance_keylevels_results	2	2	7,814	0	267	2	108	1,976	255	864,324
acaweb_fx.public.relevance_autochartist_results	2	2	6,906	0	148	0	478	1,396	142	399,513
acaweb_fx.pg_catalog.pg_class	2	2	929	0	106	0	0	300	142	618,811
acaweb_fx.public.relevance_fibonacci_results	2	2	2,494	0	44	0	94	425	24	106,868
acaweb_fx.pg_catalog.pg_type	1	1	132	0	20	0	0	51	15	102,491
acaweb_fx.public.autochartist_symbolupdates	1	1	23,378	0	3,649	0	37,992	6,937	2,527	1,168,224
acaweb_fx.pg_catalog.pg_attribute	1	1	799	0	170	0	67	366	135	815,954
acaweb_fx.pg_catalog.pg_statistic	1	1	1,045	0	149	0	582	482	142	545,805
acaweb_fx.public.latest_t15_candle_view	1	1	83	0	1	0	0	6	1	9,049
Total	37	32	57,342	45,221	4,695	2	39,367	20,937	4,467	10,169,704

Tuples removed per table

Key values

public.solr_relevance_old (47164) Main table with removed tuples on database acaweb_fx
59122 tuples Total removed

Chart
Table

		Index	Tuples			Pages
Table	Vacuums	scans	removed	remain	not yet removable	removed	remain
acaweb_fx.public.solr_relevance_old	17	17	47,164	92,739	939	0	3,118
acaweb_fx.public.autochartist_symbolupdates	1	1	5,534	52,559	8	0	40,691
acaweb_fx.public.relevance_keylevels_results	2	2	1,756	24,283	0	0	558
acaweb_fx.pg_catalog.pg_attribute	1	1	1,424	10,801	0	19	240
acaweb_fx.public.relevance_autochartist_results	2	2	1,330	16,314	0	0	760
acaweb_fx.pg_catalog.pg_statistic	1	1	529	3,726	0	0	1,194
acaweb_fx.public.relevance_fibonacci_results	2	2	411	3,039	0	0	204
acaweb_fx.pg_catalog.pg_class	2	2	332	3,298	0	0	300
acaweb_fx.public.datafeeds_latestrun	5	0	289	82	12	0	80
acaweb_fx.pg_catalog.pg_type	1	1	149	1,446	0	0	38
acaweb_fx.pg_toast.pg_toast_2619	2	2	144	338	0	0	106
acaweb_fx.public.latest_t15_candle_view	1	1	60	14	0	0	1
Total	37	32	59,122	208,639	959	19	47,290

Pages removed per table

Key values

pg_catalog.pg_attribute (19) Main table with removed pages on database acaweb_fx
19 pages Total removed

Chart
Table

Table	Number of vacuums	Index scans	Tuples removed	Pages removed
acaweb_fx.pg_catalog.pg_attribute	1	1	1424	19
acaweb_fx.pg_toast.pg_toast_2619	2	2	144	0
acaweb_fx.pg_catalog.pg_type	1	1	149	0
acaweb_fx.public.autochartist_symbolupdates	1	1	5534	0
acaweb_fx.public.datafeeds_latestrun	5	0	289	0
acaweb_fx.pg_catalog.pg_statistic	1	1	529	0
acaweb_fx.public.latest_t15_candle_view	1	1	60	0
acaweb_fx.public.relevance_keylevels_results	2	2	1756	0
acaweb_fx.public.solr_relevance_old	17	17	47164	0
acaweb_fx.public.relevance_autochartist_results	2	2	1330	0
acaweb_fx.pg_catalog.pg_class	2	2	332	0
acaweb_fx.public.relevance_fibonacci_results	2	2	411	0
Total	37	32	59,122	19

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Jan 05	09	37	52

↑ Back to the top of the Autovacuum Activity table

Locks by types

Key values

unknown Main Lock Type
0 locks Total

Chart
Table

Type of locks

NO DATASET

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

Most frequent waiting queries (N)

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

Queries that waited the most

Rank	Wait time	Query
NO DATASET

Queries by type

Key values

85,822 Total read queries
43,390 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	85,822	32.15%
INSERT	30,631	11.48%
UPDATE	2,607	0.98%
DELETE	16	0.01%
COPY FROM	96	0.04%
COPY TO	26	0.01%
CTE	9,158	3.43%
DDL	16	0.01%
TCL	840	0.31%
CURSOR	0	0.00%
OTHERS	137,690	51.59%

Queries by database

Key values

unknown Main database
265,843 Requests
1h18m5s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	917	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	203	0ms
	select	102	0ms
	tcl	331	0ms
	update	39	0ms
socialmedia	Total	142	0ms
	others	40	0ms
	select	97	0ms
	tcl	5	0ms
unknown	Total	265,843	1h18m5s
	copy from	16	0ms
	cte	9,054	0ms
	insert	30,631	0ms
	others	3,995	0ms
	select	85,623	0ms
	tcl	504	0ms
	update	2,568	0ms

Queries by user

Key values

unknown Main user
265,843 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	1,059	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	243	0ms
	select	199	0ms
	tcl	336	0ms
	update	39	0ms
unknown	Total	265,843	1h18m5s
	copy from	16	0ms
	cte	9,054	0ms
	insert	30,631	0ms
	others	3,995	0ms
	select	85,623	0ms
	tcl	504	0ms
	update	2,568	0ms

