pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Mon Mar 30 07:59:47 2026
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-03-30_090000.log
Parsed 1,734,934 log entries in 45s
Log start from 2026-03-30 09:00:00 to 2026-03-30 09:59:45

Global Stats

259 Number of unique normalized queries
206,219 Number of queries
1h42m17s Total query duration
2026-03-30 09:00:00 First query
2026-03-30 09:59:45 Last query
4,595 queries/s at 2026-03-30 09:11:23 Query peak

1h42m17s Total query duration
8s35ms Prepare/parse total duration
42s355ms Bind total duration
1h41m26s Execute total duration

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

40 Total number of automatic vacuums
56 Total number of automatic analyzes

1,956 Number temporary file
626.62 MiB Max size of temporary file
65.30 MiB Average size of temporary file

2,829 Total number of sessions
13 sessions at 2026-03-30 09:51:21 Session peak
45d22h41m42s Total duration of sessions
23m23s Average duration of sessions
72 Average queries per session
2s169ms Average queries duration per session
23m21s Average idle time per session

2,813 Total number of connections
27 connections/s at 2026-03-30 09:03:48 Connection peak
3 Total number of databases

SQL Traffic

Key values

4,595 queries/s Query Peak
2026-03-30 09:11:23 Date

SELECT Traffic

Key values

2,298 queries/s Query Peak
2026-03-30 09:11:23 Date

INSERT/UPDATE/DELETE Traffic

Key values

176 queries/s Query Peak
2026-03-30 09:00:54 Date

Queries duration

Key values

1h42m17s 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)
Mar 30	09	206,219	0ms	42s909ms	29ms	3m39s	4m13s	4m22s

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Mar 30	09	68,131	26	0ms	0ms	0ms	0ms

Day	Hour	INSERT	UPDATE	DELETE	COPY FROM	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Mar 30	09	24,062	2,451	16	96	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Mar 30	09	19,393	75,900	3.91	19.59%

Day	Hour	Count	Average / Second
Mar 30	09	2,813	0.78/s

Day	Hour	Count	Average Duration	Average idle time
Mar 30	09	2,829	23m23s	23m21s

↑ Back to the top of the General Activity table

Established Connections

Key values

27 connections Connection Peak
2026-03-30 09:03:48 Date

Connections per database

Key values

acaweb_fx Main Database
2,813 connections Total

Chart
Table

Database	User	Count
acaweb_fx		2,745
	postgres	2,388
	psql	357
socialmedia		68
	postgres	68

Connections per user

Key values

postgres Main User
2,813 connections Total

Chart
Table

User	Count
postgres	2,456
psql	357

Connections per host

Key values

192.168.4.142 Main host with 1195 connections
2,813 Total connections

Chart
Table

Host	Count
127.0.0.1	113
182.165.1.54	2
192.168.0.114	3
192.168.0.216	102
192.168.0.74	171
192.168.0.84	2
192.168.1.131	2
192.168.1.145	74
192.168.1.15	201
192.168.1.20	90
192.168.1.238	2
192.168.1.239	12
192.168.1.90	64
192.168.2.126	48
192.168.2.182	12
192.168.3.199	36
192.168.4.108	1
192.168.4.129	6
192.168.4.142	1,195
192.168.4.150	10
192.168.4.204	11
192.168.4.222	1
192.168.4.238	7
192.168.4.33	67
192.168.4.52	7
192.168.4.98	330
[local]	244

Simultaneous sessions

Key values

13 sessions Session Peak
2026-03-30 09:51:21 Date

Histogram of session times

Key values

2,322 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	2,322	82.08%
500ms-1s	119	4.21%
1s-30s	231	8.17%
30s-1m	9	0.32%
1m-10m	45	1.59%
10m-30m	56	1.98%
30m-1h	6	0.21%
1h-8h	13	0.46%
> 8h	28	0.99%

Sessions per database

Key values

acaweb_fx Main Database
2,829 sessions Total

Chart
Table

Database	User	Count	Total Duration	Average Duration
acaweb_fx	2,762	45d22h40m42s	23m57s
socialmedia	67	1m	900ms

Sessions per user

Key values

postgres Main User
2,829 sessions Total

Chart
Table

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

Sessions per host

Key values

192.168.4.142 Main Host
2,829 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
127.0.0.1	113	13s447ms	119ms
182.165.1.54	2	23h24m29s	11h42m14s
192.168.0.114	2	10m12s	5m6s
192.168.0.171	8	16d9h44m55s	2d1h13m6s
192.168.0.216	102	1m3s	621ms
192.168.0.74	172	2d22h1m38s	24m25s
192.168.0.84	2	23h59m29s	11h59m44s
192.168.1.131	2	23h59m27s	11h59m43s
192.168.1.145	74	2d9h35m21s	46m41s
192.168.1.15	201	1d16h38m7s	12m7s
192.168.1.154	8	15d3h18m57s	1d21h24m52s
192.168.1.20	90	2d13h30m12s	41m
192.168.1.238	2	23h59m25s	11h59m42s
192.168.1.239	12	75ms	6ms
192.168.1.90	64	39s892ms	623ms
192.168.2.126	48	22s481ms	468ms
192.168.2.182	12	1s12ms	84ms
192.168.3.199	36	1s338ms	37ms
192.168.4.108	1	168ms	168ms
192.168.4.129	6	84ms	14ms
192.168.4.142	1,195	8m8s	408ms
192.168.4.150	10	20h36s	2h3s
192.168.4.204	11	174ms	15ms
192.168.4.222	1	59s702ms	59s702ms
192.168.4.238	7	46s232ms	6s604ms
192.168.4.33	67	1m	900ms
192.168.4.52	7	56s754ms	8s107ms
192.168.4.98	330	13s902ms	42ms
[local]	244	4m21s	1s71ms

Sessions per application

Key values

unknown Main Host
2,829 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	2,829	45d22h41m42s	23m23s

Checkpoints Buffers

Key values

11,505 buffers Checkpoint Peak
2026-03-30 09:06:39 Date
209.763 seconds Highest write time
2.146 seconds Sync time

Checkpoints Wal files

Key values

5 files Wal files usage Peak
2026-03-30 09:06:39 Date

Checkpoints distance

Key values

161.21 Mo Distance Peak
2026-03-30 09:06:39 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Mar 30	09	39,692	1,707.516s	3.25s	1,715.23s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Mar 30	09	0	0	22	1,768	2.146s	0.05s

Day	Hour	Count	Avg time (sec)
Mar 30	09	0	0s

Day	Hour	Mean distance	Mean estimate
Mar 30	09	30,696.17 kB	67,486.00 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

580.60 MiB Temp Files size Peak
2026-03-30 09:50:29 Date

Number of temporary files

Key values

30 per second Temp Files Peak
2026-03-30 09:32:10 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Mar 30	09	1,956	124.74 GiB	65.30 MiB

↑ Back to the top of the Temporary Files Activity table

Queries generating the most temporary files (N)

