pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Fri Feb 13 13:59:44 2026
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-02-13_150000.log
Parsed 1,774,571 log entries in 43s
Log start from 2026-02-13 15:00:00 to 2026-02-13 15:59:42

Global Stats

250 Number of unique normalized queries
200,004 Number of queries
2h3m35s Total query duration
2026-02-13 15:00:00 First query
2026-02-13 15:59:42 Last query
4,703 queries/s at 2026-02-13 15:45:04 Query peak

2h3m35s Total query duration
7s658ms Prepare/parse total duration
49s629ms Bind total duration
2h2m38s Execute total duration

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

40 Total number of automatic vacuums
57 Total number of automatic analyzes

721 Number temporary file
192.30 MiB Max size of temporary file
8.32 MiB Average size of temporary file

3,238 Total number of sessions
13 sessions at 2026-02-13 15:58:48 Session peak
2d19h20m30s Total duration of sessions
1m14s Average duration of sessions
61 Average queries per session
2s290ms Average queries duration per session
1m12s Average idle time per session

3,236 Total number of connections
27 connections/s at 2026-02-13 15:48:48 Connection peak
3 Total number of databases

SQL Traffic

Key values

4,703 queries/s Query Peak
2026-02-13 15:45:04 Date

SELECT Traffic

Key values

2,321 queries/s Query Peak
2026-02-13 15:45:04 Date

INSERT/UPDATE/DELETE Traffic

Key values

201 queries/s Query Peak
2026-02-13 15:00:55 Date

Queries duration

Key values

2h3m35s Total query duration

Prepared queries ratio

Key values

0.00 Ratio of bind vs prepare
0.00 % Ratio between prepared and "usual" statements

General Activity

Day	Hour	Count	Min duration	Max duration	Avg duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Feb 13	15	200,004	0ms	39s791ms	36ms	2m41s	2m51s	4m2s

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Feb 13	15	61,018	26	0ms	0ms	0ms	0ms

Day	Hour	INSERT	UPDATE	DELETE	COPY FROM	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Feb 13	15	25,269	2,779	16	96	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Feb 13	15	21,350	73,274	3.43	22.51%

Day	Hour	Count	Average / Second
Feb 13	15	3,236	0.90/s

Day	Hour	Count	Average Duration	Average idle time
Feb 13	15	3,238	1m14s	1m12s

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Established Connections

Key values

27 connections Connection Peak
2026-02-13 15:48:48 Date

Connections per database

Key values

acaweb_fx Main Database
3,236 connections Total

Chart
Table

Database	User	Count
acaweb_fx		3,126
	postgres	2,770
	psql	356
socialmedia		110
	postgres	110

Connections per user

Key values

postgres Main User
3,236 connections Total

Chart
Table

User	Count
postgres	2,880
psql	356

Connections per host

Key values

192.168.4.142 Main host with 1286 connections
3,236 Total connections

Chart
Table

Host	Count
127.0.0.1	112
192.168.0.114	10
192.168.0.216	103
192.168.0.74	218
192.168.1.127	26
192.168.1.145	228
192.168.1.15	143
192.168.1.20	252
192.168.1.231	20
192.168.1.239	15
192.168.1.90	41
192.168.2.126	39
192.168.2.182	24
192.168.3.199	36
192.168.4.119	1
192.168.4.142	1,286
192.168.4.150	10
192.168.4.238	16
192.168.4.33	75
192.168.4.45	7
192.168.4.98	330
[local]	244

Simultaneous sessions

Key values

13 sessions Session Peak
2026-02-13 15:58:48 Date

Histogram of session times

Key values

2,652 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	2,652	81.90%
500ms-1s	177	5.47%
1s-30s	254	7.84%
30s-1m	9	0.28%
1m-10m	59	1.82%
10m-30m	68	2.10%
30m-1h	6	0.19%
1h-8h	13	0.40%
> 8h	0	0.00%

Sessions per database

Key values

acaweb_fx Main Database
3,238 sessions Total

Chart
Table

Database	User	Count	Total Duration	Average Duration
acaweb_fx	3,126	2d18h5m54s	1m16s
socialmedia	112	1h14m35s	39s961ms

Sessions per user

Key values

postgres Main User
3,238 sessions Total

Chart
Table

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

Sessions per host

Key values

192.168.4.142 Main Host
3,238 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
127.0.0.1	112	9s231ms	82ms
192.168.0.114	12	1h14m2s	6m10s
192.168.0.216	103	1m43s	1s1ms
192.168.0.74	218	9h6m28s	2m30s
192.168.1.127	26	4s155ms	159ms
192.168.1.145	228	4h17m2s	1m7s
192.168.1.15	143	7h38m39s	3m12s
192.168.1.20	252	14h33m50s	3m28s
192.168.1.231	20	9h53m	29m39s
192.168.1.239	15	98ms	6ms
192.168.1.90	41	39s743ms	969ms
192.168.2.126	39	6s290ms	161ms
192.168.2.182	24	4s192ms	174ms
192.168.3.199	36	1s429ms	39ms
192.168.4.119	1	204ms	204ms
192.168.4.142	1,286	7m47s	363ms
192.168.4.150	10	20h15m53s	2h1m35s
192.168.4.238	16	20s669ms	1s291ms
192.168.4.33	75	5m29s	4s388ms
192.168.4.45	7	35s172ms	5s24ms
192.168.4.98	330	14s347ms	43ms
[local]	244	4m19s	1s61ms

Sessions per application

Key values

unknown Main Host
3,238 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	3,238	2d19h20m30s	1m14s

Checkpoints Buffers

Key values

12,259 buffers Checkpoint Peak
2026-02-13 15:06:16 Date
209.988 seconds Highest write time
0.026 seconds Sync time

Checkpoints Wal files

Key values

5 files Wal files usage Peak
2026-02-13 15:06:16 Date

Checkpoints distance

Key values

161.87 Mo Distance Peak
2026-02-13 15:06:16 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Feb 13	15	47,331	1,955.495s	0.095s	1,955.898s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Feb 13	15	0	0	24	2,056	0.010s	0s

Day	Hour	Count	Avg time (sec)
Feb 13	15	0	0s

Day	Hour	Mean distance	Mean estimate
Feb 13	15	33,676.33 kB	65,543.75 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