Duration by user

Key values

1h18m5s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	1,059	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	243	0ms
	select	199	0ms
	tcl	336	0ms
	update	39	0ms
unknown	Total	265,843	1h18m5s
	copy from	16	0ms
	cte	9,054	0ms
	insert	30,631	0ms
	others	3,995	0ms
	select	85,623	0ms
	tcl	504	0ms
	update	2,568	0ms

Queries by host

Key values

unknown Main host
266,902 Requests
1h18m5s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	266,902	1h18m5s
	copy from	96	0ms
	copy to	26	0ms
	cte	9,158	0ms
	ddl	16	0ms
	delete	16	0ms
	insert	30,631	0ms
	others	4,238	0ms
	select	85,822	0ms
	tcl	840	0ms
	update	2,607	0ms

Queries by application

Key values

unknown Main application
266,515 Requests
1h18m5s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
psql	Total	387	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	4	0ms
	select	102	0ms
	update	39	0ms
unknown	Total	266,515	1h18m5s
	copy from	16	0ms
	cte	9,054	0ms
	insert	30,631	0ms
	others	4,234	0ms
	select	85,720	0ms
	tcl	840	0ms
	update	2,568	0ms

Number of cancelled queries

Key values

0 per second Cancelled query Peak
2026-01-05 09:08:24 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

95,432 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	95,432	71.51%
1-5ms	29,104	21.81%
5-10ms	5,728	4.29%
10-25ms	1,539	1.15%
25-50ms	239	0.18%
50-100ms	116	0.09%
100-500ms	328	0.25%
500-1000ms	97	0.07%
1000-10000ms	725	0.54%
> 10000ms	144	0.11%

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

2

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 05	09	2	0ms	0ms

2

0ms

65

Details

0ms

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

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Jan 05	09	65	0ms	0ms

3

0ms

1

Details

0ms

select "public"."processparameters"."id" AS "id", "public"."processparameters"."processid" AS "processid", "public"."processparameters"."key" AS "key", "public"."processparameters"."value" AS "value" from "public"."processparameters" where "public"."processparameters"."id" = ? and "public"."processparameters"."id" = ? limit ? offset ?;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Jan 05	09	1	0ms	0ms

4

0ms

9

Details

0ms

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

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Jan 05	09	9	0ms	0ms

5

0ms

2,309

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Jan 05	09	2,309	0ms	0ms

6

0ms

48

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Jan 05	09	48	0ms	0ms

7

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Jan 05	09	4	0ms	0ms

8

0ms

40

Details

0ms

set datestyle = iso;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Jan 05	09	40	0ms	0ms

9

0ms

40

Details

0ms

set client_encoding to ?;

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Jan 05	09	40	0ms	0ms

10

0ms

1

Details

0ms

select "public"."executions"."id" AS "id", "public"."executions"."processid" AS "processid", "public"."executions"."executiondate" AS "executiondate", "public"."executions"."errorcount" AS "errorcount", "public"."executions"."warningcount" AS "warningcount", "public"."executions"."isrunning" AS "isrunning", "public"."executions"."response" AS "response", "public"."executions"."live" AS "live", "public"."executions"."has_results" AS "has_results", "LT?"."id" AS "LA?" from "public"."executions" left outer join "public"."processes" "LT?" on "LT?"."id" = "public"."executions"."processid" where (processid = ?) order by "public"."executions"."id" desc limit ? offset ?;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Jan 05	09	1	0ms	0ms

11

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 #11

Day	Hour	Count	Duration	Avg duration
Jan 05	09	18	0ms	0ms

12

0ms

1

Details

0ms

select count(*) from "public"."executions" left outer join "public"."processes" "LT?" on "LT?"."id" = "public"."executions"."processid" where (processid = ?);

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 05	09	1	0ms	0ms

13

0ms

420

Details

0ms

commit;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Jan 05	09	420	0ms	0ms

14

0ms

293

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 #14

Day	Hour	Count	Duration	Avg duration
Jan 05	09	293	0ms	0ms

15

0ms

239

Details

0ms

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

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Jan 05	09	239	0ms	0ms

16

0ms

239

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Jan 05	09	239	0ms	0ms

17

0ms

1

Details

0ms

select user_role from phpgen_users where user_name = ?;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 05	09	1	0ms	0ms

18

0ms

6

Details

0ms

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

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Jan 05	09	6	0ms	0ms

19

0ms

2

Details

0ms

select "public"."processes"."id" AS "id", "public"."processes"."locale" AS "locale", "public"."processes"."region" AS "region", "public"."processes"."schedule" AS "schedule", "public"."processes"."enabled" AS "enabled", "public"."processes"."live" AS "live", "public"."processes"."lastmodified" AS "lastmodified", "public"."processes"."lastrun" AS "lastrun", "public"."processes"."contenttypeid" AS "contenttypeid", "public"."processes"."brokerid" AS "brokerid", "public"."processes"."uuid" AS "uuid", "LT?"."name" AS "LA?", "LT?"."name" AS "LA?" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where (brokerid = ?) and (contenttypeid = ?) order by "public"."processes"."id" asc limit ? offset ?;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Jan 05	09	2	0ms	0ms

20

0ms

11

Details

0ms

select updatedatafeedslatestrun (?);

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 05	09	11	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

