pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Thu Feb 5 14:02:26 2026
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-02-05_150000.log, ..., /home/postgres/pg_data/data/pg_log/postgresql-2026-02-05_154804.log
Parsed 8,168,928 log entries in 3m25s
Log start from 2026-02-05 15:00:00 to 2026-02-05 16:00:00

Global Stats

274 Number of unique normalized queries
784,883 Number of queries
3h11m16s Total query duration
2026-02-05 15:00:00 First query
2026-02-05 16:00:00 Last query
4,210 queries/s at 2026-02-05 15:00:04 Query peak

3h11m16s Total query duration
1m17s Prepare/parse total duration
3m50s Bind total duration
3h6m8s 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

53 Total number of automatic vacuums
56 Total number of automatic analyzes

970 Number temporary file
170.20 MiB Max size of temporary file
6.07 MiB Average size of temporary file

29,601 Total number of sessions
27 sessions at 2026-02-05 15:23:42 Session peak
2d23h29m24s Total duration of sessions
8s694ms Average duration of sessions
26 Average queries per session
387ms Average queries duration per session
8s306ms Average idle time per session

29,600 Total number of connections
122 connections/s at 2026-02-05 15:41:39 Connection peak
3 Total number of databases

SQL Traffic

Key values

4,210 queries/s Query Peak
2026-02-05 15:00:04 Date

SELECT Traffic

Key values

2,071 queries/s Query Peak
2026-02-05 15:00:04 Date

INSERT/UPDATE/DELETE Traffic

Key values

194 queries/s Query Peak
2026-02-05 15:01:52 Date

Queries duration

Key values

3h11m16s 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)
Feb 05	15	784,879	0ms	37s338ms	14ms	5m20s	5m28s	5m52s
	16	4	0ms	0ms	0ms	0ms	0ms	0ms

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Feb 05	15	283,366	26	0ms	0ms	0ms	0ms
	16	2	0	0ms	0ms	0ms	0ms

Day	Hour	INSERT	UPDATE	DELETE	COPY FROM	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Feb 05	15	32,636	3,633	16	96	0ms	0ms	0ms	0ms
	16	0	0	0	0	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Feb 05	15	159,116	348,623	2.19	47.55%
	16	1	2	2.00	50.00%

Day	Hour	Count	Average / Second
Feb 05	15	29,600	8.22/s
	16	0	0.00/s

Day	Hour	Count	Average Duration	Average idle time
Feb 05	15	29,601	8s694ms	8s317ms
	16	0	0ms	0ms

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Established Connections

Key values

122 connections Connection Peak
2026-02-05 15:41:39 Date

Connections per database

Key values

acaweb_fx Main Database
29,600 connections Total

Chart
Table

Database	User	Count
acaweb_fx		29,393
	postgres	29,036
	psql	357
socialmedia		207
	postgres	207

Connections per user

Key values

postgres Main User
29,600 connections Total

Chart
Table

User	Count
postgres	29,243
psql	357

Connections per host

Key values

192.168.1.15 Main host with 16898 connections
29,600 Total connections

Chart
Table

Host	Count
104.30.164.187	20
127.0.0.1	113
182.165.1.23	1
192.168.0.114	8
192.168.0.216	104
192.168.0.74	9,460
192.168.1.127	90
192.168.1.145	298
192.168.1.15	16,898
192.168.1.20	334
192.168.1.231	20
192.168.1.239	15
192.168.1.90	53
192.168.2.126	39
192.168.2.182	24
192.168.3.199	36
192.168.4.116	4
192.168.4.142	1,381
192.168.4.150	10
192.168.4.238	12
192.168.4.244	4
192.168.4.33	101
192.168.4.67	1
192.168.4.98	330
[local]	244

Simultaneous sessions

Key values

27 sessions Session Peak
2026-02-05 15:23:42 Date

Histogram of session times

Key values

27,184 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	27,184	91.83%
500ms-1s	244	0.82%
1s-30s	1,965	6.64%
30s-1m	59	0.20%
1m-10m	69	0.23%
10m-30m	61	0.21%
30m-1h	5	0.02%
1h-8h	14	0.05%
> 8h	0	0.00%

Sessions per database

Key values

acaweb_fx Main Database
29,601 sessions Total

Chart
Table

Database	User	Count	Total Duration	Average Duration
acaweb_fx	29,392	2d18h46m33s	8s178ms
socialmedia	209	4h42m50s	1m21s

Sessions per user

Key values

postgres Main User
29,601 sessions Total

Chart
Table

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

Sessions per host

Key values

192.168.1.15 Main Host
29,601 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
102.205.78.250	1	2h40m35s	2h40m35s
104.30.164.187	20	1h40m20s	5m1s
127.0.0.1	113	11s549ms	102ms
192.168.0.114	8	1h4m14s	8m1s
192.168.0.216	104	1m32s	894ms
192.168.0.74	9,460	5h58m39s	2s274ms
192.168.1.127	90	1m31s	1s15ms
192.168.1.145	298	7h12m24s	1m27s
192.168.1.15	16,898	4h30m4s	958ms
192.168.1.20	334	17h53m15s	3m12s
192.168.1.231	20	9h52m	29m36s
192.168.1.239	15	119ms	7ms
192.168.1.90	53	38s485ms	726ms
192.168.2.126	39	6s453ms	165ms
192.168.2.182	24	3s204ms	133ms
192.168.3.199	36	1s403ms	38ms
192.168.4.116	4	28s637ms	7s159ms
192.168.4.142	1,381	7m55s	344ms
192.168.4.150	10	20h3m37s	2h21s
192.168.4.238	12	15s614ms	1s301ms
192.168.4.244	4	42ms	10ms
192.168.4.33	102	16m21s	9s621ms
192.168.4.67	1	219ms	219ms
192.168.4.98	330	15s914ms	48ms
[local]	244	4m48s	1s183ms

Sessions per application

Key values

unknown Main Host
29,601 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	29,601	2d23h29m24s	8s694ms

Checkpoints Buffers

Key values

9,020 buffers Checkpoint Peak
2026-02-05 15:09:28 Date
209.941 seconds Highest write time
0.021 seconds Sync time

Checkpoints Wal files

Key values

6 files Wal files usage Peak
2026-02-05 15:09:28 Date

Checkpoints distance

Key values

191.46 Mo Distance Peak
2026-02-05 15:09:28 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Feb 05	15	52,796	2,156.579s	0.08s	2,157.023s
	16	0	0s	0s	0s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Feb 05	15	0	0	28	2,160	0.006s	0s
	16	0	0	0	0	0s	0s

Day	Hour	Count	Avg time (sec)
Feb 05	15	0	0s
	16	0	0s

Day	Hour	Mean distance	Mean estimate
Feb 05	15	37,249.42 kB	72,114.33 kB
	16	0.00 kB	0.00 kB

↑ Back to the top of the Checkpoint Activity table

Checkpoint causes

Key values

time (12) Main checkpoint cause
12 checkpoints Total

Chart
Table

Cause	Number of checkpoints
time	12
Total	12

Size of temporary files

Key values

183.92 MiB Temp Files size Peak
2026-02-05 15:00:08 Date

Number of temporary files

Key values

63 per second Temp Files Peak
2026-02-05 15:17:09 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Feb 05	15	970	5.75 GiB	6.07 MiB
	16	0	0	0