Rank	Count	Total size	Min size	Max size	Avg size	Query
1	239	118.20 GiB	298.56 MiB	580.60 MiB	506.42 MiB	classname, case when latestdbwritetime < current_timestamp - interval ? then ? else ? end as is_stale from latest_t15_candle_view order by classname; classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; Date: 2026-03-30 09:00:15 Duration: 0ms
2	208	336.08 MiB	137.65 KiB	3.80 MiB	1.62 MiB	with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ), ar as ( select a., rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end ), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, 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, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.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 sg.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 currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= 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 ; WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a., rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, 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, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.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 sg.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 OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4)) AND ($5 = 0 OR s.exchange in ($6)) AND ($7 = 0 OR coalesce(bim.code, s.symbol) in ($8)) AND ($9 = 0 OR ar.pattern in ($10)) AND ($11 = 0 OR ($12 = 1 AND ar.breakout >= 0) OR ($13 = 2 AND ar.breakout < 0)) AND ($14 = 0 OR ar.patternlengthbars <= $15) and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) FROM all_results WHERE (FALSE = $16 OR relevant = 1) AND ($17 = 0 OR age <= $18) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-03-30 09:00:24 Duration: 0ms
3	45	212.16 MiB	4.70 MiB	4.74 MiB	4.71 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)) AND ($5 = 0 OR s.exchange in ($6)) AND ($7 = 0 OR coalesce(bim.code, s.symbol) in ($8)) AND ($9 = 0 OR fr.pattern in ($10)) AND ($11 = 0 OR fr.patternlengthbars <= $12) AND ($13 = 0 OR ($14 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($15 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) FROM all_results WHERE (FALSE = $16 OR relevant = 1) AND ($17 = 0 OR age <= $18) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-03-30 09:00:38 Duration: 0ms
4	29	1.66 GiB	10.31 MiB	163.68 MiB	58.60 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: 2026-03-30 09:00:08 Duration: 0ms
5	26	104.03 MiB	3.07 MiB	9.11 MiB	4.00 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: 2026-03-30 09:01:26 Duration: 0ms
6	24	42.29 MiB	137.65 KiB	4.25 MiB	1.76 MiB	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 ? ; WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = $1 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4)) AND ($5 = 0 OR s.exchange in ($6)) AND ($7 = 0 OR coalesce(bim.code, s.symbol) in ($8)) AND ($9 = 0 OR p.patternname in ($10)) AND ($11 = 0 OR kr.patternclassid in ($12)) AND ($13 = 0 OR kr.patternlengthbars <= $14) AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) FROM all_results WHERE (FALSE = $15 OR relevant = 1) AND ($16 = 0 OR age <= $17) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200; Date: 2026-03-30 09:00:55 Duration: 0ms
7	16	740.12 MiB	46.26 MiB	46.26 MiB	46.26 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: 2026-03-30 09:01:13 Duration: 0ms
8	16	1.23 GiB	78.57 MiB	78.57 MiB	78.57 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: 2026-03-30 09:01:17 Duration: 0ms
9	9	28.52 MiB	3.16 MiB	3.17 MiB	3.17 MiB	select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ?), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?)), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc; SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ($2 = 0 OR s.timegranularity in ($3, $4, $5, $6, $7, $8, $9)) AND ($10 = 0 OR s.exchange in ($11)) AND ($12 = 0 OR coalesce(bim.code, s.symbol) in ($13, $14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226, $227, $228, $229, $230, $231, $232, $233, $234, $235, $236, $237, $238, $239, $240, $241, $242, $243, $244, $245, $246, $247, $248, $249, $250, $251, $252, $253, $254, $255, $256, $257, $258, $259, $260, $261, $262, $263, $264, $265, $266, $267, $268, $269, $270, $271, $272, $273, $274, $275, $276, $277, $278, $279, $280, $281, $282, $283, $284, $285, $286, $287, $288, $289, $290, $291, $292, $293, $294, $295, $296, $297, $298, $299, $300, $301, $302, $303, $304, $305, $306, $307, $308, $309, $310, $311, $312, $313, $314, $315, $316, $317, $318, $319, $320, $321, $322)) AND ($323 = 0 OR ccr.patternlengthbars <= $324)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $325 OR relevant = 1) AND ($326 = 0 OR age <= $327) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-03-30 09:19:28 Duration: 0ms
10	8	1.16 GiB	148.99 MiB	149.08 MiB	149.04 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2026-03-30 09:02:16 Duration: 0ms
11	4	315.70 MiB	78.87 MiB	78.96 MiB	78.93 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2026-03-30 09:02:05 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	580.60 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:48:44 ]
2	580.60 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:50:29 ]
3	574.62 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:11:59 ]
4	574.62 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:44:14 ]
5	574.62 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:49:13 ]
6	574.62 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:53:28 ]
7	574.62 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:57:45 ]
8	574.62 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:58:01 ]
9	574.62 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:59:14 ]
10	571.62 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:08:59 ]
11	571.62 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:58:59 ]
12	568.62 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:23:59 ]
13	565.62 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:42:14 ]
14	556.67 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:50:44 ]
15	556.67 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:55:13 ]
16	553.70 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:16:44 ]
17	553.70 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:52:59 ]
18	553.59 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:08:44 ]
19	550.71 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:13:29 ]
20	550.71 MiB	classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname; [ Date: 2026-03-30 09:28:14 ]

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	8
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	2
acaweb_fx.public.latest_t15_candle_view	2
acaweb_fx.pg_catalog.pg_depend	2
acaweb_fx.pg_catalog.pg_index	1
acaweb_fx.public.autochartist_symbolupdates	1
acaweb_fx.public.latest_candle_datetime_per_receng	1
acaweb_fx.public.relevance_consecutivecandles_results	1
acaweb_fx.public.symbollatestupdatetime	1
acaweb_fx.public.correlating_signals	1
Total	56

Vacuums per table

Key values

public.solr_relevance_old (16) Main table vacuumed on database acaweb_fx
40 vacuums Total

Chart
Table

		Index	Buffer usage			Skipped		WAL usage
Table	Vacuums	scans	hits	misses	dirtied	pins	frozen	records	full page	bytes
acaweb_fx.public.solr_relevance_old	16	16	11,078	0	51	0	0	7,628	16	1,363,871
acaweb_fx.pg_catalog.pg_attribute	4	4	3,440	0	531	0	268	1,442	470	2,705,827
acaweb_fx.pg_toast.pg_toast_2619	2	2	262	0	51	0	0	204	49	197,283
acaweb_fx.pg_catalog.pg_type	2	2	312	0	55	0	0	148	34	198,096
acaweb_fx.public.datafeeds_latestrun	2	0	240	0	5	0	0	26	6	27,882
acaweb_fx.public.relevance_keylevels_results	2	2	7,773	0	219	0	215	1,786	167	525,989
acaweb_fx.pg_catalog.pg_class	2	2	921	0	97	0	0	306	97	528,268
acaweb_fx.public.relevance_autochartist_results	2	2	6,536	0	338	3	489	1,242	592	1,472,185
acaweb_fx.public.relevance_fibonacci_results	2	2	2,318	0	41	0	113	327	16	64,857
acaweb_fx.public.autochartist_symbolupdates	1	1	22,658	0	1,545	4	37,968	5,749	1,508	848,455
acaweb_fx.pg_catalog.pg_statistic	1	1	954	0	220	0	582	491	190	730,495
acaweb_fx.public.solr_imports	1	1	65	0	2	0	0	6	1	8,927
acaweb_fx.public.relevance_consecutivecandles_results	1	1	76	0	7	0	0	19	4	26,689
acaweb_fx.pg_catalog.pg_depend	1	1	411	0	86	0	59	200	67	353,831
acaweb_fx.public.latest_t15_candle_view	1	1	66	0	1	0	0	6	1	9,025
Total	40	38	57,110	48,224	3,249	7	39,694	19,580	3,218	9,061,680

Tuples removed per table

Key values

public.solr_relevance_old (41460) Main table with removed tuples on database acaweb_fx
60029 tuples Total removed