184.81 MiB Temp Files size Peak
2026-02-13 15:00:09 Date

Number of temporary files

Key values

30 per second Temp Files Peak
2026-02-13 15:32:11 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Feb 13	15	721	5.86 GiB	8.32 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	92	399.18 MiB	4.22 MiB	4.46 MiB	4.34 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: 2026-02-13 15:00:23 Duration: 0ms
2	44	266.84 MiB	3.34 MiB	8.81 MiB	6.06 MiB	jr.resultuid as resultuid, jr.direction as direction, jr.patternendtime as identified, jr.patternlengthbars as length, jr.patternstarttime as patternstarttime, case when jr.trendchangeid = ? then ? else ? end as trendchange, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, jp.patternname as pattern_name, dtt.timezone as timezone, ? as age, cps.pip, g.basegroupname from japsticks_results jr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = jr.symbolid inner join relevance_japsticks_results rar on rar.resultuid = jr.resultuid inner join symbols s on jr.symbolid = s.symbolid and s.nonliquid = ? inner join japsticks_patterns jp on jr.patternid = jp.id inner join downloadersymbolsettings dss on jr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where jr.gmttimefound > now() - interval ? and s.deleted = ? and (jr.simulation = ? or jr.simulation is null) and (rar.relevant = ?) --and (semicolon_age = ? or rar.age <= semicolon_age) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or jp.patternname in (...)) and (? = ? or jr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results order by symbolid, resultuid ) select * from results order by identified desc, length desc ; jr.resultuid AS resultuid, jr.direction AS direction, jr.patternendtime AS identified, jr.patternlengthbars AS length, jr.patternstarttime AS patternstarttime, case when jr.trendchangeid = 1 then 'Continuation' else 'Reversal' end AS trendchange, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, jp.patternname AS pattern_name, dtt.timezone AS timezone, 0 AS age, cps.pip, g.basegroupname FROM japsticks_results jr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = jr.symbolid INNER JOIN relevance_japsticks_results rar ON rar.resultuid = jr.resultuid INNER JOIN symbols s ON jr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN japsticks_patterns jp ON jr.patternid = jp.id INNER JOIN downloadersymbolsettings dss ON jr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE jr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (jr.simulation = 0 OR jr.simulation IS NULL) AND (rar.relevant = 1) --AND (semicolon_age = 0 OR rar.age <= semicolon_age) AND ($2 = 0 OR s.timegranularity in ($3)) AND ($4 = 0 OR s.exchange in ($5)) AND ($6 = 0 OR coalesce(bim.code, s.symbol) in ($7)) AND ($8 = 0 OR jp.patternname in ($9)) AND ($10 = 0 OR jr.patternlengthbars <= $11)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-02-13 15:01:02 Duration: 0ms
3	30	1.67 GiB	2.58 MiB	192.30 MiB	56.89 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = ? ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?; with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; Date: 2026-02-13 15:00:09 Duration: 0ms
4	16	738.38 MiB	46.15 MiB	46.15 MiB	46.15 MiB	update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid; UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid; Date: 2026-02-13 15:01:13 Duration: 0ms
5	16	1.22 GiB	78.33 MiB	78.33 MiB	78.33 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid; with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; Date: 2026-02-13 15:01:16 Duration: 0ms
6	8	1.09 GiB	139.63 MiB	139.69 MiB	139.65 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2026-02-13 15:02:16 Duration: 0ms
7	4	358.27 MiB	89.48 MiB	89.67 MiB	89.57 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2026-02-13 15:02:05 Duration: 0ms
8	1	3.02 MiB	3.02 MiB	3.02 MiB	3.02 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: 2026-02-13 15:01:54 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	192.30 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-13 15:10:04 ]
2	162.70 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-13 15:50:07 ]
3	156.62 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-13 15:20:08 ]
4	139.69 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-13 15:02:16 ]
5	139.66 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-13 15:32:17 ]
6	139.66 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-13 15:17:15 ]
7	139.65 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-13 15:05:33 ]
8	139.63 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-13 15:47:15 ]
9	139.63 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-13 15:20:33 ]
10	139.63 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-13 15:35:32 ]
11	139.63 MiB	select updateresultsmaterializedview (); [ Date: 2026-02-13 15:50:32 ]
12	120.56 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-13 15:40:04 ]
13	110.75 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-13 15:30:06 ]
14	89.67 MiB	select updateageforrelevantresults (); [ Date: 2026-02-13 15:02:05 ]
15	89.61 MiB	select updateageforrelevantresults (); [ Date: 2026-02-13 15:32:06 ]
16	89.51 MiB	select updateageforrelevantresults (); [ Date: 2026-02-13 15:47:05 ]
17	89.48 MiB	select updateageforrelevantresults (); [ Date: 2026-02-13 15:17:05 ]
18	85.14 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-02-13 15:00:06 ]
19	78.33 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-02-13 15:01:16 ]
20	78.33 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2026-02-13 15:03:15 ]

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)
57 analyzes Total

Chart
Table

Table	Number of analyzes
acaweb_fx.public.solr_relevance_old	16
acaweb_fx.pg_catalog.pg_attribute	8
acaweb_fx.pg_catalog.pg_type	4
acaweb_fx.public.relevance_keylevels_results	4
acaweb_fx.pg_catalog.pg_class	4
acaweb_fx.public.relevance_autochartist_results	4
acaweb_fx.public.relevance_fibonacci_results	4
acaweb_fx.public.datafeeds_latestrun	3
acaweb_fx.pg_catalog.pg_index	2
acaweb_fx.pg_catalog.pg_depend	2
acaweb_fx.public.latest_t15_candle_view	2
acaweb_fx.public.autochartist_symbolupdates	1
acaweb_fx.public.solr_imports	1
socialmedia.public.processstatevariables	1
acaweb_fx.public.latest_candle_datetime_per_receng	1
Total	57

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	15,324	0	52	0	0	11,096	16	1,943,368
acaweb_fx.pg_catalog.pg_attribute	4	4	3,405	0	629	0	268	1,461	571	3,281,745
acaweb_fx.public.datafeeds_latestrun	3	0	347	0	13	0	0	27	4	23,494
acaweb_fx.pg_toast.pg_toast_2619	2	2	336	0	47	0	0	206	48	193,280
acaweb_fx.pg_catalog.pg_type	2	2	331	0	46	0	0	147	33	181,043
acaweb_fx.public.relevance_keylevels_results	2	2	7,821	0	221	4	188	1,878	1,303	4,383,766
acaweb_fx.public.relevance_autochartist_results	2	2	6,668	0	161	0	418	1,652	1,129	3,691,864
acaweb_fx.pg_catalog.pg_class	2	2	944	0	77	0	0	307	77	412,923
acaweb_fx.public.relevance_fibonacci_results	2	2	2,380	0	35	2	90	395	237	874,712
acaweb_fx.pg_catalog.pg_index	1	1	90	0	11	0	0	28	10	75,038
acaweb_fx.public.autochartist_symbolupdates	1	1	23,350	0	2,552	1	38,248	6,341	5,315	2,501,080
acaweb_fx.pg_catalog.pg_statistic	1	1	1,004	0	107	0	594	465	100	483,195
acaweb_fx.pg_catalog.pg_depend	1	1	396	0	75	0	59	181	63	334,372
acaweb_fx.public.latest_t15_candle_view	1	1	66	0	1	0	0	6	1	9,079
Total	40	37	62,462	47,315	4,027	7	39,865	24,190	8,907	18,388,959