35,661

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 05	09	35,661	0ms	0ms

2

10,685

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 05	09	10,685	0ms	0ms

3

8,350

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 05	09	8,350	0ms	0ms

4

7,888

Details

0ms

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

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Jan 05	09	7,888	0ms	0ms

5

5,773

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 05	09	5,773	0ms	0ms

6

5,545

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 #6

Day	Hour	Count	Duration	Avg duration
Jan 05	09	5,545	0ms	0ms

7

5,126

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Jan 05	09	5,126	0ms	0ms

8

3,946

Details

0ms

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

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Jan 05	09	3,946	0ms	0ms

9

3,382

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 #9

Day	Hour	Count	Duration	Avg duration
Jan 05	09	3,382	0ms	0ms

10

3,306

Details

0ms

select * from status_perbroker;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Jan 05	09	3,306	0ms	0ms

11

2,796

Details

0ms

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

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Jan 05	09	2,796	0ms	0ms

12

2,657

Details

0ms

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

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 05	09	2,657	0ms	0ms

13

2,309

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 #13

Day	Hour	Count	Duration	Avg duration
Jan 05	09	2,309	0ms	0ms

14

2,063

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 #14

Day	Hour	Count	Duration	Avg duration
Jan 05	09	2,063	0ms	0ms

15

1,953

Details

0ms

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

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Jan 05	09	1,953	0ms	0ms

16

1,874

Details

0ms

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

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Jan 05	09	1,874	0ms	0ms

17

1,729

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 05	09	1,729	0ms	0ms

18

1,687

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Jan 05	09	1,687	0ms	0ms

19

1,624

Details

0ms

select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Jan 05	09	1,624	0ms	0ms

20

1,605

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 #20

Day	Hour	Count	Duration	Avg duration
Jan 05	09	1,605	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

2

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 05	09	2	0ms	0ms

2

0ms

65

Details

0ms

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

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Jan 05	09	65	0ms	0ms

3

0ms

1

Details

0ms

select "public"."processparameters"."id" AS "id", "public"."processparameters"."processid" AS "processid", "public"."processparameters"."key" AS "key", "public"."processparameters"."value" AS "value" from "public"."processparameters" where "public"."processparameters"."id" = ? and "public"."processparameters"."id" = ? limit ? offset ?;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Jan 05	09	1	0ms	0ms

4

0ms

9

Details

0ms

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

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Jan 05	09	9	0ms	0ms

5

0ms

2,309

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Jan 05	09	2,309	0ms	0ms

6

0ms

48

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Jan 05	09	48	0ms	0ms

7

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Jan 05	09	4	0ms	0ms

8

0ms

40

Details

0ms

set datestyle = iso;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Jan 05	09	40	0ms	0ms

9

0ms

40

Details

0ms

set client_encoding to ?;

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Jan 05	09	40	0ms	0ms

10

0ms

1

Details

0ms

select "public"."executions"."id" AS "id", "public"."executions"."processid" AS "processid", "public"."executions"."executiondate" AS "executiondate", "public"."executions"."errorcount" AS "errorcount", "public"."executions"."warningcount" AS "warningcount", "public"."executions"."isrunning" AS "isrunning", "public"."executions"."response" AS "response", "public"."executions"."live" AS "live", "public"."executions"."has_results" AS "has_results", "LT?"."id" AS "LA?" from "public"."executions" left outer join "public"."processes" "LT?" on "LT?"."id" = "public"."executions"."processid" where (processid = ?) order by "public"."executions"."id" desc limit ? offset ?;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Jan 05	09	1	0ms	0ms

11

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 #11

Day	Hour	Count	Duration	Avg duration
Jan 05	09	18	0ms	0ms

12

0ms

1

Details

0ms

select count(*) from "public"."executions" left outer join "public"."processes" "LT?" on "LT?"."id" = "public"."executions"."processid" where (processid = ?);

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 05	09	1	0ms	0ms

13

0ms

420

Details

0ms

commit;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Jan 05	09	420	0ms	0ms

14

0ms

293

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 #14

Day	Hour	Count	Duration	Avg duration
Jan 05	09	293	0ms	0ms

15

0ms

239

Details

0ms

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

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Jan 05	09	239	0ms	0ms

16

0ms

239

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Jan 05	09	239	0ms	0ms

17

0ms

1

Details

0ms

select user_role from phpgen_users where user_name = ?;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 05	09	1	0ms	0ms

18

0ms

6

Details

0ms

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

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Jan 05	09	6	0ms	0ms

19

0ms

2

Details

0ms

select "public"."processes"."id" AS "id", "public"."processes"."locale" AS "locale", "public"."processes"."region" AS "region", "public"."processes"."schedule" AS "schedule", "public"."processes"."enabled" AS "enabled", "public"."processes"."live" AS "live", "public"."processes"."lastmodified" AS "lastmodified", "public"."processes"."lastrun" AS "lastrun", "public"."processes"."contenttypeid" AS "contenttypeid", "public"."processes"."brokerid" AS "brokerid", "public"."processes"."uuid" AS "uuid", "LT?"."name" AS "LA?", "LT?"."name" AS "LA?" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where (brokerid = ?) and (contenttypeid = ?) order by "public"."processes"."id" asc limit ? offset ?;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Jan 05	09	2	0ms	0ms

20

0ms

11

Details

0ms

select updatedatafeedslatestrun (?);