Chart
Table

		Index	Tuples			Pages
Table	Vacuums	scans	removed	remain	not yet removable	removed	remain
acaweb_fx.public.solr_relevance_old	16	16	41,460	76,064	0	0	2,661
acaweb_fx.pg_catalog.pg_attribute	4	4	6,841	42,893	0	25	1,050
acaweb_fx.public.autochartist_symbolupdates	1	1	5,474	45,189	649	0	40,691
acaweb_fx.public.relevance_keylevels_results	2	2	2,017	22,967	0	0	558
acaweb_fx.pg_catalog.pg_depend	1	1	993	14,393	0	0	144
acaweb_fx.public.relevance_autochartist_results	2	2	893	15,244	0	0	760
acaweb_fx.pg_catalog.pg_type	2	2	708	2,910	0	0	88
acaweb_fx.pg_catalog.pg_statistic	1	1	593	3,737	0	0	1,194
acaweb_fx.public.relevance_fibonacci_results	2	2	324	2,235	0	0	204
acaweb_fx.pg_catalog.pg_class	2	2	261	3,312	0	0	300
acaweb_fx.pg_toast.pg_toast_2619	2	2	158	343	8	0	104
acaweb_fx.public.datafeeds_latestrun	2	0	126	28	0	0	32
acaweb_fx.public.relevance_consecutivecandles_results	1	1	76	317	0	0	7
acaweb_fx.public.latest_t15_candle_view	1	1	54	12	0	0	1
acaweb_fx.public.solr_imports	1	1	51	1	0	0	2
Total	40	38	60,029	229,645	657	25	47,796

Pages removed per table

Key values

pg_catalog.pg_attribute (25) Main table with removed pages on database acaweb_fx
25 pages Total removed

Chart
Table

Table	Number of vacuums	Index scans	Tuples removed	Pages removed
acaweb_fx.pg_catalog.pg_attribute	4	4	6841	25
acaweb_fx.pg_toast.pg_toast_2619	2	2	158	0
acaweb_fx.pg_catalog.pg_type	2	2	708	0
acaweb_fx.public.autochartist_symbolupdates	1	1	5474	0
acaweb_fx.public.datafeeds_latestrun	2	0	126	0
acaweb_fx.pg_catalog.pg_statistic	1	1	593	0
acaweb_fx.public.solr_imports	1	1	51	0
acaweb_fx.public.relevance_consecutivecandles_results	1	1	76	0
acaweb_fx.pg_catalog.pg_depend	1	1	993	0
acaweb_fx.public.latest_t15_candle_view	1	1	54	0
acaweb_fx.public.relevance_keylevels_results	2	2	2017	0
acaweb_fx.public.solr_relevance_old	16	16	41460	0
acaweb_fx.pg_catalog.pg_class	2	2	261	0
acaweb_fx.public.relevance_autochartist_results	2	2	893	0
acaweb_fx.public.relevance_fibonacci_results	2	2	324	0
Total	40	38	60,029	25

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Mar 30	09	40	56

↑ 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

68,131 Total read queries
30,839 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	68,131	33.04%
INSERT	24,062	11.67%
UPDATE	2,451	1.19%
DELETE	16	0.01%
COPY FROM	96	0.05%
COPY TO	26	0.01%
CTE	3,476	1.69%
DDL	16	0.01%
TCL	696	0.34%
CURSOR	0	0.00%
OTHERS	107,249	52.01%

Queries by database

Key values

unknown Main database
205,300 Requests
1h41m26s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	851	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	166	0ms
	select	72	0ms
	tcl	332	0ms
	update	39	0ms
socialmedia	Total	68	0ms
	select	67	0ms
	tcl	1	0ms
unknown	Total	205,300	1h41m26s
	copy from	16	0ms
	cte	3,372	0ms
	insert	24,062	0ms
	others	4,093	0ms
	select	67,992	0ms
	tcl	363	0ms
	update	2,412	0ms

Queries by user

Key values

unknown Main user
205,300 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	919	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	166	0ms
	select	139	0ms
	tcl	333	0ms
	update	39	0ms
unknown	Total	205,300	1h41m26s
	copy from	16	0ms
	cte	3,372	0ms
	insert	24,062	0ms
	others	4,093	0ms
	select	67,992	0ms
	tcl	363	0ms
	update	2,412	0ms

Duration by user

Key values

1h41m26s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	919	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	166	0ms
	select	139	0ms
	tcl	333	0ms
	update	39	0ms
unknown	Total	205,300	1h41m26s
	copy from	16	0ms
	cte	3,372	0ms
	insert	24,062	0ms
	others	4,093	0ms
	select	67,992	0ms
	tcl	363	0ms
	update	2,412	0ms

Queries by host

Key values

unknown Main host
206,219 Requests
1h41m26s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	206,219	1h41m26s
	copy from	96	0ms
	copy to	26	0ms
	cte	3,476	0ms
	ddl	16	0ms
	delete	16	0ms
	insert	24,062	0ms
	others	4,259	0ms
	select	68,131	0ms
	tcl	696	0ms
	update	2,451	0ms

Queries by application

Key values

unknown Main application
205,862 Requests
1h41m26s (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	205,862	1h41m26s
	copy from	16	0ms
	cte	3,372	0ms
	insert	24,062	0ms
	others	4,255	0ms
	select	68,059	0ms
	tcl	696	0ms
	update	2,412	0ms

Number of cancelled queries

Key values

1 per second Cancelled query Peak
2026-03-30 09:46:00 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

68,630 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	68,630	66.64%
1-5ms	24,163	23.46%
5-10ms	2,441	2.37%
10-25ms	1,135	1.10%
25-50ms	2,819	2.74%
50-100ms	1,332	1.29%
100-500ms	993	0.96%
500-1000ms	671	0.65%
1000-10000ms	659	0.64%
> 10000ms	147	0.14%

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

7

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
Mar 30	09	7	0ms	0ms

2

0ms

6

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 #2

Day	Hour	Count	Duration	Avg duration
Mar 30	09	6	0ms	0ms

3

0ms

2,135

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
Mar 30	09	2,135	0ms	0ms

4

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 #4

Day	Hour	Count	Duration	Avg duration
Mar 30	09	4	0ms	0ms

5

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Mar 30	09	4	0ms	0ms

6

0ms

239

Details

0ms

select * from ( select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity) as k order by timegranularity;

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Mar 30	09	239	0ms	0ms

7

0ms

18

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Mar 30	09	18	0ms	0ms

8

0ms

348

Details

0ms

commit;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Mar 30	09	348	0ms	0ms

9

0ms

199

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Mar 30	09	199	0ms	0ms

10

0ms

239

Details

0ms

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

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Mar 30	09	239	0ms	0ms

11

0ms

239

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Mar 30	09	239	0ms	0ms

12

0ms

4

Details

0ms

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

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Mar 30	09	4	0ms	0ms

13

0ms

200

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 #13

Day	Hour	Count	Duration	Avg duration
Mar 30	09	200	0ms	0ms

14

0ms

35

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 #14

Day	Hour	Count	Duration	Avg duration
Mar 30	09	35	0ms	0ms

15

0ms

16

Details

0ms

with max_ra as ( select resultuid from relevance_fibonacci_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 left outer join relevance_fibonacci_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 fibonacci_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null);

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Mar 30	09	16	0ms	0ms

16

0ms

171

Details

0ms

set statement_timeout = ?;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Mar 30	09	171	0ms	0ms

17

0ms

59

Details

0ms

select id, schedule from processes where enabled = true and schedule is not null;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Mar 30	09	59	0ms	0ms

18

0ms

16

Details

0ms

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;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Mar 30	09	16	0ms	0ms

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: 2026-03-30 09:01:13 Duration: 0ms