Tuples removed per table

Key values

public.solr_relevance_old (70990) Main table with removed tuples on database acaweb_fx
89070 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	70,990	110,496	0	0	3,866
acaweb_fx.pg_catalog.pg_attribute	4	4	5,999	43,106	0	0	1,043
acaweb_fx.public.autochartist_symbolupdates	1	1	5,196	51,113	3	0	40,691
acaweb_fx.public.relevance_autochartist_results	2	2	2,020	19,458	0	0	760
acaweb_fx.public.relevance_keylevels_results	2	2	1,917	25,044	0	0	558
acaweb_fx.pg_catalog.pg_depend	1	1	856	14,410	0	0	140
acaweb_fx.pg_catalog.pg_type	2	2	797	2,892	0	0	88
acaweb_fx.pg_catalog.pg_statistic	1	1	519	3,780	0	0	1,194
acaweb_fx.pg_catalog.pg_class	2	2	286	3,298	0	0	300
acaweb_fx.public.datafeeds_latestrun	3	0	150	66	24	0	48
acaweb_fx.public.relevance_fibonacci_results	2	2	136	3,385	0	0	204
acaweb_fx.pg_toast.pg_toast_2619	2	2	133	337	3	0	108
acaweb_fx.public.latest_t15_candle_view	1	1	63	14	0	0	1
acaweb_fx.pg_catalog.pg_index	1	1	8	813	0	0	22
Total	40	37	89,070	278,212	30	0	49,023

Pages removed per table

Key values

unknown (0) Main table with removed pages on database unknown
0 pages Total removed

Chart
Table

Pages removed per tables

NO DATASET

Table	Number of vacuums	Index scans	Tuples removed
acaweb_fx.pg_catalog.pg_index	1	1	8
acaweb_fx.pg_toast.pg_toast_2619	2	2	133
acaweb_fx.pg_catalog.pg_type	2	2	797
acaweb_fx.public.datafeeds_latestrun	3	0	150
acaweb_fx.public.autochartist_symbolupdates	1	1	5196
acaweb_fx.pg_catalog.pg_statistic	1	1	519
acaweb_fx.pg_catalog.pg_attribute	4	4	5999
acaweb_fx.pg_catalog.pg_depend	1	1	856
acaweb_fx.public.latest_t15_candle_view	1	1	63
acaweb_fx.public.relevance_keylevels_results	2	2	1917
acaweb_fx.public.solr_relevance_old	16	16	70990
acaweb_fx.public.relevance_autochartist_results	2	2	2020
acaweb_fx.pg_catalog.pg_class	2	2	286
acaweb_fx.public.relevance_fibonacci_results	2	2	136
Total	40	37	89,070

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Feb 13	15	40	57

↑ Back to the top of the Autovacuum Activity table

Locks by types

Key values

unknown Main Lock Type
0 locks Total

Chart
Table

Type of locks

NO DATASET

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

Most frequent waiting queries (N)

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

Queries that waited the most

Rank	Wait time	Query
NO DATASET

Queries by type

Key values

61,018 Total read queries
33,814 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	61,018	30.51%
INSERT	25,269	12.63%
UPDATE	2,779	1.39%
DELETE	16	0.01%
COPY FROM	96	0.05%
COPY TO	26	0.01%
CTE	4,766	2.38%
DDL	16	0.01%
TCL	846	0.42%
CURSOR	0	0.00%
OTHERS	105,172	52.58%

Queries by database

Key values

unknown Main database
199,029 Requests
2h2m38s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	865	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	182	0ms
	select	72	0ms
	tcl	331	0ms
	update	38	0ms
socialmedia	Total	110	0ms
	others	26	0ms
	select	75	0ms
	tcl	9	0ms
unknown	Total	199,029	2h2m38s
	copy from	16	0ms
	cte	4,662	0ms
	insert	25,269	0ms
	others	4,962	0ms
	select	60,871	0ms
	tcl	506	0ms
	update	2,741	0ms

Queries by user

Key values

unknown Main user
199,029 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	975	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	208	0ms
	select	147	0ms
	tcl	340	0ms
	update	38	0ms
unknown	Total	199,029	2h2m38s
	copy from	16	0ms
	cte	4,662	0ms
	insert	25,269	0ms
	others	4,962	0ms
	select	60,871	0ms
	tcl	506	0ms
	update	2,741	0ms

Duration by user

Key values

2h2m38s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	975	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	208	0ms
	select	147	0ms
	tcl	340	0ms
	update	38	0ms
unknown	Total	199,029	2h2m38s
	copy from	16	0ms
	cte	4,662	0ms
	insert	25,269	0ms
	others	4,962	0ms
	select	60,871	0ms
	tcl	506	0ms
	update	2,741	0ms

Queries by host

Key values

unknown Main host
200,004 Requests
2h2m38s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	200,004	2h2m38s
	copy from	96	0ms
	copy to	26	0ms
	cte	4,766	0ms
	ddl	16	0ms
	delete	16	0ms
	insert	25,269	0ms
	others	5,170	0ms
	select	61,018	0ms
	tcl	846	0ms
	update	2,779	0ms

Queries by application

Key values

unknown Main application
199,648 Requests
2h2m38s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
psql	Total	356	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	38	0ms
unknown	Total	199,648	2h2m38s
	copy from	16	0ms
	cte	4,662	0ms
	insert	25,269	0ms
	others	5,166	0ms
	select	60,946	0ms
	tcl	846	0ms
	update	2,741	0ms

Number of cancelled queries

Key values

0 per second Cancelled query Peak
2026-02-13 15:34:26 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

63,440 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	63,440	63.44%
1-5ms	31,998	32.00%
5-10ms	1,982	1.98%
10-25ms	566	0.57%
25-50ms	210	0.21%
50-100ms	289	0.29%
100-500ms	371	0.37%
500-1000ms	125	0.12%
1000-10000ms	783	0.78%
> 10000ms	238	0.24%

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

28

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 13	15	28	0ms	0ms

2

0ms

4

Details

0ms

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

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Feb 13	15	4	0ms	0ms

3

0ms

2

Details

0ms

select distinct "public"."processes"."live" AS "live" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? order by ? asc;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2	0ms	0ms

4

0ms

232

Details

0ms

with rar_max as ( 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;

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Feb 13	15	232	0ms	0ms

5

0ms

2

Details

0ms

select count(*) from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where (brokerid = ?);

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2	0ms	0ms

6

0ms

2

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2	0ms	0ms

7

0ms

89

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 #7

Day	Hour	Count	Duration	Avg duration
Feb 13	15	89	0ms	0ms

8

0ms

2,058

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 #8

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2,058	0ms	0ms

9

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 #9

Day	Hour	Count	Duration	Avg duration
Feb 13	15	4	0ms	0ms

10

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Feb 13	15	4	0ms	0ms

11

0ms

113

Details

0ms

select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, timegranularity as interval, direction as direction, patternendtime as patternendtime, patternstartprice as psp, patternendprice as pep, target03 as t03, target16 as t16, patternlengthbars as length, p.patternname as patternname, dtt.timezone, cps.pip from fibonacci_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 fibonaccipatterns p on a.pattern = p.patternname left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 13	15	113	0ms	0ms