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 05	09	11	0ms	0ms

Time consuming prepare


Date: 2026-01-05 09:42:14
Duration: 6ms
Database: postgres
Date: 2026-01-05 09:30:57
Duration: 3ms
Database: postgres
Date: 2026-01-05 09:00:03
Duration: 5ms
Database: postgres
Date: 2026-01-05 09:46:02
Duration: 1ms
Database: postgres
Date: 2026-01-05 09:41:40
Duration: 0ms
Database: postgres
Date: 2026-01-05 09:01:15
Duration: 2ms
Database: postgres
Date: 2026-01-05 09:47:25
Duration: 1ms
Database: postgres
Date: 2026-01-05 09:47:40
Duration: 0ms
Database: postgres
Date: 2026-01-05 09:10:56
Duration: 1ms
Database: postgres
Date: 2026-01-05 09:46:30
Duration: 5ms
Database: postgres
Date: 2026-01-05 09:06:57
Duration: 6ms
Database: postgres
Date: 2026-01-05 09:14:52
Duration: 0ms
Database: postgres
Date: 2026-01-05 09:11:01
Duration: 4ms
Database: postgres
Date: 2026-01-05 09:01:15
Duration: 5ms
Database: postgres
Date: 2026-01-05 09:01:15
Duration: 5ms
Database: postgres
Date: 2026-01-05 09:10:56
Duration: 3ms
Database: postgres
Date: 2026-01-05 09:54:51
Duration: 0ms
Database: postgres
Date: 2026-01-05 09:20:05
Duration: 3ms
Database: postgres
Date: 2026-01-05 09:40:03
Duration: 0ms
Database: postgres
Date: 2026-01-05 09:14:51
Duration: 2ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

28s623ms

8,156

Details

0ms

56ms

3ms

WITH rar_max as ( ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Jan 05	09	8,156	28s623ms	3ms

WITH rar_max as ( ;

Date: 2026-01-05 09:01:16 Duration: 56ms Database: postgres parameters: $1 = 't', $2 = '558', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '160', $14 = 'AUDSGD', $15 = 'CHFSGD', $16 = 'EURDKK', $17 = 'EURHKD', $18 = 'EURNOK', $19 = 'EURPLN', $20 = 'EURSEK', $21 = 'EURSGD', $22 = 'EURTRY', $23 = 'EURZAR', $24 = 'GBPDKK', $25 = 'GBPNOK', $26 = 'GBPSEK', $27 = 'GBPSGD', $28 = 'NOKJPY', $29 = 'NOKSEK', $30 = 'SEKJPY', $31 = 'SGDJPY', $32 = 'USDCNH', $33 = 'USDCZK', $34 = 'USDDKK', $35 = 'USDHKD', $36 = 'USDHUF', $37 = 'USDMXN', $38 = 'USDNOK', $39 = 'USDPLN', $40 = 'USDRUB', $41 = 'USDSEK', $42 = 'USDTHB', $43 = 'USDTRY', $44 = 'USDZAR', $45 = 'AUDUSD', $46 = 'EURUSD', $47 = 'GBPUSD', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDJPY', $51 = 'AUDCAD', $52 = 'AUDCHF', $53 = 'AUDJPY', $54 = 'AUDNZD', $55 = 'CADCHF', $56 = 'CADJPY', $57 = 'CHFJPY', $58 = 'EURAUD', $59 = 'EURCAD', $60 = 'EURCHF', $61 = 'EURGBP', $62 = 'EURJPY', $63 = 'EURNZD', $64 = 'GBPAUD', $65 = 'GBPCAD', $66 = 'GBPCHF', $67 = 'GBPJPY', $68 = 'GBPNZD', $69 = 'NZDCAD', $70 = 'NZDCHF', $71 = 'NZDJPY', $72 = 'NZDUSD', $73 = 'USDSGD', $74 = 'AUS200', $75 = 'DE30', $76 = 'ES35', $77 = 'F40', $78 = 'HK50', $79 = 'IT40', $80 = 'JP225', $81 = 'STOXX50', $82 = 'UK100', $83 = 'US2000', $84 = 'US30', $85 = 'US500', $86 = 'CHINA50', $87 = 'USTEC', $88 = 'XAGEUR', $89 = 'XAGUSD', $90 = 'XAUUSD', $91 = 'XAUEUR', $92 = 'XPDUSD', $93 = 'XPTUSD', $94 = 'AUDSGD', $95 = 'CHFSGD', $96 = 'EURDKK', $97 = 'EURHKD', $98 = 'EURNOK', $99 = 'EURPLN', $100 = 'EURSEK', $101 = 'EURSGD', $102 = 'EURTRY', $103 = 'EURZAR', $104 = 'GBPDKK', $105 = 'GBPNOK', $106 = 'GBPSEK', $107 = 'GBPSGD', $108 = 'NOKJPY', $109 = 'NOKSEK', $110 = 'SEKJPY', $111 = 'SGDJPY', $112 = 'USDCNH', $113 = 'USDCZK', $114 = 'USDDKK', $115 = 'USDHKD', $116 = 'USDHUF', $117 = 'USDMXN', $118 = 'USDNOK', $119 = 'USDPLN', $120 = 'USDRUB', $121 = 'USDSEK', $122 = 'USDTHB', $123 = 'USDTRY', $124 = 'USDZAR', $125 = 'AUDUSD', $126 = 'EURUSD', $127 = 'GBPUSD', $128 = 'USDCAD', $129 = 'USDCHF', $130 = 'USDJPY', $131 = 'AUDCAD', $132 = 'AUDCHF', $133 = 'AUDJPY', $134 = 'AUDNZD', $135 = 'CADCHF', $136 = 'CADJPY', $137 = 'CHFJPY', $138 = 'EURAUD', $139 = 'EURCAD', $140 = 'EURCHF', $141 = 'EURGBP', $142 = 'EURJPY', $143 = 'EURNZD', $144 = 'GBPAUD', $145 = 'GBPCAD', $146 = 'GBPCHF', $147 = 'GBPJPY', $148 = 'GBPNZD', $149 = 'NZDCAD', $150 = 'NZDCHF', $151 = 'NZDJPY', $152 = 'NZDUSD', $153 = 'USDSGD', $154 = 'AUS200', $155 = 'DE30', $156 = 'ES35', $157 = 'F40', $158 = 'HK50', $159 = 'IT40', $160 = 'JP225', $161 = 'STOXX50', $162 = 'UK100', $163 = 'US2000', $164 = 'US30', $165 = 'US500', $166 = 'CHINA50', $167 = 'USTEC', $168 = 'XAGEUR', $169 = 'XAGUSD', $170 = 'XAUUSD', $171 = 'XAUEUR', $172 = 'XPDUSD', $173 = 'XPTUSD', $174 = '0', $175 = '', $176 = '0', $177 = '0', $178 = '0', $179 = '500', $180 = '500', $181 = 't', $182 = '10', $183 = '10'
WITH rar_max as ( ;