19

0ms

565

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 #19

Day	Hour	Count	Duration	Avg duration
Mar 30	09	565	0ms	0ms

20

0ms

24

Details

0ms

with selec as ( select uuid from solr_relevance_old where age <> newage or relevant <> newrelevant or hod_correct <> new_hod_correct or hod_percent <> new_hod_percent or hod_total <> new_hod_total or pattern_correct <> new_pattern_correct or pattern_percent <> new_pattern_percent or pattern_total <> new_pattern_total or percent <> new_percent or symbol_correct <> new_symbol_correct or symbol_percent <> new_symbol_percent or symbol_total <> new_symbol_total limit ? ), upp as ( update solr_relevance_old set relevant = coalesce(newrelevant, relevant), age = coalesce(newage, age), hod_correct = coalesce(new_hod_correct, coalesce(hod_correct, ?)), hod_percent = coalesce(new_hod_percent, coalesce(hod_percent, ?)), hod_total = coalesce(new_hod_total, coalesce(hod_total, ?)), pattern_correct = coalesce(new_pattern_correct, coalesce(pattern_correct, ?)), pattern_percent = coalesce(new_pattern_percent, coalesce(pattern_percent, ?)), pattern_total = coalesce(new_pattern_total, coalesce(pattern_total, ?)), percent = coalesce(new_percent, coalesce(percent, ?)), symbol_correct = coalesce(new_symbol_correct, coalesce(symbol_correct, ?)), symbol_percent = coalesce(new_symbol_percent, coalesce(symbol_percent, ?)), symbol_total = coalesce(new_symbol_total, coalesce(symbol_total, ?)) where uuid in ( select uuid from selec) returning * ) select ? || upp.uuid || ? || upp.age || ? || upp.relevant || ? || upp.hod_correct || ? || upp.hod_percent || ? || upp.hod_total || ? || upp.pattern_correct || ? || upp.pattern_percent || ? || upp.pattern_total || ? || upp.percent || ? || upp.symbol_correct || ? || upp.symbol_percent || ? || upp.symbol_total || ? from upp;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Mar 30	09	24	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

25,460

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Mar 30	09	25,460	0ms	0ms

2

7,924

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
Mar 30	09	7,924	0ms	0ms

3

6,499

Details

0ms

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

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Mar 30	09	6,499	0ms	0ms

4

5,740

Details

0ms

insert into autochartist_results (resultid, symbolid, bandwidth, pattern, qtytp, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, relevancestartdistance, simulation, writtendatetime) values (?, ?, ?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Mar 30	09	5,740	0ms	0ms

5

5,656

Details

0ms

insert into t15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Mar 30	09	5,656	0ms	0ms

6

4,642

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Mar 30	09	4,642	0ms	0ms

7

3,332

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Mar 30	09	3,332	0ms	0ms

8

2,909

Details

0ms

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

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Mar 30	09	2,909	0ms	0ms

9

2,528

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Mar 30	09	2,528	0ms	0ms

10

2,435

Details

0ms

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

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Mar 30	09	2,435	0ms	0ms

11

2,135

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 #11

Day	Hour	Count	Duration	Avg duration
Mar 30	09	2,135	0ms	0ms

12

1,982

Details

0ms

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

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Mar 30	09	1,982	0ms	0ms

13

1,852

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Mar 30	09	1,852	0ms	0ms

14

1,817

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Mar 30	09	1,817	0ms	0ms

15

1,541

Details

0ms

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

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Mar 30	09	1,541	0ms	0ms

16

1,332

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 #16

Day	Hour	Count	Duration	Avg duration
Mar 30	09	1,332	0ms	0ms

17

1,043

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 #17

Day	Hour	Count	Duration	Avg duration
Mar 30	09	1,043	0ms	0ms

18

749

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 #18

Day	Hour	Count	Duration	Avg duration
Mar 30	09	749	0ms	0ms

19

600

Details

0ms

select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, a.patternprice, atbaridentified as patternendtime, breakout, p.patternname, dtt.timezone, a.direction, case when a.patternclassid = ? then a.predictionpricefrom else a.patternprice end as predictionpricefrom, case when a.patternclassid = ? then a.predictionpriceto else a.patternprice end as predictionpriceto, s.timegranularity as interval, patternlengthbars as length, 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 left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Mar 30	09	600	0ms	0ms

20

565

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 #20

Day	Hour	Count	Duration	Avg duration
Mar 30	09	565	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

7

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
Mar 30	09	7	0ms	0ms

2

0ms

6

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 #2

Day	Hour	Count	Duration	Avg duration
Mar 30	09	6	0ms	0ms

3

0ms

2,135

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
Mar 30	09	2,135	0ms	0ms

4

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 #4

Day	Hour	Count	Duration	Avg duration
Mar 30	09	4	0ms	0ms

5

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Mar 30	09	4	0ms	0ms

6

0ms

239

Details

0ms

select * from ( select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity) as k order by timegranularity;

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Mar 30	09	239	0ms	0ms

7

0ms

18

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Mar 30	09	18	0ms	0ms

8

0ms

348

Details

0ms

commit;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Mar 30	09	348	0ms	0ms

9

0ms

199

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Mar 30	09	199	0ms	0ms

10

0ms

239

Details

0ms

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

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Mar 30	09	239	0ms	0ms

11

0ms

239

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Mar 30	09	239	0ms	0ms

12

0ms

4

Details

0ms

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

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Mar 30	09	4	0ms	0ms

13

0ms

200

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 #13

Day	Hour	Count	Duration	Avg duration
Mar 30	09	200	0ms	0ms

14

0ms

35

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 #14

Day	Hour	Count	Duration	Avg duration
Mar 30	09	35	0ms	0ms

15

0ms

16

Details

0ms

with max_ra as ( select resultuid from relevance_fibonacci_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 left outer join relevance_fibonacci_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 fibonacci_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null);

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Mar 30	09	16	0ms	0ms

16

0ms

171

Details

0ms

set statement_timeout = ?;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Mar 30	09	171	0ms	0ms

17

0ms

59

Details

0ms

select id, schedule from processes where enabled = true and schedule is not null;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Mar 30	09	59	0ms	0ms

18

0ms

16

Details

0ms

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;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Mar 30	09	16	0ms	0ms

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: 2026-03-30 09:01:13 Duration: 0ms

19

0ms

565

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 #19

Day	Hour	Count	Duration	Avg duration
Mar 30	09	565	0ms	0ms

20

0ms

24

Details

0ms

with selec as ( select uuid from solr_relevance_old where age <> newage or relevant <> newrelevant or hod_correct <> new_hod_correct or hod_percent <> new_hod_percent or hod_total <> new_hod_total or pattern_correct <> new_pattern_correct or pattern_percent <> new_pattern_percent or pattern_total <> new_pattern_total or percent <> new_percent or symbol_correct <> new_symbol_correct or symbol_percent <> new_symbol_percent or symbol_total <> new_symbol_total limit ? ), upp as ( update solr_relevance_old set relevant = coalesce(newrelevant, relevant), age = coalesce(newage, age), hod_correct = coalesce(new_hod_correct, coalesce(hod_correct, ?)), hod_percent = coalesce(new_hod_percent, coalesce(hod_percent, ?)), hod_total = coalesce(new_hod_total, coalesce(hod_total, ?)), pattern_correct = coalesce(new_pattern_correct, coalesce(pattern_correct, ?)), pattern_percent = coalesce(new_pattern_percent, coalesce(pattern_percent, ?)), pattern_total = coalesce(new_pattern_total, coalesce(pattern_total, ?)), percent = coalesce(new_percent, coalesce(percent, ?)), symbol_correct = coalesce(new_symbol_correct, coalesce(symbol_correct, ?)), symbol_percent = coalesce(new_symbol_percent, coalesce(symbol_percent, ?)), symbol_total = coalesce(new_symbol_total, coalesce(symbol_total, ?)) where uuid in ( select uuid from selec) returning * ) select ? || upp.uuid || ? || upp.age || ? || upp.relevant || ? || upp.hod_correct || ? || upp.hod_percent || ? || upp.hod_total || ? || upp.pattern_correct || ? || upp.pattern_percent || ? || upp.pattern_total || ? || upp.percent || ? || upp.symbol_correct || ? || upp.symbol_percent || ? || upp.symbol_total || ? from upp;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Mar 30	09	24	0ms	0ms