12

0ms

26

Details

0ms

set datestyle = iso;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Feb 13	15	26	0ms	0ms

13

0ms

2,279

Details

0ms

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

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2,279	0ms	0ms

14

0ms

10

Details

0ms

insert into resultmedia (processresultsid, type, name, filename) values (?, ?, ?, ?) returning id;

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 13	15	10	0ms	0ms

15

0ms

2

Details

0ms

update "public"."processes" set "locale" = ?, "region" = ?, "schedule" = ? where "id" = ?;

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2	0ms	0ms

16

0ms

2

Details

0ms

select t.pricedatetime as pricedatetime, t.open as open, t.high as high, t.low as low, t.close "..." close, t.volume as volume, t.bsf as bsf from t1440 t where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2	0ms	0ms

17

0ms

26

Details

0ms

set client_encoding to ?;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Feb 13	15	26	0ms	0ms

18

0ms

239

Details

0ms

select v.datname, c.relname, v.phase, v.heap_blks_total, v.heap_blks_scanned, v.heap_blks_vacuumed, v.index_vacuum_count, v.max_dead_tuples, v.num_dead_tuples from pg_stat_progress_vacuum as v join pg_class c on c.oid = v.relid;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 13	15	239	0ms	0ms

19

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 #19

Day	Hour	Count	Duration	Avg duration
Feb 13	15	18	0ms	0ms

20

0ms

2

Details

0ms

select distinct "public"."processes"."live" AS "live" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" order by ? asc;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

21,741

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 13	15	21,741	0ms	0ms

2

13,692

Details

0ms

select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Feb 13	15	13,692	0ms	0ms

3

11,016

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
Feb 13	15	11,016	0ms	0ms

4

5,478

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
Feb 13	15	5,478	0ms	0ms

5

5,382

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
Feb 13	15	5,382	0ms	0ms

6

3,804

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Feb 13	15	3,804	0ms	0ms

7

3,137

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
Feb 13	15	3,137	0ms	0ms

8

2,602

Details

0ms

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

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2,602	0ms	0ms

9

2,279

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2,279	0ms	0ms

10

2,219

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2,219	0ms	0ms

11

2,193

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2,193	0ms	0ms

12

2,058

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 #12

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2,058	0ms	0ms

13

2,002

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 #13

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2,002	0ms	0ms

14

1,156

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 #14

Day	Hour	Count	Duration	Avg duration
Feb 13	15	1,156	0ms	0ms

15

1,127

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 #15

Day	Hour	Count	Duration	Avg duration
Feb 13	15	1,127	0ms	0ms

16

614

Details

0ms

with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ) select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as ruid, s.symbolid as sid, s.symbol as sym, longname, shortname, exchange as e, timegranularity as tg, a.patternid as pid, a.direction as d, a.patternprice as pp, atbaridentified as pet, case when (x9 != ?) then x9 when (x8 != ?) then x8 when (x7 != ?) then x7 when (x6 != ?) then x6 when (x5 != ?) then x5 when (x4 != ?) then x4 when (x3 != ?) then x3 when (x2 != ?) then x2 end as pst, patternprice as patp, x0, x1, x2, case when (x3 != ?) then x3 else ? end as x3, case when (x4 != ?) then x4 else ? end as x4, case when (x5 != ?) then x5 else ? end as x5, case when (x6 != ?) then x6 else ? end as x6, case when (x7 != ?) then x7 else ? end as x7, case when (x8 != ?) then x8 else ? end as x8, errormargin as erm, breakoutprice as pe, breakoutbars as be, breakout, atbaridentified as atbar, atpriceidentified as atprice, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzos, dtt.timezone as timezone, approachingtimestamp as apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, furthestprice as fp, newlevels.filtered, a.uniquepointsvalue as upv, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from keylevels_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join hrspatterns p on a.patternid = p.patternid inner join rar_max rm on ? = ? left outer join relevance_keylevels_results rar on a.resultuid = rar.resultuid left join lateral calc_kl_signal_filter (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 13	15	614	0ms	0ms

17

472

Details

0ms

select downloadersymbol, spike_threshold from price_datafeed_spike_threshold where classname = ?;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Feb 13	15	472	0ms	0ms

18

472

Details

0ms

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

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 13	15	472	0ms	0ms

19

436

Details

0ms

select t.pricedatetime as pricedatetime, t.open as open, t.high as high, t.low as low, t.close "..." close, t.volume as volume, t.bsf as bsf from t15 t where t.symbolid = ? and (bsf = ? or bsf is null) and pricedatetime >= ? and pricedatetime <= ? order by pricedatetime desc limit ?;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Feb 13	15	436	0ms	0ms

20

425

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 #20

Day	Hour	Count	Duration	Avg duration
Feb 13	15	425	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

28

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Feb 13	15	28	0ms	0ms

2

0ms

4

Details

0ms

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

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Feb 13	15	4	0ms	0ms

3

0ms

2

Details

0ms

select distinct "public"."processes"."live" AS "live" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? order by ? asc;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2	0ms	0ms

4

0ms

232

Details

0ms

with rar_max as ( 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;

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Feb 13	15	232	0ms	0ms

5

0ms

2

Details

0ms

select count(*) from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where (brokerid = ?);

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2	0ms	0ms

6

0ms

2

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2	0ms	0ms

7

0ms

89

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 #7

Day	Hour	Count	Duration	Avg duration
Feb 13	15	89	0ms	0ms

8

0ms

2,058

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 #8

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2,058	0ms	0ms

9

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 #9

Day	Hour	Count	Duration	Avg duration
Feb 13	15	4	0ms	0ms

10

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Feb 13	15	4	0ms	0ms

11

0ms

113

Details

0ms

select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, timegranularity as interval, direction as direction, patternendtime as patternendtime, patternstartprice as psp, patternendprice as pep, target03 as t03, target16 as t16, patternlengthbars as length, p.patternname as patternname, dtt.timezone, cps.pip from fibonacci_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 fibonaccipatterns p on a.pattern = p.patternname left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Feb 13	15	113	0ms	0ms

12

0ms

26

Details

0ms

set datestyle = iso;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Feb 13	15	26	0ms	0ms

13

0ms

2,279

Details

0ms

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

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2,279	0ms	0ms

14

0ms

10

Details

0ms

insert into resultmedia (processresultsid, type, name, filename) values (?, ?, ?, ?) returning id;

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Feb 13	15	10	0ms	0ms

15

0ms

2

Details

0ms

update "public"."processes" set "locale" = ?, "region" = ?, "schedule" = ? where "id" = ?;

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2	0ms	0ms

16

0ms

2

Details

0ms

select t.pricedatetime as pricedatetime, t.open as open, t.high as high, t.low as low, t.close "..." close, t.volume as volume, t.bsf as bsf from t1440 t where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2	0ms	0ms