↑ 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	58	278.75 MiB	4.73 MiB	4.95 MiB	4.81 MiB	select resultuid from relevance_fibonacci_results order by resultuid desc limit ?), fr as ( select a., rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp)))), results as ( select distinct on (symbolid) from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc; SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1), fr AS ( SELECT a., rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4, $5, $6, $7, $8, $9, $10)) AND ($11 = 0 OR s.exchange in ($12)) AND ($13 = 0 OR coalesce(bim.code, s.symbol) in ($14)) AND ($15 = 0 OR fr.pattern in ($16)) AND ($17 = 0 OR fr.patternlengthbars <= $18) AND ($19 = 0 OR ($20 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($21 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) FROM all_results WHERE (FALSE = $22 OR relevant = 1) AND ($23 = 0 OR age <= $24) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-02-05 15:49:08 Duration: 0ms
2	33	211.83 MiB	2.98 MiB	8.53 MiB	6.42 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: 2026-02-05 15:48:42 Duration: 0ms
3	30	1.66 GiB	3.83 MiB	170.20 MiB	56.71 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: 2026-02-05 15:50:07 Duration: 0ms
4	16	620.25 MiB	38.77 MiB	38.77 MiB	38.77 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: 2026-02-05 15:48:13 Duration: 0ms
5	16	1.12 GiB	71.51 MiB	71.52 MiB	71.52 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: 2026-02-05 15:48:17 Duration: 0ms
6	8	1.05 GiB	134.42 MiB	134.47 MiB	134.45 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2026-02-05 15:50:32 Duration: 0ms
7	4	363.35 MiB	90.78 MiB	90.91 MiB	90.84 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2026-02-05 15:32:04 Duration: 0ms
8	3	9.26 MiB	3.09 MiB	3.09 MiB	3.09 MiB	select distinct p.id as processid, ? \|\| p.id \|\| ? \|\| b.name \|\| ? \|\| b.id \|\| ? \|\| ct.name \|\| ? \|\| p.locale \|\| ? \|\| coalesce(p.region, ?) as label, b.name, ct.name, p.locale, p.region from processes p left outer join executions e on e.processid = p.id inner join contenttypes ct on ct.id = p.contenttypeid inner join brokers b on b.id = p.brokerid order by b.name, ct.name, p.locale, p.region; SELECT DISTINCT p.id as processid, 'pid: ' \|\| p.id \|\| ' - ' \|\| b.name \|\| ' (' \|\| b.id \|\| ') ' \|\| ct.name \|\| ' ' \|\| p.locale \|\| ':' \|\| coalesce(p.region, '') as label, b.name, ct.name, p.locale, p.region from processes p left outer join executions e on e.processid = p.id inner join contenttypes ct on ct.id = p.contenttypeid inner join brokers b on b.id = p.brokerid ORDER BY b.name, ct.name, p.locale, p.region; Date: 2026-02-05 15:50:52 Duration: 0ms
9	2	6.14 MiB	3.07 MiB	3.07 MiB	3.07 MiB	select distinct leid.maxexecutionid as executionid, ? \|\| p.id \|\| ? \|\| b.name \|\| ? \|\| b.id \|\| ? \|\| ct.name \|\| ? \|\| p.locale \|\| ? \|\| coalesce(p.region, ?) as label, b.name, ct.name, p.locale, p.region from processes p inner join executions e on e.processid = p.id inner join contenttypes ct on ct.id = p.contenttypeid inner join brokers b on b.id = p.brokerid inner join latest_executionid_perprocess leid on leid.processid = p.id order by b.name, ct.name, p.locale, p.region; SELECT DISTINCT leid.maxexecutionid as executionid, 'pid: ' \|\| p.id \|\| ' - ' \|\| b.name \|\| ' (' \|\| b.id \|\| ') ' \|\| ct.name \|\| ' ' \|\| p.locale \|\| ':' \|\| coalesce(p.region, '') as label, b.name, ct.name, p.locale, p.region from processes p inner join executions e on e.processid = p.id inner join contenttypes ct on ct.id = p.contenttypeid inner join brokers b on b.id = p.brokerid inner join latest_executionid_perprocess leid on leid.processid = p.id ORDER BY b.name, ct.name, p.locale, p.region; Date: 2026-02-05 15:50:48 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	170.20 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: 2026-02-05 15:30:06 ]
2	169.33 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: 2026-02-05 15:10:04 ]
3	163.68 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-05 15:20:06 ]
4	134.47 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-05 15:32:14 ]
5	134.47 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-05 15:47:15 ]
6	134.46 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-05 15:35:33 ]
7	134.46 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-05 15:50:32 ]
8	134.46 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-05 15:17:15 ]
9	134.45 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-05 15:02:15 ]
10	134.44 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-05 15:20:32 ]
11	134.42 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-05 15:05:32 ]
12	128.91 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: 2026-02-05 15:40:04 ]
13	113.66 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-05 15:00:05 ]
14	110.12 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-05 15:00:05 ]
15	92.17 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 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: 2026-02-05 15:40:05 ]
16	90.91 MiB	select updateageforrelevantresults (); [ Date: 2026-02-05 15:02:05 ]
17	90.86 MiB	select updateageforrelevantresults (); [ Date: 2026-02-05 15:32:04 ]
18	90.79 MiB	select updateageforrelevantresults (); [ Date: 2026-02-05 15:17:05 ]
19	90.78 MiB	select updateageforrelevantresults (); [ Date: 2026-02-05 15:47:05 ]
20	82.05 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: 2026-02-05 15:50:05 ]

Vacuums / Analyzes Distribution

Key values

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

Analyzes per table

Key values

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

Chart
Table

Table	Number of analyzes
acaweb_fx.public.solr_relevance_old	16
acaweb_fx.pg_catalog.pg_attribute	6
acaweb_fx.public.relevance_keylevels_results	4
acaweb_fx.pg_catalog.pg_class	4
acaweb_fx.public.relevance_fibonacci_results	4
acaweb_fx.pg_catalog.pg_type	4
acaweb_fx.public.relevance_autochartist_results	4
acaweb_fx.public.datafeeds_latestrun	3
acaweb_fx.pg_catalog.pg_index	2
acaweb_fx.public.latest_t15_candle_view	2
acaweb_fx.pg_catalog.pg_depend	2
acaweb_fx.public.autochartist_symbolupdates	1
acaweb_fx.public.solr_imports	1
socialmedia.public.processes	1
acaweb_fx.public.latest_candle_datetime_per_receng	1
acaweb_fx.public.symbollatestupdatetime	1
Total	56