Time consuming prepare


Date: 2026-03-30 09:10:11
Duration: 16ms
Database: postgres
Date: 2026-03-30 09:31:14
Duration: 7ms
Database: postgres
Date: 2026-03-30 09:09:26
Duration: 8ms
Database: postgres
Date: 2026-03-30 09:30:38
Duration: 3ms
Database: postgres
Date: 2026-03-30 09:45:56
Duration: 0ms
Database: postgres
Date: 2026-03-30 09:56:18
Duration: 9ms
Database: postgres
Date: 2026-03-30 09:46:52
Duration: 0ms
Database: postgres
Date: 2026-03-30 09:17:39
Duration: 0ms
Database: postgres
Date: 2026-03-30 09:11:23
Duration: 4ms
Database: postgres
Date: 2026-03-30 09:30:22
Duration: 16ms
Database: postgres
Date: 2026-03-30 09:01:31
Duration: 6ms
Database: postgres
Date: 2026-03-30 09:01:22
Duration: 4ms
Database: postgres
Date: 2026-03-30 09:30:37
Duration: 1ms
Database: postgres
Date: 2026-03-30 09:12:12
Duration: 7ms
Database: postgres
Date: 2026-03-30 09:14:59
Duration: 0ms
Database: postgres
Date: 2026-03-30 09:07:50
Duration: 4ms
Database: postgres
Date: 2026-03-30 09:37:55
Duration: 1ms
Database: postgres
Date: 2026-03-30 09:22:08
Duration: 8ms
Database: postgres
Date: 2026-03-30 09:11:17
Duration: 2ms
Database: postgres
Date: 2026-03-30 09:00:34
Duration: 4ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

23s331ms

2,381

Details

0ms

82ms

9ms

WITH rar_max as ( ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Mar 30	09	2,381	23s331ms	9ms

WITH rar_max as ( ;

Date: 2026-03-30 09:09:26 Duration: 82ms Database: postgres parameters: $1 = '607910055791515301', $2 = '607910055791515301', $3 = '607910055791515301'
WITH rar_max as ( ;

Date: 2026-03-30 09:30:42 Duration: 76ms Database: postgres parameters: $1 = '607925626812431301', $2 = '607925626812431301', $3 = '607925626812431301'
WITH rar_max as ( ;

Date: 2026-03-30 09:11:07 Duration: 68ms Database: postgres parameters: $1 = 't', $2 = '538', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '125', $14 = 'ANGLO', $15 = 'BARC', $16 = 'BAY', $17 = 'BPLON', $18 = 'HSBCL', $19 = 'LLOY', $20 = 'RIO', $21 = 'RollsRoyce', $22 = 'TESCO', $23 = 'VOD', $24 = 'AUDCAD', $25 = 'AUDCHF', $26 = 'AUDJPY', $27 = 'AUDNZD', $28 = 'AUDUSD', $29 = 'CADCHF', $30 = 'CADJPY', $31 = 'CHFJPY', $32 = 'EURAUD', $33 = 'EURCAD', $34 = 'EURCHF', $35 = 'EURDKK', $36 = 'EURGBP', $37 = 'EURHUF', $38 = 'EURJPY', $39 = 'EURNOK', $40 = 'EURNZD', $41 = 'EURPLN', $42 = 'EURUSD', $43 = 'GBPAUD', $44 = 'GBPCAD', $45 = 'GBPCHF', $46 = 'GBPJPY', $47 = 'GBPNZD', $48 = 'GBPUSD', $49 = 'GBPZAR', $50 = 'NZDCAD', $51 = 'NZDCHF', $52 = 'NZDJPY', $53 = 'NZDUSD', $54 = 'USDCAD', $55 = 'USDCHF', $56 = 'USDCNH', $57 = 'USDCZK', $58 = 'USDDKK', $59 = 'USDHKD', $60 = 'USDHUF', $61 = 'USDJPY', $62 = 'USDMXN', $63 = 'USDNOK', $64 = 'USDPLN', $65 = 'USDSEK', $66 = 'USDSGD', $67 = 'USDTRY', $68 = 'USDZAR', $69 = 'XAGEUR', $70 = 'XAGUSD', $71 = 'XAUEUR', $72 = 'XAUUSD', $73 = 'ZARJPY', $74 = 'Cocoa', $75 = 'Coffee', $76 = 'Copper', $77 = 'Palladium', $78 = 'Platinum', $79 = 'Sugar', $80 = 'UKOIL', $81 = 'USOIL', $82 = 'AUS200', $83 = 'FRA40', $84 = 'JPN225', $85 = 'NETH25', $86 = 'SPA35', $87 = 'SUI20', $88 = 'UK100', $89 = 'USA100', $90 = 'USA30', $91 = 'USDIndex', $92 = 'ALCOA', $93 = 'ALIBABA', $94 = 'AMAZON', $95 = 'AMEX', $96 = 'APPLE', $97 = 'BBVA', $98 = 'BOA', $99 = 'BOEING', $100 = 'CHEVRON', $101 = 'CISCO', $102 = 'COKE', $103 = 'EBAY', $104 = 'GE', $105 = 'GOOGLE', $106 = 'GS', $107 = 'HLT', $108 = 'IBM', $109 = 'ILMN', $110 = 'INTEL', $111 = 'Iberdrola', $112 = 'MCARD', $113 = 'MCDON', $114 = 'META', $115 = 'MSFT', $116 = 'Mapfre', $117 = 'Netflix', $118 = 'PFIZER', $119 = 'QCOM', $120 = 'Santander', $121 = 'TEVA', $122 = 'Telefonica', $123 = 'Tesla', $124 = 'AUDUSD', $125 = 'EURGBP', $126 = 'EURUSD', $127 = 'GBPUSD', $128 = 'NZDUSD', $129 = 'USDCAD', $130 = 'USDCHF', $131 = 'USDJPY', $132 = 'Adidas', $133 = 'Bayer', $134 = 'Daimler', $135 = 'Danone', $136 = 'LVMH', $137 = 'Lufthansa', $138 = 'Volksw', $139 = '0', $140 = '', $141 = '0', $142 = '0', $143 = '0', $144 = '700', $145 = '700', $146 = 't', $147 = '10', $148 = '10'

2

8s508ms

19,136

Details

0ms

23ms

0ms

SELECT ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	09	19,136	8s508ms	0ms

SELECT ;

Date: 2026-03-30 09:22:12 Duration: 23ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '515840233919005300'
SELECT ;

Date: 2026-03-30 09:07:50 Duration: 19ms Database: postgres parameters: $1 = '689', $2 = '689', $3 = '515840245886912300'
SELECT ;

Date: 2026-03-30 09:47:28 Duration: 18ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '515840243204359300'

3

3s179ms

1,175

Details

1ms

9ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	09	1,175	3s179ms	2ms

SELECT symbolid, ;

Date: 2026-03-30 09:02:01 Duration: 9ms Database: postgres parameters: $1 = 'ATFX', $2 = '15', $3 = '#DB1', $4 = '#DAI'
SELECT symbolid, ;

Date: 2026-03-30 09:32:23 Duration: 8ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'USDCAD.ID', $4 = 'USDCHF.ID', $5 = 'USDCHF', $6 = 'USDCHF.FX', $7 = 'USDCAD.FX'
SELECT symbolid, ;

Date: 2026-03-30 09:31:12 Duration: 8ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '15', $3 = 'NAS100'

4

1s442ms

232

Details

0ms

35ms

6ms

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

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	09	232	1s442ms	6ms

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

Date: 2026-03-30 09:11:18 Duration: 35ms Database: postgres parameters: $1 = '1504', $2 = '1504'
select distinct s.statsid as statsid, sy.exchange as name;

Date: 2026-03-30 09:00:48 Duration: 24ms Database: postgres parameters: $1 = '1436', $2 = '1436'
select distinct s.statsid as statsid, sy.exchange as name;