Date: 2026-01-05 09:11:08 Duration: 55ms Database: postgres parameters: $1 = 't', $2 = '958', $3 = '3', $4 = '60', $5 = '240', $6 = '1440', $7 = '0', $8 = '', $9 = '50', $10 = 'AUDCAD', $11 = 'AUDJPY', $12 = 'AUDUSD', $13 = 'EURAUD', $14 = 'EURCHF', $15 = 'EURGBP', $16 = 'EURJPY', $17 = 'EURMXN', $18 = 'EURUSD', $19 = 'GBPJPY', $20 = 'GBPUSD', $21 = 'NZDUSD', $22 = 'USDCAD', $23 = 'USDCHF', $24 = 'USDJPY', $25 = 'USDMXN', $26 = 'BTCUSD', $27 = 'ETHUSD', $28 = 'LTCUSD', $29 = 'AAPL.US', $30 = 'AMD.US', $31 = 'AMZN.US', $32 = 'BABA.US', $33 = 'BRK.B.US', $34 = 'GOOG.US', $35 = 'INTC.US', $36 = 'META.US', $37 = 'MSFT.US', $38 = 'NFLX.US', $39 = 'NKE.US', $40 = 'NVDA.US', $41 = 'PYPL.US', $42 = 'TSLA.US', $43 = 'V.US', $44 = 'Cocoa', $45 = 'Coffee', $46 = 'NatGas', $47 = 'SpotBrent', $48 = 'XAGUSD', $49 = 'XAUUSD', $50 = 'AUS200', $51 = 'EUSTX50', $52 = 'FRA40', $53 = 'GER40', $54 = 'HK50', $55 = 'JPN225', $56 = 'NAS100', $57 = 'UK100', $58 = 'US30', $59 = 'US500', $60 = '0', $61 = '', $62 = '0', $63 = '0', $64 = '0', $65 = '700', $66 = '700', $67 = 't', $68 = '10', $69 = '10'
WITH rar_max as ( ;

Date: 2026-01-05 09:25:16 Duration: 43ms Database: postgres parameters: $1 = '607449402474274301', $2 = '607449402474274301', $3 = '607449402474274301'

2

8s875ms

23,991

Details

0ms

17ms

0ms

SELECT ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	09	23,991	8s875ms	0ms

SELECT ;

Date: 2026-01-05 09:24:45 Duration: 17ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '515840243267806300'
SELECT ;

Date: 2026-01-05 09:00:04 Duration: 12ms Database: postgres parameters: $1 = '558', $2 = '0', $3 = '0', $4 = 'NZDCAD', $5 = 'NZDCAD'
SELECT ;

Date: 2026-01-05 09:01:16 Duration: 11ms Database: postgres parameters: $1 = '515840243245614300'

3

2s271ms

1,009

Details

1ms

8ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	09	1,009	2s271ms	2ms

SELECT symbolid, ;

Date: 2026-01-05 09:15:49 Duration: 8ms Database: postgres parameters: $1 = 'AXIORY', $2 = '15', $3 = 'EURCZK', $4 = 'EURCAD', $5 = 'EURCNH', $6 = 'EURAUD', $7 = 'EURCHF'
SELECT symbolid, ;

Date: 2026-01-05 09:31:01 Duration: 4ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'RK_HSI', $4 = 'NZDUSD.ID', $5 = 'OIL', $6 = 'RK_SSI', $7 = 'NZDUSD.FX', $8 = 'R_HSI'
SELECT symbolid, ;

Date: 2026-01-05 09:45:55 Duration: 3ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '15', $3 = 'NZDUSD', $4 = 'NZDJPY', $5 = 'NZDCHF', $6 = 'SPX500', $7 = 'TRXUSD'

4

1s383ms

189

Details

0ms

39ms

7ms

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

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	09	189	1s383ms	7ms

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

Date: 2026-01-05 09:10:57 Duration: 39ms Database: postgres parameters: $1 = '538', $2 = '538'
select distinct s.statsid as statsid, sy.exchange as name;

Date: 2026-01-05 09:10:56 Duration: 37ms Database: postgres parameters: $1 = '489', $2 = '489'
select distinct s.statsid as statsid, sy.exchange as name;

Date: 2026-01-05 09:10:57 Duration: 35ms Database: postgres parameters: $1 = '538', $2 = '538'

5

769ms

8,854

Details

0ms

31ms

0ms

select category, ;

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	09	8,854	769ms	0ms

select category, ;