Vacuums per table

Key values

public.solr_relevance_old (26) Main table vacuumed on database acaweb_fx
53 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	26	18	21,152	0	83	0	145	12,018	1,211	6,466,419
acaweb_fx.pg_catalog.pg_attribute	4	4	3,376	0	637	0	268	1,468	559	3,276,960
acaweb_fx.public.relevance_autochartist_results	4	4	14,039	0	391	9	887	2,273	349	1,131,564
acaweb_fx.public.datafeeds_latestrun	3	0	360	0	5	0	0	39	5	36,376
acaweb_fx.pg_toast.pg_toast_2619	2	2	267	0	61	0	0	156	52	182,848
acaweb_fx.pg_catalog.pg_type	2	2	311	0	99	0	0	152	63	265,050
acaweb_fx.pg_catalog.pg_statistic	2	2	1,932	0	413	0	1,188	936	363	1,392,555
acaweb_fx.public.relevance_keylevels_results	2	2	7,531	0	203	4	188	1,886	189	636,727
acaweb_fx.pg_catalog.pg_class	2	2	930	0	163	0	0	310	146	642,779
acaweb_fx.public.relevance_fibonacci_results	2	2	2,616	0	56	4	86	504	41	125,575
acaweb_fx.pg_catalog.pg_index	1	1	105	0	11	0	0	27	10	74,970
acaweb_fx.public.autochartist_symbolupdates	1	1	23,264	0	2,902	2	38,201	6,426	4,825	1,874,701
acaweb_fx.pg_catalog.pg_depend	1	1	401	0	99	0	59	185	73	368,697
acaweb_fx.public.latest_t15_candle_view	1	1	71	0	1	0	0	6	1	9,031
Total	53	42	76,355	53,847	5,124	19	41,022	26,386	7,887	16,484,252

Tuples removed per table

Key values

public.solr_relevance_old (109425) Main table with removed tuples on database acaweb_fx
126276 tuples Total removed

Chart
Table

		Index	Tuples			Pages
Table	Vacuums	scans	removed	remain	not yet removable	removed	remain
acaweb_fx.public.solr_relevance_old	26	18	109,425	242,677	67,130	0	5,991
acaweb_fx.pg_catalog.pg_attribute	4	4	5,856	43,768	784	0	1,052
acaweb_fx.public.autochartist_symbolupdates	1	1	4,618	46,044	2	0	40,691
acaweb_fx.pg_catalog.pg_depend	1	1	1,229	14,410	0	0	140
acaweb_fx.public.relevance_autochartist_results	4	4	1,212	38,117	2,946	0	1,520
acaweb_fx.pg_catalog.pg_statistic	2	2	1,158	7,565	0	0	2,388
acaweb_fx.public.relevance_keylevels_results	2	2	1,077	25,279	0	0	558
acaweb_fx.pg_catalog.pg_type	2	2	735	2,892	0	10	78
acaweb_fx.public.relevance_fibonacci_results	2	2	336	3,173	0	0	204
acaweb_fx.pg_catalog.pg_class	2	2	290	3,298	0	0	300
acaweb_fx.public.datafeeds_latestrun	3	0	164	42	0	0	48
acaweb_fx.pg_toast.pg_toast_2619	2	2	114	360	30	3	99
acaweb_fx.public.latest_t15_candle_view	1	1	55	14	0	0	1
acaweb_fx.pg_catalog.pg_index	1	1	7	813	0	0	22
Total	53	42	126,276	428,452	70,892	13	53,092

Pages removed per table

Key values

pg_catalog.pg_type (10) Main table with removed pages on database acaweb_fx
13 pages Total removed

Chart
Table

Table	Number of vacuums	Index scans	Tuples removed	Pages removed
acaweb_fx.pg_catalog.pg_type	2	2	735	10
acaweb_fx.pg_toast.pg_toast_2619	2	2	114	3
acaweb_fx.pg_catalog.pg_index	1	1	7	0
acaweb_fx.public.autochartist_symbolupdates	1	1	4618	0
acaweb_fx.public.datafeeds_latestrun	3	0	164	0
acaweb_fx.pg_catalog.pg_statistic	2	2	1158	0
acaweb_fx.pg_catalog.pg_attribute	4	4	5856	0
acaweb_fx.pg_catalog.pg_depend	1	1	1229	0
acaweb_fx.public.latest_t15_candle_view	1	1	55	0
acaweb_fx.public.relevance_keylevels_results	2	2	1077	0
acaweb_fx.pg_catalog.pg_class	2	2	290	0
acaweb_fx.public.solr_relevance_old	26	18	109425	0
acaweb_fx.public.relevance_autochartist_results	4	4	1212	0
acaweb_fx.public.relevance_fibonacci_results	2	2	336	0
Total	53	42	126,276	13

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Feb 05	15	53	56
	16	0	0

↑ 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

283,368 Total read queries
51,237 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	283,368	36.10%
INSERT	32,636	4.16%
UPDATE	3,633	0.46%
DELETE	16	0.00%
COPY FROM	96	0.01%
COPY TO	26	0.00%
CTE	13,902	1.77%
DDL	16	0.00%
TCL	912	0.12%
CURSOR	0	0.00%
OTHERS	450,278	57.37%

Queries by database

Key values

unknown Main database
783,818 Requests
3h6m8s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	868	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	183	0ms
	select	72	0ms
	tcl	332	0ms
	update	39	0ms
socialmedia	Total	197	0ms
	others	90	0ms
	select	101	0ms
	tcl	6	0ms
unknown	Total	783,818	3h6m8s
	copy from	16	0ms
	cte	13,798	0ms
	insert	32,636	0ms
	others	57,565	0ms
	select	283,195	0ms
	tcl	574	0ms
	update	3,594	0ms

Queries by user

Key values

unknown Main user
783,818 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	1,065	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	273	0ms
	select	173	0ms
	tcl	338	0ms
	update	39	0ms
unknown	Total	783,818	3h6m8s
	copy from	16	0ms
	cte	13,798	0ms
	insert	32,636	0ms
	others	57,565	0ms
	select	283,195	0ms
	tcl	574	0ms
	update	3,594	0ms

Duration by user

Key values

3h6m8s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	1,065	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	273	0ms
	select	173	0ms
	tcl	338	0ms
	update	39	0ms
unknown	Total	783,818	3h6m8s
	copy from	16	0ms
	cte	13,798	0ms
	insert	32,636	0ms
	others	57,565	0ms
	select	283,195	0ms
	tcl	574	0ms
	update	3,594	0ms

Queries by host

Key values

unknown Main host
784,883 Requests
3h6m8s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	784,883	3h6m8s
	copy from	96	0ms
	copy to	26	0ms
	cte	13,902	0ms
	ddl	16	0ms
	delete	16	0ms
	insert	32,636	0ms
	others	57,838	0ms
	select	283,368	0ms
	tcl	912	0ms
	update	3,633	0ms

Queries by application

Key values

unknown Main application
784,526 Requests
3h6m8s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
psql	Total	357	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	4	0ms
	select	72	0ms
	update	39	0ms
unknown	Total	784,526	3h6m8s
	copy from	16	0ms
	cte	13,798	0ms
	insert	32,636	0ms
	others	57,834	0ms
	select	283,296	0ms
	tcl	912	0ms
	update	3,594	0ms

Number of cancelled queries

Key values

0 per second Cancelled query Peak
2026-02-05 15:23:06 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

257,047 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	257,047	65.50%
1-5ms	119,231	30.38%
5-10ms	8,848	2.25%
10-25ms	4,437	1.13%
25-50ms	305	0.08%
50-100ms	433	0.11%
100-500ms	496	0.13%
500-1000ms	246	0.06%
1000-10000ms	1,069	0.27%
> 10000ms	328	0.08%