Date: 2026-03-30 09:11:17 Duration: 21ms Database: postgres parameters: $1 = '1436', $2 = '1436'

5

988ms

462

Details

1ms

15ms

2ms

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

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	09	462	988ms	2ms

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

Date: 2026-03-30 09:30:42 Duration: 15ms Database: postgres parameters: $1 = 'FPMARKETS'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-03-30 09:00:53 Duration: 4ms Database: postgres parameters: $1 = 'DXFEED_FX'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-03-30 09:30:22 Duration: 2ms Database: postgres parameters: $1 = 'MILLENNIUMPF'

6

699ms

8,013

Details

0ms

3ms

0ms

select category, ;

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	09	8,013	699ms	0ms

select category, ;

Date: 2026-03-30 09:11:23 Duration: 3ms Database: postgres parameters: $1 = '515852059296080307', $2 = 'symbol', $3 = 'AUDJPY', $4 = 'USDMXN', $5 = 'NZDJPY', $6 = 'EURMXN', $7 = 'USDNOK', $8 = 'USDJPY', $9 = 'NOKJPY', $10 = 'CADJPY', $11 = 'GBPJPY', $12 = 'CHFJPY', $13 = 'ZARJPY', $14 = 'USDZAR', $15 = 'EURNOK', $16 = 'HKDJPY', $17 = 'USDSEK', $18 = 'GBPZAR', $19 = 'USDDKK', $20 = 'EURJPY', $21 = 'EURTRY', $22 = 'EURSEK', $23 = 'USDPLN', $24 = 'GBPAUD', $25 = 'USDCNH', $26 = 'EURNZD', $27 = 'GBPNZD', $28 = 'EURAUD', $29 = 'EURPLN', $30 = 'ZARJPY', $31 = 'EURGBP', $32 = 'GBPCAD', $33 = 'EURNOK', $34 = 'USDZAR', $35 = 'USDCAD', $36 = 'EURCAD', $37 = 'NOKJPY', $38 = 'EURNZD', $39 = 'HKDJPY', $40 = 'GBPUSD', $41 = 'EURCHF', $42 = 'GBPZAR', $43 = 'USDMXN', $44 = 'EURSEK', $45 = 'USDSGD', $46 = 'EURMXN', $47 = 'AUDJPY', $48 = 'CADJPY', $49 = 'GBPCAD', $50 = 'CADCHF', $51 = 'USDPLN', $52 = 'EURCAD', $53 = '515852059296080307', $54 = 'symbol', $55 = 'AUDJPY', $56 = 'USDMXN', $57 = 'NZDJPY', $58 = 'EURMXN', $59 = 'USDNOK', $60 = 'USDJPY', $61 = 'NOKJPY', $62 = 'CADJPY', $63 = 'GBPJPY', $64 = 'CHFJPY', $65 = 'ZARJPY', $66 = 'USDZAR', $67 = 'EURNOK', $68 = 'HKDJPY', $69 = 'USDSEK', $70 = 'GBPZAR', $71 = 'USDDKK', $72 = 'EURJPY', $73 = 'EURTRY', $74 = 'EURSEK', $75 = 'USDPLN', $76 = 'GBPAUD', $77 = 'USDCNH', $78 = 'EURNZD', $79 = 'GBPNZD', $80 = 'EURAUD', $81 = 'EURPLN', $82 = 'ZARJPY', $83 = 'EURGBP', $84 = 'GBPCAD', $85 = 'EURNOK', $86 = 'USDZAR', $87 = 'USDCAD', $88 = 'EURCAD', $89 = 'NOKJPY', $90 = 'EURNZD', $91 = 'HKDJPY', $92 = 'GBPUSD', $93 = 'EURCHF', $94 = 'GBPZAR', $95 = 'USDMXN', $96 = 'EURSEK', $97 = 'USDSGD', $98 = 'EURMXN', $99 = 'AUDJPY', $100 = 'CADJPY', $101 = 'GBPCAD', $102 = 'CADCHF', $103 = 'USDPLN', $104 = 'EURCAD'
select category, ;

Date: 2026-03-30 09:11:23 Duration: 1ms Database: postgres parameters: $1 = '515852059324736307', $2 = 'symbol', $3 = 'USDMXN', $4 = 'CHFZAR', $5 = 'AUDJPY', $6 = 'CADJPY', $7 = 'USDJPY', $8 = 'USDZAR', $9 = 'CHFJPY', $10 = 'GBPZAR', $11 = 'EURMXN', $12 = 'ZARJPY', $13 = 'TRYJPY', $14 = 'EURCNH', $15 = 'NZDJPY', $16 = 'AUDZAR', $17 = 'GBPJPY', $18 = 'EURZAR', $19 = 'USDHUF', $20 = 'EURNOK', $21 = 'USDNOK', $22 = 'EURTRY', $23 = 'USDSEK', $24 = 'EURHKD', $25 = 'SGDJPY', $26 = 'USDCZK', $27 = 'USDDKK', $28 = 'CHFHUF', $29 = 'EURJPY', $30 = 'EURSEK', $31 = 'NZDSEK', $32 = 'EURHUF', $33 = 'USDPLN', $34 = 'GBPNZD', $35 = 'USDCNH', $36 = 'USDILS', $37 = 'EURCZK', $38 = 'EURNZD', $39 = 'GBPAUD', $40 = 'EURPLN', $41 = 'EURAUD', $42 = 'EURCZK', $43 = 'TRYJPY', $44 = 'EURGBP', $45 = 'EURHUF', $46 = 'CHFHUF', $47 = 'USDTRY', $48 = 'GBPCAD', $49 = 'ZARJPY', $50 = 'USDCAD', $51 = 'EURDKK', $52 = 'AUDZAR'
select category, ;

Date: 2026-03-30 09:00:53 Duration: 1ms Database: postgres parameters: $1 = '515852059324253307', $2 = 'symbol', $3 = 'USDMXN', $4 = 'CHFZAR', $5 = 'AUDJPY', $6 = 'CADJPY', $7 = 'USDJPY', $8 = 'USDZAR', $9 = 'CHFJPY', $10 = 'GBPZAR', $11 = 'EURMXN', $12 = 'ZARJPY', $13 = 'TRYJPY', $14 = 'EURCNH', $15 = 'NZDJPY', $16 = 'AUDZAR', $17 = 'GBPJPY', $18 = 'EURZAR', $19 = 'USDHUF', $20 = 'EURNOK', $21 = 'USDNOK', $22 = 'EURTRY', $23 = 'USDSEK', $24 = 'EURHKD', $25 = 'SGDJPY', $26 = 'USDCZK', $27 = 'USDDKK', $28 = 'CHFHUF', $29 = 'EURJPY', $30 = 'EURSEK', $31 = 'NZDSEK', $32 = 'EURHUF', $33 = 'USDPLN', $34 = 'GBPNZD', $35 = 'USDCNH', $36 = 'USDILS', $37 = 'EURCZK', $38 = 'EURNZD', $39 = 'GBPAUD', $40 = 'EURPLN', $41 = 'EURAUD', $42 = 'EURCZK', $43 = 'TRYJPY', $44 = 'EURGBP', $45 = 'EURHUF', $46 = 'CHFHUF', $47 = 'USDTRY', $48 = 'GBPCAD', $49 = 'ZARJPY', $50 = 'USDCAD', $51 = 'EURDKK', $52 = 'AUDZAR', $53 = '515852059324253307', $54 = 'symbol', $55 = 'USDMXN', $56 = 'CHFZAR', $57 = 'AUDJPY', $58 = 'CADJPY', $59 = 'USDJPY', $60 = 'USDZAR', $61 = 'CHFJPY', $62 = 'GBPZAR', $63 = 'EURMXN', $64 = 'ZARJPY', $65 = 'TRYJPY', $66 = 'EURCNH', $67 = 'NZDJPY', $68 = 'AUDZAR', $69 = 'GBPJPY', $70 = 'EURZAR', $71 = 'USDHUF', $72 = 'EURNOK', $73 = 'USDNOK', $74 = 'EURTRY', $75 = 'USDSEK', $76 = 'EURHKD', $77 = 'SGDJPY', $78 = 'USDCZK', $79 = 'USDDKK', $80 = 'CHFHUF', $81 = 'EURJPY', $82 = 'EURSEK', $83 = 'NZDSEK', $84 = 'EURHUF', $85 = 'USDPLN', $86 = 'GBPNZD', $87 = 'USDCNH', $88 = 'USDILS', $89 = 'EURCZK', $90 = 'EURNZD', $91 = 'GBPAUD', $92 = 'EURPLN', $93 = 'EURAUD', $94 = 'EURCZK', $95 = 'TRYJPY', $96 = 'EURGBP', $97 = 'EURHUF', $98 = 'CHFHUF', $99 = 'USDTRY', $100 = 'GBPCAD', $101 = 'ZARJPY', $102 = 'USDCAD', $103 = 'EURDKK', $104 = 'AUDZAR'