17

0ms

26

Details

0ms

set client_encoding to ?;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Feb 13	15	26	0ms	0ms

18

0ms

239

Details

0ms

select v.datname, c.relname, v.phase, v.heap_blks_total, v.heap_blks_scanned, v.heap_blks_vacuumed, v.index_vacuum_count, v.max_dead_tuples, v.num_dead_tuples from pg_stat_progress_vacuum as v join pg_class c on c.oid = v.relid;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Feb 13	15	239	0ms	0ms

19

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 #19

Day	Hour	Count	Duration	Avg duration
Feb 13	15	18	0ms	0ms

20

0ms

2

Details

0ms

select distinct "public"."processes"."live" AS "live" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" order by ? asc;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Feb 13	15	2	0ms	0ms

Time consuming prepare


Date: 2026-02-13 15:31:00
Duration: 12ms
Database: postgres
Date: 2026-02-13 15:01:26
Duration: 3ms
Database: postgres
Date: 2026-02-13 15:00:44
Duration: 12ms
Database: postgres
Date: 2026-02-13 15:45:04
Duration: 1ms
Database: postgres
Date: 2026-02-13 15:31:30
Duration: 4ms
Database: postgres
Date: 2026-02-13 15:41:52
Duration: 0ms
Database: postgres
Date: 2026-02-13 15:10:57
Duration: 0ms
Database: postgres
Date: 2026-02-13 15:16:29
Duration: 0ms
Database: postgres
Date: 2026-02-13 15:31:04
Duration: 7ms
Database: postgres
Date: 2026-02-13 15:21:42
Duration: 7ms
Database: postgres
Date: 2026-02-13 15:52:05
Duration: 4ms
Database: postgres
Date: 2026-02-13 15:14:19
Duration: 0ms
Database: postgres
Date: 2026-02-13 15:00:03
Duration: 2ms
Database: postgres
Date: 2026-02-13 15:15:50
Duration: 0ms
Database: postgres
Date: 2026-02-13 15:01:28
Duration: 0ms
Database: postgres
Date: 2026-02-13 15:00:02
Duration: 3ms
Database: postgres
Date: 2026-02-13 15:50:04
Duration: 3ms
Database: postgres
Date: 2026-02-13 15:05:31
Duration: 0ms
Database: postgres
Date: 2026-02-13 15:35:25
Duration: 1ms
Database: postgres
Date: 2026-02-13 15:07:42
Duration: 1ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

29s974ms

3,734

Details

0ms

55ms

8ms

WITH rar_max as ( ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Feb 13	15	3,734	29s974ms	8ms

WITH rar_max as ( ;

Date: 2026-02-13 15:00:04 Duration: 55ms Database: postgres parameters: $1 = '607672120325526301', $2 = '607672120325526301', $3 = '607672120325526301'
WITH rar_max as ( ;

Date: 2026-02-13 15:00:04 Duration: 55ms Database: postgres parameters: $1 = '607672119920287301', $2 = '607672119920287301', $3 = '607672119920287301'
WITH rar_max as ( ;

Date: 2026-02-13 15:00:04 Duration: 52ms Database: postgres parameters: $1 = '607672058125185301', $2 = '607672058125185301', $3 = '607672058125185301'

2

12s60ms

28,105

Details

0ms

34ms

0ms

SELECT ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	15	28,105	12s60ms	0ms

SELECT ;

Date: 2026-02-13 15:00:03 Duration: 34ms Database: postgres parameters: $1 = '515840243241002300'
SELECT ;

Date: 2026-02-13 15:00:04 Duration: 27ms Database: postgres parameters: $1 = '500991628206122200'
SELECT ;

Date: 2026-02-13 15:00:04 Duration: 23ms Database: postgres parameters: $1 = '515840243263596300'

3

2s879ms

1,250

Details

1ms

10ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	15	1,250	2s879ms	2ms

SELECT symbolid, ;

Date: 2026-02-13 15:30:54 Duration: 10ms Database: postgres parameters: $1 = 'HOTFOREX', $2 = '15', $3 = 'NZDCAD', $4 = 'NZDUSD', $5 = 'EURNZD', $6 = 'LLOY', $7 = 'Coffee', $8 = 'Cocoa', $9 = 'EURCHF', $10 = 'EURDKK', $11 = 'LVMH.K', $12 = 'Mapfre.K', $13 = 'EURCAD', $14 = 'EURUSD', $15 = 'Daimler.K', $16 = 'EURNOK', $17 = 'Copper', $18 = 'HSBCL', $19 = 'GBPCAD', $20 = 'GBPUSD', $21 = 'EURGBP', $22 = 'EURPLN', $23 = 'Danone.K', $24 = 'EURJPY', $25 = 'GBPCHF', $26 = 'NETH25', $27 = 'EURHUF', $28 = 'NZDCHF', $29 = 'Palladium', $30 = 'GBPNZD', $31 = 'Iberdrola.K', $32 = 'FRA40', $33 = 'GBPJPY', $34 = 'GBPAUD', $35 = 'NZDJPY', $36 = 'GBPZAR', $37 = 'EURAUD', $38 = 'Lufthansa.K', $39 = 'JPN225'
SELECT symbolid, ;

Date: 2026-02-13 15:45:04 Duration: 7ms Database: postgres parameters: $1 = 'ATFX', $2 = '15', $3 = '#DBK'
SELECT symbolid, ;

Date: 2026-02-13 15:15:35 Duration: 7ms Database: postgres parameters: $1 = 'AXIORY', $2 = '15', $3 = 'XPTUSD', $4 = 'ZARJPY'

4

763ms

472

Details

1ms

2ms

1ms

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

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	15	472	763ms	1ms

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

Date: 2026-02-13 15:00:27 Duration: 2ms Database: postgres parameters: $1 = 'BDSWISS'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-02-13 15:15:57 Duration: 2ms Database: postgres parameters: $1 = 'HOTFOREX'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-02-13 15:47:00 Duration: 2ms Database: postgres parameters: $1 = 'FPMARKETS'

5

656ms

68

Details

0ms

22ms

9ms

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

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	15	68	656ms	9ms

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

Date: 2026-02-13 15:05:44 Duration: 22ms Database: postgres parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;

Date: 2026-02-13 15:51:29 Duration: 20ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;

Date: 2026-02-13 15:50:43 Duration: 19ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

6

514ms

21,637

Details

0ms

5ms

0ms

select 1;

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	15	21,637	514ms	0ms

select 1;

Date: 2026-02-13 15:20:30 Duration: 5ms Database: postgres
select 1;

Date: 2026-02-13 15:56:54 Duration: 4ms Database: postgres
select 1;

Date: 2026-02-13 15:21:46 Duration: 3ms Database: postgres

7

496ms

16

Details

28ms

44ms

31ms

with sym_info as ( ;

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	15	16	496ms	31ms

with sym_info as ( ;

Date: 2026-02-13 15:21:54 Duration: 44ms Database: postgres parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'
with sym_info as ( ;