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

55

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 05	15	55	0ms	0ms

2

0ms

8

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 #2

Day	Hour	Count	Duration	Avg duration
Feb 05	15	8	0ms	0ms

3

0ms

2,053

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 #3

Day	Hour	Count	Duration	Avg duration
Feb 05	15	2,053	0ms	0ms

4

0ms

119

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
Feb 05	15	119	0ms	0ms

5

0ms

4

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Feb 05	15	4	0ms	0ms

6

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Feb 05	15	4	0ms	0ms

7

0ms

90

Details

0ms

set datestyle = iso;

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Feb 05	15	90	0ms	0ms

8

0ms

90

Details

0ms

set client_encoding to ?;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Feb 05	15	90	0ms	0ms

9

0ms

18

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Feb 05	15	18	0ms	0ms

10

0ms

3

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 #10

Day	Hour	Count	Duration	Avg duration
Feb 05	15	3	0ms	0ms

11

0ms

456

Details

0ms

commit;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 05	15	456	0ms	0ms

12

0ms

502

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 #12

Day	Hour	Count	Duration	Avg duration
Feb 05	15	502	0ms	0ms

13

0ms

240

Details

0ms

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

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Feb 05	15	240	0ms	0ms

14

0ms

240

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 05	15	240	0ms	0ms

15

0ms

4

Details

0ms

select count(*) 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 ((("LT?"."name" = ?)) and (("public"."processes"."locale" = ?) or ("public"."processes"."locale" = ?))) and (brokerid = ?);

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Feb 05	15	4	0ms	0ms

16

0ms

10

Details

0ms

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

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 05	15	10	0ms	0ms

17

0ms

3

Details

0ms

select count(*) 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 ((("public"."processes"."locale" = ?) or ("public"."processes"."locale" = ?))) and (brokerid = ?);

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Feb 05	15	3	0ms	0ms

18

0ms

93

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 "public"."processes"."id" = ?;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 05	15	93	0ms	0ms

19

0ms

455

Details

0ms

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

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 05	15	455	0ms	0ms

20

0ms

24

Details

0ms

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

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 05	15	24	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

134,045

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 05	15	134,043	0ms	0ms
	16	2	0ms	0ms

2

115,539

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
Feb 05	15	115,539	0ms	0ms

3

28,473

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Feb 05	15	28,473	0ms	0ms

4

28,446

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Feb 05	15	28,446	0ms	0ms

5

8,361

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 #5

Day	Hour	Count	Duration	Avg duration
Feb 05	15	8,361	0ms	0ms

6

7,868

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Feb 05	15	7,868	0ms	0ms

7

6,874

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 #7

Day	Hour	Count	Duration	Avg duration
Feb 05	15	6,874	0ms	0ms

8

5,928

Details

0ms

select * from status_perbroker;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Feb 05	15	5,928	0ms	0ms

9

5,815

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 #9

Day	Hour	Count	Duration	Avg duration
Feb 05	15	5,815	0ms	0ms

10

5,564

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 #10

Day	Hour	Count	Duration	Avg duration
Feb 05	15	5,564	0ms	0ms

11

3,936

Details

0ms

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

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 05	15	3,936	0ms	0ms

12

3,135

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 #12

Day	Hour	Count	Duration	Avg duration
Feb 05	15	3,135	0ms	0ms

13

3,124

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 #13

Day	Hour	Count	Duration	Avg duration
Feb 05	15	3,124	0ms	0ms

14

3,072

Details

0ms

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

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 05	15	3,072	0ms	0ms

15

3,018

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 #15

Day	Hour	Count	Duration	Avg duration
Feb 05	15	3,018	0ms	0ms

16

2,814

Details

0ms

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

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 05	15	2,814	0ms	0ms

17

2,053

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 #17

Day	Hour	Count	Duration	Avg duration
Feb 05	15	2,053	0ms	0ms

18

1,228

Details

0ms

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

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 05	15	1,228	0ms	0ms

19

504

Details

0ms

select downloadersymbol, spike_threshold from price_datafeed_spike_threshold where classname = ?;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 05	15	504	0ms	0ms

20

504

Details

0ms

select s.symbolid, dss.downloadfrequency, dss.downloadersymbol from downloadersymbolsettings dss inner join symbols s on dss.symbolid = s.symbolid where dss.classname = ? and s.deleted = ? and dss.enabled = ?;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 05	15	504	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

55

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 05	15	55	0ms	0ms

2

0ms

8

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 #2

Day	Hour	Count	Duration	Avg duration
Feb 05	15	8	0ms	0ms

3

0ms

2,053

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 #3

Day	Hour	Count	Duration	Avg duration
Feb 05	15	2,053	0ms	0ms

4

0ms

119

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
Feb 05	15	119	0ms	0ms

5

0ms

4

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Feb 05	15	4	0ms	0ms

6

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Feb 05	15	4	0ms	0ms

7

0ms

90

Details

0ms

set datestyle = iso;

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Feb 05	15	90	0ms	0ms

8

0ms

90

Details

0ms

set client_encoding to ?;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Feb 05	15	90	0ms	0ms

9

0ms

18

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Feb 05	15	18	0ms	0ms

10

0ms

3

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 #10

Day	Hour	Count	Duration	Avg duration
Feb 05	15	3	0ms	0ms

11

0ms

456

Details

0ms

commit;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 05	15	456	0ms	0ms

12

0ms

502

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 #12

Day	Hour	Count	Duration	Avg duration
Feb 05	15	502	0ms	0ms

13

0ms

240

Details

0ms

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

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Feb 05	15	240	0ms	0ms

14

0ms

240

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 05	15	240	0ms	0ms

15

0ms

4

Details

0ms

select count(*) 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 ((("LT?"."name" = ?)) and (("public"."processes"."locale" = ?) or ("public"."processes"."locale" = ?))) and (brokerid = ?);

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Feb 05	15	4	0ms	0ms

16

0ms

10

Details

0ms

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

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 05	15	10	0ms	0ms

17

0ms

3

Details

0ms

select count(*) 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 ((("public"."processes"."locale" = ?) or ("public"."processes"."locale" = ?))) and (brokerid = ?);

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Feb 05	15	3	0ms	0ms

18

0ms

93

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 "public"."processes"."id" = ?;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 05	15	93	0ms	0ms

19

0ms

455

Details

0ms

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

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 05	15	455	0ms	0ms

20

0ms

24

Details

0ms

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

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 05	15	24	0ms	0ms

Time consuming prepare


Date: 2026-02-05 15:46:33
Duration: 28ms
Database: postgres
Date: 2026-02-05 15:08:00
Duration: 22ms
Database: postgres
Date: 2026-02-05 15:45:29
Duration: 17ms
Database: postgres
Date: 2026-02-05 15:45:50
Duration: 11ms
Database: postgres
Date: 2026-02-05 15:46:43
Duration: 4ms
Database: postgres
Date: 2026-02-05 15:46:02
Duration: 7ms
Database: postgres
Date: 2026-02-05 15:52:15
Duration: 8ms
Database: postgres
Date: 2026-02-05 15:30:49
Duration: 1ms
Database: postgres
Date: 2026-02-05 15:02:29
Duration: 0ms
Database: postgres
Date: 2026-02-05 15:31:06
Duration: 1ms
Database: postgres
Date: 2026-02-05 15:06:42
Duration: 7ms
Database: postgres
Date: 2026-02-05 15:08:01
Duration: 4ms
Database: postgres
Date: 2026-02-05 15:11:12
Duration: 4ms
Database: postgres
Date: 2026-02-05 15:14:27
Duration: 0ms
Database: postgres
Date: 2026-02-05 15:31:45
Duration: 2ms
Database: postgres
Date: 2026-02-05 15:01:23
Duration: 0ms
Database: postgres
Date: 2026-02-05 15:31:45
Duration: 1ms
Database: postgres
Date: 2026-02-05 15:02:03
Duration: 2ms
Database: postgres
Date: 2026-02-05 15:00:05
Duration: 3ms
Database: postgres
Date: 2026-02-05 15:40:02
Duration: 3ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