7

633ms

25,356

Details

0ms

28ms

0ms

select 1;

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	09	25,356	633ms	0ms

select 1;

Date: 2026-03-30 09:36:48 Duration: 28ms Database: postgres
select 1;

Date: 2026-03-30 09:35:52 Duration: 12ms Database: postgres
select 1;

Date: 2026-03-30 09:12:13 Duration: 9ms Database: postgres

8

571ms

19

Details

0ms

48ms

30ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	09	19	571ms	30ms

with wh_patitioned as ( ;

Date: 2026-03-30 09:12:13 Duration: 48ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2026-03-30 09:41:56 Duration: 46ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2026-03-30 09:12:12 Duration: 42ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'

9

347ms

30

Details

0ms

19ms

11ms

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

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	09	30	347ms	11ms

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

Date: 2026-03-30 09:31:55 Duration: 19ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;

Date: 2026-03-30 09:17:24 Duration: 19ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;

Date: 2026-03-30 09:02:44 Duration: 19ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

10

333ms

43

Details

4ms

15ms

7ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #10

Day	Hour	Count	Duration	Avg duration
	09	43	333ms	7ms

WITH last_candle AS ( ;

Date: 2026-03-30 09:46:55 Duration: 15ms Database: postgres parameters: $1 = '667', $2 = '667'
WITH last_candle AS ( ;

Date: 2026-03-30 09:01:31 Duration: 15ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-03-30 09:08:06 Duration: 14ms Database: postgres parameters: $1 = '621', $2 = '621'

11

324ms

422

Details

0ms

8ms

0ms

SELECT absolutetimezoneoffset;

Times Reported Time consuming bind #11

Day	Hour	Count	Duration	Avg duration
	09	422	324ms	0ms

SELECT absolutetimezoneoffset;

Date: 2026-03-30 09:11:23 Duration: 8ms Database: postgres parameters: $1 = '627', $2 = 'BROKER'
SELECT absolutetimezoneoffset;

Date: 2026-03-30 09:53:08 Duration: 2ms Database: postgres parameters: $1 = '619', $2 = 'FOREX'
SELECT absolutetimezoneoffset;

Date: 2026-03-30 09:11:24 Duration: 1ms Database: postgres parameters: $1 = '667', $2 = 'BROKER'

12

314ms

3,332

Details

0ms

4ms

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 #12

Day	Hour	Count	Duration	Avg duration
	09	3,332	314ms	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: 2026-03-30 09:17:20 Duration: 4ms Database: postgres parameters: $1 = '2026-03-27 22:30:00', $2 = '200.135', $3 = '200.275', $4 = '199.15', $5 = '199.37', $6 = '1392', $7 = '515840249387271300', $8 = '0', $9 = '2026-03-30 09:17:20.916', $10 = '2026-03-30 09:17:20.908', $11 = '200.135', $12 = '200.275', $13 = '199.15', $14 = '199.37', $15 = '1392', $16 = '0', $17 = '2026-03-30 09:17:20.916', $18 = '2026-03-30 09:17:20.908'
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: 2026-03-30 09:47:52 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 22:30:00', $2 = '293.385', $3 = '293.505', $4 = '291.64', $5 = '292.45', $6 = '644', $7 = '515840249444435300', $8 = '0', $9 = '2026-03-30 09:47:52.523', $10 = '2026-03-30 09:47:52.419', $11 = '293.385', $12 = '293.505', $13 = '291.64', $14 = '292.45', $15 = '644', $16 = '0', $17 = '2026-03-30 09:47:52.523', $18 = '2026-03-30 09:47:52.419'
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: 2026-03-30 09:01:54 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 22:30:00', $2 = '108.225', $3 = '108.26', $4 = '107.715', $5 = '108.05', $6 = '259', $7 = '515840249426757300', $8 = '0', $9 = '2026-03-30 09:01:54.922', $10 = '2026-03-30 09:01:54.81', $11 = '108.225', $12 = '108.26', $13 = '107.715', $14 = '108.05', $15 = '259', $16 = '0', $17 = '2026-03-30 09:01:54.922', $18 = '2026-03-30 09:01:54.81'

13

294ms

5,656

Details

0ms

2ms

0ms

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

Times Reported Time consuming bind #13

Day	Hour	Count	Duration	Avg duration
	09	5,656	294ms	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: 2026-03-30 09:30:21 Duration: 2ms Database: postgres parameters: $1 = '2026-03-27 22:45:00', $2 = '139.76', $3 = '139.85', $4 = '139.285', $5 = '139.805', $6 = '447', $7 = '515840249434121300', $8 = '0', $9 = '2026-03-30 09:30:21.892', $10 = '2026-03-30 09:30:21.705', $11 = '139.76', $12 = '139.85', $13 = '139.285', $14 = '139.805', $15 = '447', $16 = '0', $17 = '2026-03-30 09:30:21.892', $18 = '2026-03-30 09:30:21.705'
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: 2026-03-30 09:47:28 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 23:45:00', $2 = '4505.825', $3 = '4505.865', $4 = '4491.36', $5 = '4493.925', $6 = '3739', $7 = '515840249390867300', $8 = '0', $9 = '2026-03-30 09:47:28.236', $10 = '2026-03-30 09:47:28.193', $11 = '4505.825', $12 = '4505.865', $13 = '4491.36', $14 = '4493.925', $15 = '3739', $16 = '0', $17 = '2026-03-30 09:47:28.236', $18 = '2026-03-30 09:47:28.193'
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: 2026-03-30 09:47:20 Duration: 0ms Database: postgres parameters: $1 = '2026-03-30 10:30:00', $2 = '0.68563', $3 = '0.68571', $4 = '0.6848', $5 = '0.68488', $6 = '860', $7 = '515840249374319300', $8 = '0', $9 = '2026-03-30 09:47:20.108', $10 = '2026-03-30 09:47:20.049', $11 = '0.68563', $12 = '0.68571', $13 = '0.6848', $14 = '0.68488', $15 = '860', $16 = '0', $17 = '2026-03-30 09:47:20.108', $18 = '2026-03-30 09:47:20.049'