Date: 2026-01-05 09:10:58 Duration: 31ms Database: postgres parameters: $1 = '601729875346766307', $2 = 'symbol', $3 = 'JPN225', $4 = 'USA30', $5 = 'UK100', $6 = 'USA100', $7 = 'AUS200', $8 = 'USDIndex', $9 = 'NETH25', $10 = 'FRA40', $11 = 'UK100', $12 = 'SUI20', $13 = 'USDIndex', $14 = 'USA30', $15 = 'JPN225', $16 = 'AUS200', $17 = 'USA100', $18 = 'SPA35', $19 = 'SUI20', $20 = 'FRA40', $21 = 'SPA35', $22 = 'NETH25', $23 = '601729875346766307', $24 = 'symbol', $25 = 'JPN225', $26 = 'USA30', $27 = 'UK100', $28 = 'USA100', $29 = 'AUS200', $30 = 'USDIndex', $31 = 'NETH25', $32 = 'FRA40', $33 = 'UK100', $34 = 'SUI20', $35 = 'USDIndex', $36 = 'USA30', $37 = 'JPN225', $38 = 'AUS200', $39 = 'USA100', $40 = 'SPA35', $41 = 'SUI20', $42 = 'FRA40', $43 = 'SPA35', $44 = 'NETH25'
select category, ;

Date: 2026-01-05 09:11:02 Duration: 13ms Database: postgres parameters: $1 = '601729875366045307', $2 = 'breakout', $3 = '601729875366045307', $4 = 'breakout'
select category, ;

Date: 2026-01-05 09:11:02 Duration: 8ms Database: postgres parameters: $1 = '515852059309933307', $2 = 'symbol', $3 = 'NZDJPY', $4 = 'CADJPY', $5 = 'XAUUSD', $6 = 'GBPJPY', $7 = 'USDJPY', $8 = 'CHFJPY', $9 = 'XAGUSD', $10 = 'EURJPY', $11 = 'GBPNZD', $12 = 'EURNZD', $13 = 'GBPCAD', $14 = 'EURCAD', $15 = 'CADCHF', $16 = 'USDCAD', $17 = 'EURCHF', $18 = 'GBPUSD', $19 = 'GBPCAD', $20 = 'CADJPY', $21 = 'EURNZD', $22 = 'EURCAD', $23 = 'NZDUSD', $24 = 'GBPCHF', $25 = 'GBPCHF', $26 = 'XAUUSD', $27 = 'XAGUSD', $28 = 'GBPUSD', $29 = 'GBPJPY', $30 = 'EURUSD', $31 = 'NZDJPY', $32 = 'USDJPY', $33 = 'AUDUSD', $34 = 'USDCAD', $35 = 'USDCHF', $36 = 'EURJPY', $37 = 'EURUSD', $38 = 'GBPNZD', $39 = 'CHFJPY', $40 = 'USDCHF', $41 = 'AUDUSD', $42 = 'NZDUSD', $43 = 'EURCHF', $44 = 'CADCHF', $45 = '515852059309933307', $46 = 'symbol', $47 = 'NZDJPY', $48 = 'CADJPY', $49 = 'XAUUSD', $50 = 'GBPJPY', $51 = 'USDJPY', $52 = 'CHFJPY', $53 = 'XAGUSD', $54 = 'EURJPY', $55 = 'GBPNZD', $56 = 'EURNZD', $57 = 'GBPCAD', $58 = 'EURCAD', $59 = 'CADCHF', $60 = 'USDCAD', $61 = 'EURCHF', $62 = 'GBPUSD', $63 = 'GBPCAD', $64 = 'CADJPY', $65 = 'EURNZD', $66 = 'EURCAD', $67 = 'NZDUSD', $68 = 'GBPCHF', $69 = 'GBPCHF', $70 = 'XAUUSD', $71 = 'XAGUSD', $72 = 'GBPUSD', $73 = 'GBPJPY', $74 = 'EURUSD', $75 = 'NZDJPY', $76 = 'USDJPY', $77 = 'AUDUSD', $78 = 'USDCAD', $79 = 'USDCHF', $80 = 'EURJPY', $81 = 'EURUSD', $82 = 'GBPNZD', $83 = 'CHFJPY', $84 = 'USDCHF', $85 = 'AUDUSD', $86 = 'NZDUSD', $87 = 'EURCHF', $88 = 'CADCHF'

6

729ms

25

Details

0ms

54ms

29ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	09	25	729ms	29ms

with wh_patitioned as ( ;

Date: 2026-01-05 09:01:15 Duration: 54ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2026-01-05 09:01:40 Duration: 51ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2026-01-05 09:55:48 Duration: 49ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'

7

678ms

418

Details

1ms

2ms

1ms

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

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	09	418	678ms	1ms

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

Date: 2026-01-05 09:46:02 Duration: 2ms Database: postgres parameters: $1 = 'MILLENNIUMPF'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-01-05 09:46:03 Duration: 2ms Database: postgres parameters: $1 = 'PEPPERSTONE'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-01-05 09:15:49 Duration: 2ms Database: postgres parameters: $1 = 'MILLENNIUMPF'

8

568ms

35,540

Details

0ms

3ms

0ms

select 1;

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	09	35,540	568ms	0ms

select 1;

Date: 2026-01-05 09:24:20 Duration: 3ms Database: postgres
select 1;

Date: 2026-01-05 09:00:04 Duration: 2ms Database: postgres
select 1;