2m9s

127,934

Details

0ms

41ms

1ms

SELECT ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Feb 05	15	127,934	2m9s	1ms

SELECT ;

Date: 2026-02-05 15:31:10 Duration: 41ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840249415181300'
SELECT ;

Date: 2026-02-05 15:26:07 Duration: 34ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840243153282300'
SELECT ;

Date: 2026-02-05 15:58:34 Duration: 34ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840233379456300'

2

1m27s

12,744

Details

0ms

53ms

6ms

WITH rar_max as ( ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	15	12,744	1m27s	6ms

WITH rar_max as ( ;

Date: 2026-02-05 15:06:41 Duration: 53ms Database: postgres parameters: $1 = 't', $2 = '489', $3 = '0', $4 = '0', $5 = '0', $6 = '', $7 = '0', $8 = '', $9 = '0', $10 = '', $11 = '0', $12 = '0', $13 = '0', $14 = '0', $15 = '0', $16 = 't', $17 = '0', $18 = '0'
WITH rar_max as ( ;

Date: 2026-02-05 15:51:44 Duration: 49ms Database: postgres parameters: $1 = '538', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '125', $13 = 'ANGLO', $14 = 'BARC', $15 = 'BAY', $16 = 'BPLON', $17 = 'HSBCL', $18 = 'LLOY', $19 = 'RIO', $20 = 'RollsRoyce', $21 = 'TESCO', $22 = 'VOD', $23 = 'AUDCAD', $24 = 'AUDCHF', $25 = 'AUDJPY', $26 = 'AUDNZD', $27 = 'AUDUSD', $28 = 'CADCHF', $29 = 'CADJPY', $30 = 'CHFJPY', $31 = 'EURAUD', $32 = 'EURCAD', $33 = 'EURCHF', $34 = 'EURDKK', $35 = 'EURGBP', $36 = 'EURHUF', $37 = 'EURJPY', $38 = 'EURNOK', $39 = 'EURNZD', $40 = 'EURPLN', $41 = 'EURUSD', $42 = 'GBPAUD', $43 = 'GBPCAD', $44 = 'GBPCHF', $45 = 'GBPJPY', $46 = 'GBPNZD', $47 = 'GBPUSD', $48 = 'GBPZAR', $49 = 'NZDCAD', $50 = 'NZDCHF', $51 = 'NZDJPY', $52 = 'NZDUSD', $53 = 'USDCAD', $54 = 'USDCHF', $55 = 'USDCNH', $56 = 'USDCZK', $57 = 'USDDKK', $58 = 'USDHKD', $59 = 'USDHUF', $60 = 'USDJPY', $61 = 'USDMXN', $62 = 'USDNOK', $63 = 'USDPLN', $64 = 'USDSEK', $65 = 'USDSGD', $66 = 'USDTRY', $67 = 'USDZAR', $68 = 'XAGEUR', $69 = 'XAGUSD', $70 = 'XAUEUR', $71 = 'XAUUSD', $72 = 'ZARJPY', $73 = 'Cocoa', $74 = 'Coffee', $75 = 'Copper', $76 = 'Palladium', $77 = 'Platinum', $78 = 'Sugar', $79 = 'UKOIL', $80 = 'USOIL', $81 = 'AUS200', $82 = 'FRA40', $83 = 'JPN225', $84 = 'NETH25', $85 = 'SPA35', $86 = 'SUI20', $87 = 'UK100', $88 = 'USA100', $89 = 'USA30', $90 = 'USDIndex', $91 = 'ALCOA', $92 = 'ALIBABA', $93 = 'AMAZON', $94 = 'AMEX', $95 = 'APPLE', $96 = 'BBVA', $97 = 'BOA', $98 = 'BOEING', $99 = 'CHEVRON', $100 = 'CISCO', $101 = 'COKE', $102 = 'EBAY', $103 = 'GE', $104 = 'GOOGLE', $105 = 'GS', $106 = 'HLT', $107 = 'IBM', $108 = 'ILMN', $109 = 'INTEL', $110 = 'Iberdrola', $111 = 'MCARD', $112 = 'MCDON', $113 = 'META', $114 = 'MSFT', $115 = 'Mapfre', $116 = 'Netflix', $117 = 'PFIZER', $118 = 'QCOM', $119 = 'Santander', $120 = 'TEVA', $121 = 'Telefonica', $122 = 'Tesla', $123 = 'AUDUSD', $124 = 'EURGBP', $125 = 'EURUSD', $126 = 'GBPUSD', $127 = 'NZDUSD', $128 = 'USDCAD', $129 = 'USDCHF', $130 = 'USDJPY', $131 = 'Adidas', $132 = 'Bayer', $133 = 'Daimler', $134 = 'Danone', $135 = 'LVMH', $136 = 'Lufthansa', $137 = 'Volksw', $138 = '700', $139 = '700', $140 = 't', $141 = '10', $142 = '10'
WITH rar_max as ( ;