14

200ms

2,135

Details

0ms

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

Times Reported Time consuming bind #14

Day	Hour	Count	Duration	Avg duration
	09	2,135	200ms	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: 2026-03-30 09:32:22 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 22:00:00', $2 = '274.76', $3 = '275.33', $4 = '273.775', $5 = '273.88', $6 = '3000', $7 = '515840249421801300', $8 = '0', $9 = '2026-03-30 09:32:22.638', $10 = '2026-03-30 09:32:22.638', $11 = '274.76', $12 = '275.33', $13 = '273.775', $14 = '273.88', $15 = '3000', $16 = '0', $17 = '2026-03-30 09:32:22.639', $18 = '2026-03-30 09:32:22.638'
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: 2026-03-30 09:46:52 Duration: 0ms Database: postgres parameters: $1 = '2026-03-27 22:00:00', $2 = '484.525', $3 = '485.805', $4 = '482.515', $5 = '483.44', $6 = '1157', $7 = '515840249431852300', $8 = '0', $9 = '2026-03-30 09:46:52.41', $10 = '2026-03-30 09:46:52.41', $11 = '484.525', $12 = '485.805', $13 = '482.515', $14 = '483.44', $15 = '1157', $16 = '0', $17 = '2026-03-30 09:46:52.41', $18 = '2026-03-30 09:46:52.41'
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: 2026-03-30 09:02:09 Duration: 0ms Database: postgres parameters: $1 = '2026-03-30 09:00:00', $2 = '0.57411', $3 = '0.5751', $4 = '0.57406', $5 = '0.57416', $6 = '1961', $7 = '515840230541091300', $8 = '0', $9 = '2026-03-30 09:02:09.19', $10 = '2026-03-30 09:02:09.19', $11 = '0.57411', $12 = '0.5751', $13 = '0.57406', $14 = '0.57416', $15 = '1961', $16 = '0', $17 = '2026-03-30 09:02:09.19', $18 = '2026-03-30 09:02:09.19'

15

171ms

4

Details

30ms

47ms

42ms

with sym_info as ( ;

Times Reported Time consuming bind #15

Day	Hour	Count	Duration	Avg duration
	09	4	171ms	42ms

with sym_info as ( ;

Date: 2026-03-30 09:22:08 Duration: 47ms 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: 2026-03-30 09:36:13 Duration: 47ms 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: 2026-03-30 09:36:01 Duration: 46ms Database: postgres parameters: $1 = '627', $2 = 'Forex', $3 = 'Forex', $4 = '627', $5 = 'Forex', $6 = '627', $7 = '627', $8 = 'Forex', $9 = '627'

16

103ms

98

Details

0ms

5ms

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 #16

Day	Hour	Count	Duration	Avg duration
	09	98	103ms	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: 2026-03-30 09:30:59 Duration: 5ms 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: 2026-03-30 09:05:35 Duration: 2ms Database: postgres parameters: $1 = '558', $2 = 'US30', $3 = '558'
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2026-03-30 09:06:44 Duration: 2ms Database: postgres parameters: $1 = '632', $2 = 'XAGUSD', $3 = '632'

17

80ms

184

Details

0ms

1ms

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 #17

Day	Hour	Count	Duration	Avg duration
	09	184	80ms	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: 2026-03-30 09:14:59 Duration: 1ms Database: postgres
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2026-03-30 09:14:58 Duration: 1ms Database: postgres
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2026-03-30 09:14:59 Duration: 0ms Database: postgres

18

68ms

12

Details

3ms

9ms

5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	09	12	68ms	5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-03-30 09:01:31 Duration: 9ms Database: postgres parameters: $1 = '627', $2 = '627'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-03-30 09:01:02 Duration: 9ms Database: postgres parameters: $1 = '627', $2 = '627'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-03-30 09:11:05 Duration: 9ms Database: postgres parameters: $1 = '538', $2 = '538'

19

58ms

12

Details

1ms

9ms

4ms

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

Times Reported Time consuming bind #19

Day	Hour	Count	Duration	Avg duration
	09	12	58ms	4ms

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

Date: 2026-03-30 09:00:34 Duration: 9ms Database: postgres parameters: $1 = '619', $2 = 'AXIORY', $3 = 'EURUSD', $4 = 'USDJPY', $5 = 'GBPUSD', $6 = 'AUDUSD', $7 = 'USDCHF', $8 = 'USDCAD', $9 = 'NZDUSD', $10 = 'GBPJPY', $11 = 'EURJPY', $12 = 'EURCHF', $13 = 'GBPCHF', $14 = 'EURCAD', $15 = 'GBPCAD', $16 = 'EURNZD', $17 = 'GBPNZD', $18 = 'CADJPY', $19 = 'CADCHF', $20 = 'CHFJPY', $21 = 'NZDJPY', $22 = 'XAUUSD', $23 = 'XAGUSD', $24 = 'EURUSD', $25 = 'USDJPY', $26 = 'GBPUSD', $27 = 'AUDUSD', $28 = 'USDCHF', $29 = 'USDCAD', $30 = 'NZDUSD', $31 = 'GBPJPY', $32 = 'EURJPY', $33 = 'EURCHF', $34 = 'GBPCHF', $35 = 'EURCAD', $36 = 'GBPCAD', $37 = 'EURNZD', $38 = 'GBPNZD', $39 = 'CADJPY', $40 = 'CADCHF', $41 = 'CHFJPY', $42 = 'NZDJPY', $43 = 'XAUUSD', $44 = 'XAGUSD', $45 = '5'
WITH pre_symbols AS ( /* find relevant symbols */ ;

Date: 2026-03-30 09:14:56 Duration: 8ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD'
WITH pre_symbols AS ( /* find relevant symbols */ ;

Date: 2026-03-30 09:14:56 Duration: 7ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'

20

48ms

844

Details

0ms

select distinct category;

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	09	844	48ms	0ms

select distinct category;

Date: 2026-03-30 09:53:09 Duration: 0ms Database: postgres parameters: $1 = '515852059324253307'
select distinct category;

Date: 2026-03-30 09:11:20 Duration: 0ms Database: postgres parameters: $1 = '515852059305993307', $2 = '515852059305993307'
select distinct category;

Date: 2026-03-30 09:44:46 Duration: 0ms Database: postgres parameters: $1 = '515852059305993307', $2 = '515852059305993307'

Log levels

Key values

407,003 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	540	0.13%
DETAIL	92,994	22.85%
ERROR	240	0.06%
LOG	312,075	76.68%
STATEMENT	1,154	0.28%

Events distribution

Key values

0 PANIC entries
0 FATAL entries
240 ERROR entries
0 WARNING entries

Most Frequent Errors/Events

Key values

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

Rank

Times reported

Error

1

239

Details

ERROR: canceling statement due to statement timeout

Times Reported Most Frequent Error / Event #1

Day	Hour	Count
Mar 30	09	239

ERROR: canceling statement due to statement timeout

2

1

Details

ERROR: relation "..." does not exist

Times Reported Most Frequent Error / Event #2

Day	Hour	Count
Mar 30	09	1

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

Global information

Overview

Global Stats

SQL Traffic

Key values

SELECT Traffic

Key values

INSERT/UPDATE/DELETE Traffic

Key values

Queries duration

Key values

Prepared queries ratio

Key values

General Activity

Connections

Established Connections

Key values

Connections per database

Key values

Connections per user

Key values

Connections per host

Key values

Sessions

Simultaneous sessions

Key values

Histogram of session times

Key values

Sessions per database

Key values

Sessions per user

Key values

Sessions per host

Key values

Sessions per application

Key values

Checkpoints / Restartpoints

Checkpoints Buffers

Key values

Checkpoints Wal files

Key values

Checkpoints distance

Key values

Checkpoints Activity

Checkpoint causes

Key values

Temporary Files

Size of temporary files

Key values

Number of temporary files

Key values

Temporary Files Activity

Queries generating the most temporary files (N)

Queries generating the largest temporary files

Vacuums

Vacuums / Analyzes Distribution

Key values

Analyzes per table

Key values

Vacuums per table

Key values

Tuples removed per table

Key values

Pages removed per table

Key values

Autovacuum Activity

Locks

Locks by types

Key values

Type of locks

Most frequent waiting queries (N)

Queries that waited the most

Queries

Queries by type

Key values

Queries by database

Key values

Queries by user

Key values

Duration by user