Date: 2026-02-13 15:06:58 Duration: 36ms Database: postgres parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'
with sym_info as ( ;

Date: 2026-02-13 15:36:42 Duration: 36ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'

8

489ms

60

Details

4ms

13ms

8ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	15	60	489ms	8ms

WITH last_candle AS ( ;

Date: 2026-02-13 15:16:02 Duration: 13ms Database: postgres parameters: $1 = '538', $2 = '538'
WITH last_candle AS ( ;

Date: 2026-02-13 15:16:00 Duration: 12ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-02-13 15:32:00 Duration: 12ms Database: postgres parameters: $1 = '558', $2 = '558'

9

358ms

20

Details

0ms

39ms

17ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	15	20	358ms	17ms

with wh_patitioned as ( ;

Date: 2026-02-13 15:23:37 Duration: 39ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2026-02-13 15:51:01 Duration: 29ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2026-02-13 15:55:23 Duration: 28ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'

10

236ms

5,382

Details

0ms

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

Times Reported Time consuming bind #10

Day	Hour	Count	Duration	Avg duration
	15	5,382	236ms	0ms

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

Date: 2026-02-13 15:32:21 Duration: 0ms Database: postgres parameters: $1 = '2026-02-12 23:45:00', $2 = '260.79', $3 = '262.35', $4 = '260.285', $5 = '261.725', $6 = '563', $7 = '515840216708269300', $8 = '0', $9 = '2026-02-13 15:32:21.801', $10 = '2026-02-13 15:32:21.723', $11 = '260.79', $12 = '262.35', $13 = '260.285', $14 = '261.725', $15 = '563', $16 = '0', $17 = '2026-02-13 15:32:21.801', $18 = '2026-02-13 15:32:21.723'
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-13 15:17:27 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 14:45:00', $2 = '8890.4', $3 = '8895.4', $4 = '8881.5', $5 = '8884.5', $6 = '244', $7 = '515840245910095300', $8 = '0', $9 = '2026-02-13 15:17:27.227', $10 = '2026-02-13 15:17:27.153', $11 = '8890.4', $12 = '8895.4', $13 = '8881.5', $14 = '8884.5', $15 = '244', $16 = '0', $17 = '2026-02-13 15:17:27.227', $18 = '2026-02-13 15:17:27.153'
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-13 15:26:54 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 15:00:00', $2 = '49364.94', $3 = '49373.79', $4 = '49271.29', $5 = '49328.79', $6 = '6095', $7 = '515840248000537300', $8 = '0', $9 = '2026-02-13 15:26:54.716', $10 = '2026-02-13 15:26:54.644', $11 = '49364.94', $12 = '49373.79', $13 = '49271.29', $14 = '49328.79', $15 = '6095', $16 = '0', $17 = '2026-02-13 15:26:54.716', $18 = '2026-02-13 15:26:54.644'

11

233ms

3,137

Details

0ms

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

Times Reported Time consuming bind #11

Day	Hour	Count	Duration	Avg duration
	15	3,137	233ms	0ms

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

Date: 2026-02-13 15:11:53 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 14:00:00', $2 = '26381.5', $3 = '26433.9', $4 = '26372.5', $5 = '26412.8', $6 = '5850', $7 = '515840247933633300', $8 = '0', $9 = '2026-02-13 15:11:53.624', $10 = '2026-02-13 15:11:53.524', $11 = '26381.5', $12 = '26433.9', $13 = '26372.5', $14 = '26412.8', $15 = '5850', $16 = '0', $17 = '2026-02-13 15:11:53.624', $18 = '2026-02-13 15:11:53.524'
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-13 15:41:52 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 14:30:00', $2 = '26412.5', $3 = '26437.3', $4 = '26268.9', $5 = '26271.5', $6 = '8494', $7 = '515840247933633300', $8 = '0', $9 = '2026-02-13 15:41:52.442', $10 = '2026-02-13 15:41:52.351', $11 = '26412.5', $12 = '26437.3', $13 = '26268.9', $14 = '26271.5', $15 = '8494', $16 = '0', $17 = '2026-02-13 15:41:52.442', $18 = '2026-02-13 15:41:52.351'
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-13 15:41:40 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 15:00:00', $2 = '8885.4', $3 = '8919.4', $4 = '8879.4', $5 = '8906.45', $6 = '4516', $7 = '515840248015340300', $8 = '0', $9 = '2026-02-13 15:41:40.366', $10 = '2026-02-13 15:41:40.273', $11 = '8885.4', $12 = '8919.4', $13 = '8879.4', $14 = '8906.45', $15 = '4516', $16 = '0', $17 = '2026-02-13 15:41:40.366', $18 = '2026-02-13 15:41:40.273'

12

166ms

2,058

Details

0ms

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

Times Reported Time consuming bind #12

Day	Hour	Count	Duration	Avg duration
	15	2,058	166ms	0ms

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

Date: 2026-02-13 15:00:27 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 14:00:00', $2 = '0.56493', $3 = '0.565', $4 = '0.56401', $5 = '0.56418', $6 = '2449', $7 = '515840245865318300', $8 = '0', $9 = '2026-02-13 15:00:27.55', $10 = '2026-02-13 15:00:27.549', $11 = '0.56493', $12 = '0.565', $13 = '0.56401', $14 = '0.56418', $15 = '2449', $16 = '0', $17 = '2026-02-13 15:00:27.55', $18 = '2026-02-13 15:00:27.549'
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-13 15:16:02 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 14:00:00', $2 = '0.960185', $3 = '0.96135', $4 = '0.960015', $5 = '0.96102', $6 = '5914', $7 = '515840230419498300', $8 = '0', $9 = '2026-02-13 15:16:02.096', $10 = '2026-02-13 15:16:02.095', $11 = '0.960185', $12 = '0.96135', $13 = '0.960015', $14 = '0.96102', $15 = '5914', $16 = '0', $17 = '2026-02-13 15:16:02.096', $18 = '2026-02-13 15:16:02.095'
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-02-13 15:31:00 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 14:00:00', $2 = '8890.35', $3 = '8893.35', $4 = '8878.35', $5 = '8881.35', $6 = '1013', $7 = '500991628266153200', $8 = '0', $9 = '2026-02-13 15:31:00.442', $10 = '2026-02-13 15:31:00.441', $11 = '8890.35', $12 = '8893.35', $13 = '8878.35', $14 = '8881.35', $15 = '1013', $16 = '0', $17 = '2026-02-13 15:31:00.442', $18 = '2026-02-13 15:31:00.441'

13

120ms

306

Details

0ms

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

Times Reported Time consuming bind #13

Day	Hour	Count	Duration	Avg duration
	15	306	120ms	0ms

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

Date: 2026-02-13 15:14:18 Duration: 0ms Database: postgres
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2026-02-13 15:14:19 Duration: 0ms Database: postgres
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2026-02-13 15:14:18 Duration: 0ms Database: postgres