Date: 2026-02-05 15:46:07 Duration: 48ms Database: postgres parameters: $1 = '558', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '160', $13 = 'AUDSGD', $14 = 'CHFSGD', $15 = 'EURDKK', $16 = 'EURHKD', $17 = 'EURNOK', $18 = 'EURPLN', $19 = 'EURSEK', $20 = 'EURSGD', $21 = 'EURTRY', $22 = 'EURZAR', $23 = 'GBPDKK', $24 = 'GBPNOK', $25 = 'GBPSEK', $26 = 'GBPSGD', $27 = 'NOKJPY', $28 = 'NOKSEK', $29 = 'SEKJPY', $30 = 'SGDJPY', $31 = 'USDCNH', $32 = 'USDCZK', $33 = 'USDDKK', $34 = 'USDHKD', $35 = 'USDHUF', $36 = 'USDMXN', $37 = 'USDNOK', $38 = 'USDPLN', $39 = 'USDRUB', $40 = 'USDSEK', $41 = 'USDTHB', $42 = 'USDTRY', $43 = 'USDZAR', $44 = 'AUDUSD', $45 = 'EURUSD', $46 = 'GBPUSD', $47 = 'USDCAD', $48 = 'USDCHF', $49 = 'USDJPY', $50 = 'AUDCAD', $51 = 'AUDCHF', $52 = 'AUDJPY', $53 = 'AUDNZD', $54 = 'CADCHF', $55 = 'CADJPY', $56 = 'CHFJPY', $57 = 'EURAUD', $58 = 'EURCAD', $59 = 'EURCHF', $60 = 'EURGBP', $61 = 'EURJPY', $62 = 'EURNZD', $63 = 'GBPAUD', $64 = 'GBPCAD', $65 = 'GBPCHF', $66 = 'GBPJPY', $67 = 'GBPNZD', $68 = 'NZDCAD', $69 = 'NZDCHF', $70 = 'NZDJPY', $71 = 'NZDUSD', $72 = 'USDSGD', $73 = 'AUS200', $74 = 'DE30', $75 = 'ES35', $76 = 'F40', $77 = 'HK50', $78 = 'IT40', $79 = 'JP225', $80 = 'STOXX50', $81 = 'UK100', $82 = 'US2000', $83 = 'US30', $84 = 'US500', $85 = 'CHINA50', $86 = 'USTEC', $87 = 'XAGEUR', $88 = 'XAGUSD', $89 = 'XAUUSD', $90 = 'XAUEUR', $91 = 'XPDUSD', $92 = 'XPTUSD', $93 = 'AUDSGD', $94 = 'CHFSGD', $95 = 'EURDKK', $96 = 'EURHKD', $97 = 'EURNOK', $98 = 'EURPLN', $99 = 'EURSEK', $100 = 'EURSGD', $101 = 'EURTRY', $102 = 'EURZAR', $103 = 'GBPDKK', $104 = 'GBPNOK', $105 = 'GBPSEK', $106 = 'GBPSGD', $107 = 'NOKJPY', $108 = 'NOKSEK', $109 = 'SEKJPY', $110 = 'SGDJPY', $111 = 'USDCNH', $112 = 'USDCZK', $113 = 'USDDKK', $114 = 'USDHKD', $115 = 'USDHUF', $116 = 'USDMXN', $117 = 'USDNOK', $118 = 'USDPLN', $119 = 'USDRUB', $120 = 'USDSEK', $121 = 'USDTHB', $122 = 'USDTRY', $123 = 'USDZAR', $124 = 'AUDUSD', $125 = 'EURUSD', $126 = 'GBPUSD', $127 = 'USDCAD', $128 = 'USDCHF', $129 = 'USDJPY', $130 = 'AUDCAD', $131 = 'AUDCHF', $132 = 'AUDJPY', $133 = 'AUDNZD', $134 = 'CADCHF', $135 = 'CADJPY', $136 = 'CHFJPY', $137 = 'EURAUD', $138 = 'EURCAD', $139 = 'EURCHF', $140 = 'EURGBP', $141 = 'EURJPY', $142 = 'EURNZD', $143 = 'GBPAUD', $144 = 'GBPCAD', $145 = 'GBPCHF', $146 = 'GBPJPY', $147 = 'GBPNZD', $148 = 'NZDCAD', $149 = 'NZDCHF', $150 = 'NZDJPY', $151 = 'NZDUSD', $152 = 'USDSGD', $153 = 'AUS200', $154 = 'DE30', $155 = 'ES35', $156 = 'F40', $157 = 'HK50', $158 = 'IT40', $159 = 'JP225', $160 = 'STOXX50', $161 = 'UK100', $162 = 'US2000', $163 = 'US30', $164 = 'US500', $165 = 'CHINA50', $166 = 'USTEC', $167 = 'XAGEUR', $168 = 'XAGUSD', $169 = 'XAUUSD', $170 = 'XAUEUR', $171 = 'XPDUSD', $172 = 'XPTUSD', $173 = '500', $174 = '500', $175 = 't', $176 = '10', $177 = '10'

3

3s719ms

133,932

Details

0ms

12ms

0ms

select 1;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	15	133,930	3s718ms	0ms
	16	2	0ms	0ms

select 1;

Date: 2026-02-05 15:52:00 Duration: 12ms Database: postgres
select 1;

Date: 2026-02-05 15:52:00 Duration: 12ms Database: postgres
select 1;

Date: 2026-02-05 15:26:54 Duration: 7ms Database: postgres

4

3s548ms

1,349

Details

1ms

12ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	15	1,349	3s548ms	2ms

SELECT symbolid, ;

Date: 2026-02-05 15:47:10 Duration: 12ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'GBPJPY', $4 = 'GBPCHF.ID'
SELECT symbolid, ;

Date: 2026-02-05 15:46:20 Duration: 12ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'XAGUSD.FX'
SELECT symbolid, ;

Date: 2026-02-05 15:46:39 Duration: 10ms Database: postgres parameters: $1 = 'ATFX', $2 = '15', $3 = 'JP225'

5

1s278ms

149

Details

4ms

30ms

8ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	15	149	1s278ms	8ms

WITH last_candle AS ( ;

Date: 2026-02-05 15:52:00 Duration: 30ms Database: postgres parameters: $1 = '529', $2 = '529'
WITH last_candle AS ( ;

Date: 2026-02-05 15:16:01 Duration: 25ms Database: postgres parameters: $1 = '958', $2 = '958'
WITH last_candle AS ( ;

Date: 2026-02-05 15:52:00 Duration: 22ms Database: postgres parameters: $1 = '529', $2 = '529'

6

883ms

504

Details

1ms

4ms

1ms

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

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	15	504	883ms	1ms

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

Date: 2026-02-05 15:30:52 Duration: 4ms Database: postgres parameters: $1 = 'AXIORY'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-02-05 15:46:04 Duration: 3ms Database: postgres parameters: $1 = 'GLOBALGTMT5'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-02-05 15:46:40 Duration: 2ms Database: postgres parameters: $1 = 'ICMARKETS'

7

687ms

71

Details

0ms

20ms

9ms

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

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	15	71	687ms	9ms

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

Date: 2026-02-05 15:06:04 Duration: 20ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;

Date: 2026-02-05 15:46:40 Duration: 19ms Database: postgres parameters: $1 = '489', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;

Date: 2026-02-05 15:24:27 Duration: 19ms Database: postgres parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

8

656ms

27

Details

0ms

42ms

24ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	15	27	656ms	24ms

with wh_patitioned as ( ;

Date: 2026-02-05 15:37:36 Duration: 42ms 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: 2026-02-05 15:24:06 Duration: 41ms 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: 2026-02-05 15:55:01 Duration: 41ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'

9

546ms

12

Details

44ms

51ms

45ms

with sym_info as ( ;

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	15	12	546ms	45ms

with sym_info as ( ;

Date: 2026-02-05 15:51:48 Duration: 51ms Database: postgres parameters: $1 = '627', $2 = 'Forex', $3 = 'Forex', $4 = '627', $5 = 'Forex', $6 = '627', $7 = '627', $8 = 'Forex', $9 = '627'
with sym_info as ( ;

Date: 2026-02-05 15:51:53 Duration: 46ms 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: 2026-02-05 15:36:41 Duration: 45ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'