Date: 2026-01-05 09:50:36 Duration: 2ms Database: postgres

9

362ms

12

Details

28ms

44ms

30ms

with sym_info as ( ;

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	09	12	362ms	30ms

with sym_info as ( ;

Date: 2026-01-05 09:06:57 Duration: 44ms Database: postgres parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'
with sym_info as ( ;

Date: 2026-01-05 09:21:41 Duration: 30ms 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: 2026-01-05 09:06:46 Duration: 30ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'

10

344ms

466

Details

0ms

12ms

0ms

SELECT absolutetimezoneoffset;

Times Reported Time consuming bind #10

Day	Hour	Count	Duration	Avg duration
	09	466	344ms	0ms

SELECT absolutetimezoneoffset;

Date: 2026-01-05 09:10:56 Duration: 12ms Database: postgres parameters: $1 = '489', $2 = 'BROKER'
SELECT absolutetimezoneoffset;

Date: 2026-01-05 09:11:02 Duration: 2ms Database: postgres parameters: $1 = '692', $2 = 'FOREX'
SELECT absolutetimezoneoffset;

Date: 2026-01-05 09:10:57 Duration: 1ms Database: postgres parameters: $1 = '538', $2 = 'Commodities'

11

329ms

31

Details

0ms

19ms

10ms

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

Times Reported Time consuming bind #11

Day	Hour	Count	Duration	Avg duration
	09	31	329ms	10ms

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

Date: 2026-01-05 09:36:13 Duration: 19ms 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: 2026-01-05 09:26:19 Duration: 19ms 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: 2026-01-05 09:36:12 Duration: 19ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

12

313ms

46

Details

4ms

30ms

6ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #12

Day	Hour	Count	Duration	Avg duration
	09	46	313ms	6ms

WITH last_candle AS ( ;

Date: 2026-01-05 09:01:15 Duration: 30ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-01-05 09:01:34 Duration: 12ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-01-05 09:04:00 Duration: 11ms Database: postgres parameters: $1 = '558', $2 = '558'

13

240ms

5,773

Details

0ms

2ms

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 #13

Day	Hour	Count	Duration	Avg duration
	09	5,773	240ms	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: 2026-01-05 09:15:40 Duration: 2ms Database: postgres parameters: $1 = '2026-01-05 09:00:00', $2 = '10.07941', $3 = '10.09447', $4 = '10.07903', $5 = '10.09427', $6 = '1436', $7 = '500991628252276200', $8 = '0', $9 = '2026-01-05 09:15:40.238', $10 = '2026-01-05 09:15:40.127', $11 = '10.07941', $12 = '10.09447', $13 = '10.07903', $14 = '10.09427', $15 = '1436', $16 = '0', $17 = '2026-01-05 09:15:40.238', $18 = '2026-01-05 09:15:40.127'
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: 2026-01-05 09:47:40 Duration: 0ms Database: postgres parameters: $1 = '2026-01-05 09:15:00', $2 = '8721.2', $3 = '8726.4', $4 = '8720.1', $5 = '8722.4', $6 = '766', $7 = '515840248015086300', $8 = '0', $9 = '2026-01-05 09:47:40.469', $10 = '2026-01-05 09:47:40.212', $11 = '8721.2', $12 = '8726.4', $13 = '8720.1', $14 = '8722.4', $15 = '766', $16 = '0', $17 = '2026-01-05 09:47:40.469', $18 = '2026-01-05 09:47:40.212'
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: 2026-01-05 09:56:53 Duration: 0ms Database: postgres parameters: $1 = '2026-01-05 09:30:00', $2 = '25277.8', $3 = '25278.8', $4 = '25259.8', $5 = '25269.17', $6 = '2455', $7 = '515840248038958300', $8 = '0', $9 = '2026-01-05 09:56:53.018', $10 = '2026-01-05 09:56:52.941', $11 = '25277.8', $12 = '25278.8', $13 = '25259.8', $14 = '25269.17', $15 = '2455', $16 = '0', $17 = '2026-01-05 09:56:53.018', $18 = '2026-01-05 09:56:52.941'

14

229ms

3,382

Details

0ms

1ms

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 #14

Day	Hour	Count	Duration	Avg duration
	09	3,382	229ms	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: 2026-01-05 09:01:04 Duration: 1ms Database: postgres parameters: $1 = '2026-01-05 08:30:00', $2 = '75.4955', $3 = '75.532', $4 = '75.354', $5 = '75.4695', $6 = '6103', $7 = '515840230625412300', $8 = '0', $9 = '2026-01-05 09:01:04.811', $10 = '2026-01-05 09:01:04.784', $11 = '75.4955', $12 = '75.532', $13 = '75.354', $14 = '75.4695', $15 = '6103', $16 = '0', $17 = '2026-01-05 09:01:04.811', $18 = '2026-01-05 09:01:04.784'
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: 2026-01-05 09:41:40 Duration: 0ms Database: postgres parameters: $1 = '2026-01-05 09:00:00', $2 = '8727.4', $3 = '8728.7', $4 = '8720.1', $5 = '8722.4', $6 = '1367', $7 = '515840248015340300', $8 = '0', $9 = '2026-01-05 09:41:40.047', $10 = '2026-01-05 09:41:39.963', $11 = '8727.4', $12 = '8728.7', $13 = '8720.1', $14 = '8722.4', $15 = '1367', $16 = '0', $17 = '2026-01-05 09:41:40.047', $18 = '2026-01-05 09:41:39.963'
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: 2026-01-05 09:10:51 Duration: 0ms Database: postgres parameters: $1 = '2026-01-02 22:30:00', $2 = '9991.2', $3 = '9999.9', $4 = '9983.9', $5 = '9999.1', $6 = '4392', $7 = '515840247999481300', $8 = '0', $9 = '2026-01-05 09:10:51.057', $10 = '2026-01-05 09:10:51.015', $11 = '9991.2', $12 = '9999.9', $13 = '9983.9', $14 = '9999.1', $15 = '4392', $16 = '0', $17 = '2026-01-05 09:10:51.057', $18 = '2026-01-05 09:10:51.015'