14

89ms

88

Details

0ms

1ms

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

Times Reported Time consuming bind #14

Day	Hour	Count	Duration	Avg duration
	15	88	89ms	1ms

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

Date: 2026-02-13 15:49:34 Duration: 1ms Database: postgres parameters: $1 = '667', $2 = 'XAUUSD.r', $3 = '667'
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2026-02-13 15:05:37 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'USDPLN.a', $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: 2026-02-13 15:06:29 Duration: 1ms Database: postgres parameters: $1 = '667', $2 = 'AUDCAD', $3 = '667'

15

73ms

400

Details

0ms

4ms

0ms

/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;

Times Reported Time consuming bind #15

Day	Hour	Count	Duration	Avg duration
	15	400	73ms	0ms

/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;

Date: 2026-02-13 15:50:34 Duration: 4ms Database: postgres parameters: $1 = '607672233174980301'
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;

Date: 2026-02-13 15:20:30 Duration: 4ms Database: postgres parameters: $1 = '607671822061753301'
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;

Date: 2026-02-13 15:50:32 Duration: 4ms Database: postgres parameters: $1 = '607672410491473301'

16

43ms

10

Details

3ms

6ms

4ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #16

Day	Hour	Count	Duration	Avg duration
	15	10	43ms	4ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-13 15:38:09 Duration: 6ms Database: postgres parameters: $1 = '689', $2 = '689'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-13 15:35:33 Duration: 6ms Database: postgres parameters: $1 = '689', $2 = '689'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-02-13 15:34:03 Duration: 5ms Database: postgres parameters: $1 = '538', $2 = '538'

17

39ms

111

Details

0ms

2ms

0ms

/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, 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 '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb 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 where resultuid = $1 and dtt.dayofweek = 3;

Times Reported Time consuming bind #17

Day	Hour	Count	Duration	Avg duration
	15	111	39ms	0ms

/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, 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 '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb 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 where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-02-13 15:20:56 Duration: 2ms Database: postgres parameters: $1 = '607672291365735303'
/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, 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 '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb 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 where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-02-13 15:06:31 Duration: 2ms Database: postgres parameters: $1 = '607672235914995303'
/*server.KeyLevelResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, 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 '1900-01-01' END as x3, CASE WHEN (x4 != '') THEN x4 ELSE '1900-01-01' END as x4, CASE WHEN (x5 != '') THEN x5 ELSE '1900-01-01' END as x5, CASE WHEN (x6 != '') THEN x6 ELSE '1900-01-01' END as x6, CASE WHEN (x7 != '') THEN x7 ELSE '1900-01-01' END as x7, CASE WHEN (x8 != '') THEN x8 ELSE '1900-01-01' END as x8, CASE WHEN (x9 != '') THEN x9 ELSE '1900-01-01' END as x9, errorMargin as erm, breakoutprice as pE, breakoutbars as be, breakout, atbaridentified as atBar, PatternLengthBars AS l, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz, approachingtimestamp AS apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb 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 where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-02-13 15:20:32 Duration: 2ms Database: postgres parameters: $1 = '607672238563561303'

18

34ms

8

Details

2ms

7ms

4ms

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

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	15	8	34ms	4ms

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

Date: 2026-02-13 15:14:18 Duration: 7ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'
WITH pre_symbols AS ( /* find relevant symbols */ ;

Date: 2026-02-13 15:14:18 Duration: 6ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'
WITH pre_symbols AS ( /* find relevant symbols */ ;

Date: 2026-02-13 15:14:18 Duration: 6ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'

19

32ms

54

Details

0ms

2ms

0ms

/*server.FibonacciResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, Exchange AS e, longname as lo, shortname as sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, 1 - errormargin as rq, 1 - noise as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM Fibonacci_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 fibonaccipatterns p on a.pattern = p.patternname where resultuid = $1 and dtt.dayofweek = 3;

Times Reported Time consuming bind #19

Day	Hour	Count	Duration	Avg duration
	15	54	32ms	0ms

/*server.FibonacciResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, Exchange AS e, longname as lo, shortname as sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, 1 - errormargin as rq, 1 - noise as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM Fibonacci_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 fibonaccipatterns p on a.pattern = p.patternname where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-02-13 15:20:43 Duration: 2ms Database: postgres parameters: $1 = '607672056755983302'
/*server.FibonacciResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, Exchange AS e, longname as lo, shortname as sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, 1 - errormargin as rq, 1 - noise as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM Fibonacci_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 fibonaccipatterns p on a.pattern = p.patternname where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-02-13 15:18:09 Duration: 2ms Database: postgres parameters: $1 = '607672172782154302'
/*server.FibonacciResult*/ SELECT ResultUID AS ruid, s.symbolid AS sid, symbol AS sym, Exchange AS e, longname as lo, shortname as sho, timegranularity AS tg, p.PatternID AS pid, Direction AS d, PatternStartTime AS pst, PatternEndTime AS pet, PatternStartPrice AS psp, PatternEndPrice AS pep, priceX as px, timeX as tx, priceA as pa, timeA as ta, priceB as pb, timeB as tb, priceC as pc, timeC as tc, priceD as pd, timeD as td, averagequality as aq, timequality as tq, 1 - errormargin as rq, 1 - noise as c, target10 as t10, target06 as t06, target16 as t16, target07 as t07, target12 as t12, target03 as t03, target05 as t05, PatternLengthBars AS l, temporarypattern as tp, Bandwidth AS bw, QtyTP AS qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM Fibonacci_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 fibonaccipatterns p on a.pattern = p.patternname where resultuid = $1 and dtt.dayofweek = 3;

Date: 2026-02-13 15:59:23 Duration: 2ms Database: postgres parameters: $1 = '607672353214863302'

20

31ms

88

Details

0ms

3ms

0ms

SELECT DISTINCT COALESCE(stddev_15 / 2, 0) AS low_15_stddev, COALESCE(ave_15 / 2, 0) AS low_15_ave, COALESCE(stddev_15 / 2, 0) AS high_15_stddev, COALESCE(ave_15 / 2, 0) AS high_15_ave, COALESCE(stddev_30 / 2, 0) AS low_30_stddev, COALESCE(ave_30 / 2, 0) AS low_30_ave, COALESCE(stddev_30 / 2, 0) AS high_30_stddev, COALESCE(ave_30 / 2, 0) AS high_30_ave, COALESCE(stddev_60 / 2, 0) AS low_60_stddev, COALESCE(ave_60 / 2, 0) AS low_60_ave, COALESCE(stddev_60 / 2, 0) AS high_60_stddev, COALESCE(ave_60 / 2, 0) AS high_60_ave, COALESCE(stddev_240 / 2, 0) AS low_240_stddev, COALESCE(ave_240 / 2, 0) AS low_240_ave, COALESCE(stddev_240 / 2, 0) AS high_240_stddev, COALESCE(ave_240 / 2, 0) AS high_240_ave, COALESCE(stddev_1440 / 2, 0) AS low_1440_stddev, COALESCE(ave_1440 / 2, 0) AS low_1440_ave, COALESCE(stddev_1440 / 2, 0) AS high_1440_stddev, COALESCE(ave_1440 / 2, 0) AS high_1440_ave, s.exchange AS exchange, s.symbol AS symbol, s.longname, ps.enddate AS executiondate, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, dss.downloadersymbol FROM powerstats_trumpet ps INNER JOIN downloadersymbolsettings dss ON dss.symbolid = ps.symbolid INNER JOIN datafeedstimetable dtt ON dtt.classname = dss.classname INNER JOIN symbols s ON ps.symbolid = s.symbolid WHERE ps.dayofweek = $1 AND ps.fromtime = $2 AND ps.symbolid = $3 ORDER BY ps.enddate DESC LIMIT 1;