10

306ms

5,815

Details

0ms

1ms

0ms

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

Times Reported Time consuming bind #10

Day	Hour	Count	Duration	Avg duration
	15	5,815	306ms	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: 2026-02-05 15:47:52 Duration: 1ms Database: postgres parameters: $1 = '2026-02-05 15:15:00', $2 = '8836.31', $3 = '8850.31', $4 = '8830.31', $5 = '8838.31', $6 = '316', $7 = '515840238058964300', $8 = '0', $9 = '2026-02-05 15:47:52.299', $10 = '2026-02-05 15:47:52.249', $11 = '8836.31', $12 = '8850.31', $13 = '8830.31', $14 = '8838.31', $15 = '316', $16 = '0', $17 = '2026-02-05 15:47:52.299', $18 = '2026-02-05 15:47:52.249'
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: 2026-02-05 15:55:58 Duration: 0ms Database: postgres parameters: $1 = '2026-02-05 15:15:00', $2 = '49314.79', $3 = '49346.34', $4 = '49293.79', $5 = '49342.79', $6 = '6058', $7 = '515840248000537300', $8 = '0', $9 = '2026-02-05 15:55:58.593', $10 = '2026-02-05 15:55:58.521', $11 = '49314.79', $12 = '49346.34', $13 = '49293.79', $14 = '49342.79', $15 = '6058', $16 = '0', $17 = '2026-02-05 15:55:58.593', $18 = '2026-02-05 15:55:58.521'
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: 2026-02-05 15:48:01 Duration: 0ms Database: postgres parameters: $1 = '2026-02-05 00:30:00', $2 = '1138.3695', $3 = '1141.239', $4 = '1128.4585', $5 = '1129.504', $6 = '1951', $7 = '515840249472960300', $8 = '0', $9 = '2026-02-05 15:48:01.638', $10 = '2026-02-05 15:48:01.569', $11 = '1138.3695', $12 = '1141.239', $13 = '1128.4585', $14 = '1129.504', $15 = '1951', $16 = '0', $17 = '2026-02-05 15:48:01.638', $18 = '2026-02-05 15:48:01.569'

11

277ms

3,124

Details

0ms

5ms

0ms

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

Times Reported Time consuming bind #11

Day	Hour	Count	Duration	Avg duration
	15	3,124	277ms	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: 2026-02-05 15:02:15 Duration: 5ms Database: postgres parameters: $1 = '2026-02-05 15:30:00', $2 = '379.822', $3 = '380.159', $4 = '379.711', $5 = '379.856', $6 = '2777', $7 = '515840249384846300', $8 = '0', $9 = '2026-02-05 15:02:15.015', $10 = '2026-02-05 15:02:14.6', $11 = '379.822', $12 = '380.159', $13 = '379.711', $14 = '379.856', $15 = '2777', $16 = '0', $17 = '2026-02-05 15:02:15.015', $18 = '2026-02-05 15:02:14.6'
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: 2026-02-05 15:31:08 Duration: 1ms Database: postgres parameters: $1 = '2026-02-05 15:00:00', $2 = '53857.5', $3 = '54037.5', $4 = '53847.5', $5 = '53937.5', $6 = '1019', $7 = '515840230555870300', $8 = '0', $9 = '2026-02-05 15:31:08.555', $10 = '2026-02-05 15:31:08.554', $11 = '53857.5', $12 = '54037.5', $13 = '53847.5', $14 = '53937.5', $15 = '1019', $16 = '0', $17 = '2026-02-05 15:31:08.555', $18 = '2026-02-05 15:31:08.554'
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: 2026-02-05 15:30:52 Duration: 0ms Database: postgres parameters: $1 = '2026-02-05 15:00:00', $2 = '0.9535', $3 = '0.95421', $4 = '0.95322', $5 = '0.95333', $6 = '11144', $7 = '515840243909396300', $8 = '0', $9 = '2026-02-05 15:30:52.394', $10 = '2026-02-05 15:30:52.393', $11 = '0.9535', $12 = '0.95421', $13 = '0.95322', $14 = '0.95333', $15 = '11144', $16 = '0', $17 = '2026-02-05 15:30:52.394', $18 = '2026-02-05 15:30:52.393'

12

187ms

2,053

Details

0ms

1ms

0ms

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

Times Reported Time consuming bind #12

Day	Hour	Count	Duration	Avg duration
	15	2,053	187ms	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: 2026-02-05 15:07:30 Duration: 1ms Database: postgres parameters: $1 = '2026-02-05 14:00:00', $2 = '31.7175', $3 = '31.7935', $4 = '31.71', $5 = '31.7475', $6 = '1677', $7 = '605679104110175300', $8 = '0', $9 = '2026-02-05 15:07:30.576', $10 = '2026-02-05 15:07:30.576', $11 = '31.7175', $12 = '31.7935', $13 = '31.71', $14 = '31.7475', $15 = '1677', $16 = '0', $17 = '2026-02-05 15:07:30.576', $18 = '2026-02-05 15:07:30.576'
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: 2026-02-05 15:01:39 Duration: 0ms Database: postgres parameters: $1 = '2026-02-04 21:00:00', $2 = '417.42', $3 = '418.63', $4 = '415.08', $5 = '415.11', $6 = '8394', $7 = '515840247896450300', $8 = '0', $9 = '2026-02-05 15:01:39.202', $10 = '2026-02-05 15:01:39.123', $11 = '417.42', $12 = '418.63', $13 = '415.08', $14 = '415.11', $15 = '8394', $16 = '0', $17 = '2026-02-05 15:01:39.202', $18 = '2026-02-05 15:01:39.123'
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: 2026-02-05 15:01:40 Duration: 0ms Database: postgres parameters: $1 = '2026-02-05 14:00:00', $2 = '1.94895', $3 = '1.95018', $4 = '1.94151', $5 = '1.94859', $6 = '16824', $7 = '515840230478137300', $8 = '0', $9 = '2026-02-05 15:01:40.186', $10 = '2026-02-05 15:01:40.186', $11 = '1.94895', $12 = '1.95018', $13 = '1.94151', $14 = '1.94859', $15 = '16824', $16 = '0', $17 = '2026-02-05 15:01:40.186', $18 = '2026-02-05 15:01:40.186'

13

156ms

28,473

Details

0ms

2ms

0ms

SET extra_float_digits = 3;

Times Reported Time consuming bind #13

Day	Hour	Count	Duration	Avg duration
	15	28,473	156ms	0ms

SET extra_float_digits = 3;

Date: 2026-02-05 15:27:54 Duration: 2ms Database: postgres
SET extra_float_digits = 3;

Date: 2026-02-05 15:11:14 Duration: 2ms Database: postgres
SET extra_float_digits = 3;

Date: 2026-02-05 15:13:02 Duration: 2ms Database: postgres

14

143ms

28,446

Details

0ms

4ms

0ms

SET application_name = 'PostgreSQL JDBC Driver';

Times Reported Time consuming bind #14

Day	Hour	Count	Duration	Avg duration
	15	28,446	143ms	0ms

SET application_name = 'PostgreSQL JDBC Driver';

Date: 2026-02-05 15:16:52 Duration: 4ms Database: postgres
SET application_name = 'PostgreSQL JDBC Driver';

Date: 2026-02-05 15:33:26 Duration: 2ms Database: postgres
SET application_name = 'PostgreSQL JDBC Driver';

Date: 2026-02-05 15:20:36 Duration: 2ms Database: postgres

15

98ms

93

Details

0ms

2ms

1ms

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

Times Reported Time consuming bind #15

Day	Hour	Count	Duration	Avg duration
	15	93	98ms	1ms

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

Date: 2026-02-05 15:54:35 Duration: 2ms Database: postgres parameters: $1 = '689', $2 = 'XAUUSD', $3 = '689'
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2026-02-05 15:16:07 Duration: 1ms Database: postgres parameters: $1 = '538', $2 = 'GBPUSD', $3 = '538'
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2026-02-05 15:10:54 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'USDCHF', $3 = '558'