15

172ms

2,309

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 #15

Day	Hour	Count	Duration	Avg duration
	09	2,309	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: 2026-01-05 09:30:40 Duration: 0ms Database: postgres parameters: $1 = '2026-01-02 23:00:00', $2 = '270.355', $3 = '271.025', $4 = '270.22', $5 = '271.01', $6 = '2203', $7 = '515840249386608300', $8 = '0', $9 = '2026-01-05 09:30:40.271', $10 = '2026-01-05 09:30:40.211', $11 = '270.355', $12 = '271.025', $13 = '270.22', $14 = '271.01', $15 = '2203', $16 = '0', $17 = '2026-01-05 09:30:40.271', $18 = '2026-01-05 09:30:40.211'
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: 2026-01-05 09:02:54 Duration: 0ms Database: postgres parameters: $1 = '2026-01-05 07:00:00', $2 = '25290.78', $3 = '25304.9', $4 = '25270.4', $5 = '25300.78', $6 = '8896', $7 = '515840248039327300', $8 = '0', $9 = '2026-01-05 09:02:54.435', $10 = '2026-01-05 09:02:54.338', $11 = '25290.78', $12 = '25304.9', $13 = '25270.4', $14 = '25300.78', $15 = '8896', $16 = '0', $17 = '2026-01-05 09:02:54.435', $18 = '2026-01-05 09:02:54.338'
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: 2026-01-05 09:01:05 Duration: 0ms Database: postgres parameters: $1 = '2026-01-05 08:00:00', $2 = '3.603', $3 = '3.603', $4 = '3.598', $5 = '3.599', $6 = '181', $7 = '515840243916351300', $8 = '0', $9 = '2026-01-05 09:01:05.249', $10 = '2026-01-05 09:01:05.248', $11 = '3.603', $12 = '3.603', $13 = '3.598', $14 = '3.599', $15 = '181', $16 = '0', $17 = '2026-01-05 09:01:05.249', $18 = '2026-01-05 09:01:05.248'

16

146ms

389

Details

0ms

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

Times Reported Time consuming bind #16

Day	Hour	Count	Duration	Avg duration
	09	389	146ms	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: 2026-01-05 09:14:52 Duration: 0ms Database: postgres
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2026-01-05 09:14:53 Duration: 0ms Database: postgres
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2026-01-05 09:14:52 Duration: 0ms Database: postgres

17

91ms

18

Details

3ms

9ms

5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #17

Day	Hour	Count	Duration	Avg duration
	09	18	91ms	5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-05 09:01:01 Duration: 9ms Database: postgres parameters: $1 = '627', $2 = '627'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-05 09:01:22 Duration: 9ms Database: postgres parameters: $1 = '627', $2 = '627'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-05 09:11:08 Duration: 6ms Database: postgres parameters: $1 = '958', $2 = '958'

18

56ms

932

Details

0ms

1ms

0ms

select distinct category;

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	09	932	56ms	0ms

select distinct category;

Date: 2026-01-05 09:10:57 Duration: 1ms Database: postgres parameters: $1 = '601729875343618307'
select distinct category;

Date: 2026-01-05 09:10:57 Duration: 0ms Database: postgres parameters: $1 = '601729875343618307', $2 = '601729875343618307'
select distinct category;

Date: 2026-01-05 09:10:56 Duration: 0ms Database: postgres parameters: $1 = '515852059297940307', $2 = '515852059297940307'

19

51ms

466

Details

0ms

1ms

0ms

SELECT name;

Times Reported Time consuming bind #19

Day	Hour	Count	Duration	Avg duration
	09	466	51ms	0ms

SELECT name;

Date: 2026-01-05 09:10:56 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307', $2 = '515852059317765307'
SELECT name;

Date: 2026-01-05 09:10:56 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307', $2 = '515852059317765307'
SELECT name;

Date: 2026-01-05 09:10:56 Duration: 0ms Database: postgres parameters: $1 = '515852059317765307', $2 = '515852059317765307'

20

46ms

12

Details

1ms

7ms

3ms

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

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	09	12	46ms	3ms

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

Date: 2026-01-05 09:14:51 Duration: 7ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'
WITH pre_symbols AS ( /* find relevant symbols */ ;

Date: 2026-01-05 09:14:51 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: 2026-01-05 09:14:51 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'

Log levels

Key values

511,292 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	689	0.13%
DETAIL	115,768	22.64%
ERROR	1	0.00%
LOG	393,997	77.06%
STATEMENT	837	0.16%

Events distribution

Key values

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

Most Frequent Errors/Events

Key values

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

Rank

Times reported

Error

1

Details

ERROR: relation "..." does not exist

Times Reported Most Frequent Error / Event #1

Day	Hour	Count
Jan 05	09	1

ERROR: relation "t0" does not exist at character 83

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

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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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Type of locks

Most frequent waiting queries (N)

Queries that waited the most

Queries

Queries by type

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Queries by database

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Queries by user

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Duration by user