16

98ms

252

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
	15	252	98ms	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: 2026-02-05 15:14:27 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: 2026-02-05 15:14:27 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: 2026-02-05 15:14:28 Duration: 0ms Database: postgres

17

90ms

17

Details

3ms

7ms

5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #17

Day	Hour	Count	Duration	Avg duration
	15	17	90ms	5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-05 15:54:28 Duration: 7ms Database: postgres parameters: $1 = '489', $2 = '489'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-05 15:11:16 Duration: 7ms Database: postgres parameters: $1 = '958', $2 = '958'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-05 15:47:20 Duration: 7ms Database: postgres parameters: $1 = '538', $2 = '538'

18

64ms

513

Details

0ms

1ms

0ms

select category, ;

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	15	513	64ms	0ms

select category, ;

Date: 2026-02-05 15:32:47 Duration: 1ms Database: postgres parameters: $1 = '605634061978417307', $2 = 'significant'
select category, ;

Date: 2026-02-05 15:32:42 Duration: 0ms Database: postgres parameters: $1 = '605634061978417307', $2 = 'symbol', $3 = 'USDJPY', $4 = 'AUDJPY', $5 = 'EURMXN', $6 = 'GBPJPY', $7 = 'EURJPY', $8 = 'USDMXN', $9 = 'GBPUSD', $10 = 'EURAUD', $11 = 'EURUSD', $12 = 'USDCAD', $13 = 'AUDCAD', $14 = 'AUDUSD', $15 = 'NZDUSD', $16 = 'USDCHF', $17 = 'EURCHF', $18 = 'USDCAD', $19 = 'EURGBP', $20 = 'EURGBP', $21 = 'USDMXN', $22 = 'GBPUSD', $23 = 'GBPJPY', $24 = 'NZDUSD', $25 = 'EURJPY', $26 = 'EURCHF', $27 = 'AUDCAD', $28 = 'EURAUD', $29 = 'USDCHF', $30 = 'EURMXN', $31 = 'AUDJPY', $32 = 'USDJPY', $33 = 'AUDUSD', $34 = 'EURUSD', $35 = '605634061978417307', $36 = 'symbol', $37 = 'USDJPY', $38 = 'AUDJPY', $39 = 'EURMXN', $40 = 'GBPJPY', $41 = 'EURJPY', $42 = 'USDMXN', $43 = 'GBPUSD', $44 = 'EURAUD', $45 = 'EURUSD', $46 = 'USDCAD', $47 = 'AUDCAD', $48 = 'AUDUSD', $49 = 'NZDUSD', $50 = 'USDCHF', $51 = 'EURCHF', $52 = 'USDCAD', $53 = 'EURGBP', $54 = 'EURGBP', $55 = 'USDMXN', $56 = 'GBPUSD', $57 = 'GBPJPY', $58 = 'NZDUSD', $59 = 'EURJPY', $60 = 'EURCHF', $61 = 'AUDCAD', $62 = 'EURAUD', $63 = 'USDCHF', $64 = 'EURMXN', $65 = 'AUDJPY', $66 = 'USDJPY', $67 = 'AUDUSD', $68 = 'EURUSD'
select category, ;

Date: 2026-02-05 15:32:30 Duration: 0ms Database: postgres parameters: $1 = '605633814906094307', $2 = 'symbol', $3 = 'INTC.US', $4 = 'BABA.US', $5 = 'PYPL.US', $6 = 'TSLA.US', $7 = 'AMD.US', $8 = 'V.US', $9 = 'NVDA.US', $10 = 'AMZN.US', $11 = 'META.US', $12 = 'BRK.B.US', $13 = 'MSFT.US', $14 = 'NFLX.US', $15 = 'NKE.US', $16 = 'AAPL.US', $17 = 'GOOG.US', $18 = 'NVDA.US', $19 = 'BRK.B.US', $20 = 'INTC.US', $21 = 'NKE.US', $22 = 'BABA.US', $23 = 'PYPL.US', $24 = 'AMD.US', $25 = 'NFLX.US', $26 = 'V.US', $27 = 'GOOG.US', $28 = 'AMZN.US', $29 = 'TSLA.US', $30 = 'AAPL.US', $31 = 'META.US', $32 = 'MSFT.US', $33 = '605633814906094307', $34 = 'symbol', $35 = 'INTC.US', $36 = 'BABA.US', $37 = 'PYPL.US', $38 = 'TSLA.US', $39 = 'AMD.US', $40 = 'V.US', $41 = 'NVDA.US', $42 = 'AMZN.US', $43 = 'META.US', $44 = 'BRK.B.US', $45 = 'MSFT.US', $46 = 'NFLX.US', $47 = 'NKE.US', $48 = 'AAPL.US', $49 = 'GOOG.US', $50 = 'NVDA.US', $51 = 'BRK.B.US', $52 = 'INTC.US', $53 = 'NKE.US', $54 = 'BABA.US', $55 = 'PYPL.US', $56 = 'AMD.US', $57 = 'NFLX.US', $58 = 'V.US', $59 = 'GOOG.US', $60 = 'AMZN.US', $61 = 'TSLA.US', $62 = 'AAPL.US', $63 = 'META.US', $64 = 'MSFT.US'

19

63ms

418

Details

0ms

4ms

0ms

/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz 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 where resultuid = $1;

Times Reported Time consuming bind #19

Day	Hour	Count	Duration	Avg duration
	15	418	63ms	0ms

/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz 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 where resultuid = $1;

Date: 2026-02-05 15:20:59 Duration: 4ms Database: postgres parameters: $1 = '607626937632632301'
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz 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 where resultuid = $1;

Date: 2026-02-05 15:06:17 Duration: 3ms Database: postgres parameters: $1 = '607626641228994301'
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz 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 where resultuid = $1;

Date: 2026-02-05 15:48:03 Duration: 3ms Database: postgres parameters: $1 = '607626995355458301'

20

63ms

23

Details

1ms

8ms

2ms

WITH rcr_max as ( ;

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	15	23	63ms	2ms

WITH rcr_max as ( ;

Date: 2026-02-05 15:02:03 Duration: 8ms Database: postgres parameters: $1 = '607623456983063305', $2 = '607623456983063305', $3 = '607623456983063305'
WITH rcr_max as ( ;

Date: 2026-02-05 15:32:11 Duration: 6ms Database: postgres parameters: $1 = '607623456983063305', $2 = '607623456983063305', $3 = '607623456983063305'
WITH rcr_max as ( ;

Date: 2026-02-05 15:17:08 Duration: 5ms Database: postgres parameters: $1 = '607623401340911305', $2 = '607623401340911305', $3 = '607623401340911305'

Log levels

Key values

1,698,474 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	637	0.04%
DETAIL	314,500	18.52%
ERROR	1	0.00%
LOG	1,382,552	81.40%
STATEMENT	784	0.05%

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

Times Reported Most Frequent Error / Event #1

Day	Hour	Count
Feb 05	15	1

ERROR: duplicate key value violates unique constraint "uk_processparams_processid_key"

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