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	15	88	31ms	0ms

SELECT DISTINCT COALESCE(stddev_15 / 2, 0) AS low_15_stddev, COALESCE(ave_15 / 2, 0) AS low_15_ave, COALESCE(stddev_15 / 2, 0) AS high_15_stddev, COALESCE(ave_15 / 2, 0) AS high_15_ave, COALESCE(stddev_30 / 2, 0) AS low_30_stddev, COALESCE(ave_30 / 2, 0) AS low_30_ave, COALESCE(stddev_30 / 2, 0) AS high_30_stddev, COALESCE(ave_30 / 2, 0) AS high_30_ave, COALESCE(stddev_60 / 2, 0) AS low_60_stddev, COALESCE(ave_60 / 2, 0) AS low_60_ave, COALESCE(stddev_60 / 2, 0) AS high_60_stddev, COALESCE(ave_60 / 2, 0) AS high_60_ave, COALESCE(stddev_240 / 2, 0) AS low_240_stddev, COALESCE(ave_240 / 2, 0) AS low_240_ave, COALESCE(stddev_240 / 2, 0) AS high_240_stddev, COALESCE(ave_240 / 2, 0) AS high_240_ave, COALESCE(stddev_1440 / 2, 0) AS low_1440_stddev, COALESCE(ave_1440 / 2, 0) AS low_1440_ave, COALESCE(stddev_1440 / 2, 0) AS high_1440_stddev, COALESCE(ave_1440 / 2, 0) AS high_1440_ave, s.exchange AS exchange, s.symbol AS symbol, s.longname, ps.enddate AS executiondate, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, dss.downloadersymbol FROM powerstats_trumpet ps INNER JOIN downloadersymbolsettings dss ON dss.symbolid = ps.symbolid INNER JOIN datafeedstimetable dtt ON dtt.classname = dss.classname INNER JOIN symbols s ON ps.symbolid = s.symbolid WHERE ps.dayofweek = $1 AND ps.fromtime = $2 AND ps.symbolid = $3 ORDER BY ps.enddate DESC LIMIT 1;

Date: 2026-02-13 15:54:41 Duration: 3ms Database: postgres parameters: $1 = '5', $2 = '930', $3 = '515840233495930300'
SELECT DISTINCT COALESCE(stddev_15 / 2, 0) AS low_15_stddev, COALESCE(ave_15 / 2, 0) AS low_15_ave, COALESCE(stddev_15 / 2, 0) AS high_15_stddev, COALESCE(ave_15 / 2, 0) AS high_15_ave, COALESCE(stddev_30 / 2, 0) AS low_30_stddev, COALESCE(ave_30 / 2, 0) AS low_30_ave, COALESCE(stddev_30 / 2, 0) AS high_30_stddev, COALESCE(ave_30 / 2, 0) AS high_30_ave, COALESCE(stddev_60 / 2, 0) AS low_60_stddev, COALESCE(ave_60 / 2, 0) AS low_60_ave, COALESCE(stddev_60 / 2, 0) AS high_60_stddev, COALESCE(ave_60 / 2, 0) AS high_60_ave, COALESCE(stddev_240 / 2, 0) AS low_240_stddev, COALESCE(ave_240 / 2, 0) AS low_240_ave, COALESCE(stddev_240 / 2, 0) AS high_240_stddev, COALESCE(ave_240 / 2, 0) AS high_240_ave, COALESCE(stddev_1440 / 2, 0) AS low_1440_stddev, COALESCE(ave_1440 / 2, 0) AS low_1440_ave, COALESCE(stddev_1440 / 2, 0) AS high_1440_stddev, COALESCE(ave_1440 / 2, 0) AS high_1440_ave, s.exchange AS exchange, s.symbol AS symbol, s.longname, ps.enddate AS executiondate, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, dss.downloadersymbol FROM powerstats_trumpet ps INNER JOIN downloadersymbolsettings dss ON dss.symbolid = ps.symbolid INNER JOIN datafeedstimetable dtt ON dtt.classname = dss.classname INNER JOIN symbols s ON ps.symbolid = s.symbolid WHERE ps.dayofweek = $1 AND ps.fromtime = $2 AND ps.symbolid = $3 ORDER BY ps.enddate DESC LIMIT 1;

Date: 2026-02-13 15:04:17 Duration: 1ms Database: postgres parameters: $1 = '5', $2 = '885', $3 = '515840233442150300'
SELECT DISTINCT COALESCE(stddev_15 / 2, 0) AS low_15_stddev, COALESCE(ave_15 / 2, 0) AS low_15_ave, COALESCE(stddev_15 / 2, 0) AS high_15_stddev, COALESCE(ave_15 / 2, 0) AS high_15_ave, COALESCE(stddev_30 / 2, 0) AS low_30_stddev, COALESCE(ave_30 / 2, 0) AS low_30_ave, COALESCE(stddev_30 / 2, 0) AS high_30_stddev, COALESCE(ave_30 / 2, 0) AS high_30_ave, COALESCE(stddev_60 / 2, 0) AS low_60_stddev, COALESCE(ave_60 / 2, 0) AS low_60_ave, COALESCE(stddev_60 / 2, 0) AS high_60_stddev, COALESCE(ave_60 / 2, 0) AS high_60_ave, COALESCE(stddev_240 / 2, 0) AS low_240_stddev, COALESCE(ave_240 / 2, 0) AS low_240_ave, COALESCE(stddev_240 / 2, 0) AS high_240_stddev, COALESCE(ave_240 / 2, 0) AS high_240_ave, COALESCE(stddev_1440 / 2, 0) AS low_1440_stddev, COALESCE(ave_1440 / 2, 0) AS low_1440_ave, COALESCE(stddev_1440 / 2, 0) AS high_1440_stddev, COALESCE(ave_1440 / 2, 0) AS high_1440_ave, s.exchange AS exchange, s.symbol AS symbol, s.longname, ps.enddate AS executiondate, dtt.absolutetimezoneoffset AS datafeedtimezoneoffset, dtt.timezone AS datafeedtimezonename, dss.downloadersymbol FROM powerstats_trumpet ps INNER JOIN downloadersymbolsettings dss ON dss.symbolid = ps.symbolid INNER JOIN datafeedstimetable dtt ON dtt.classname = dss.classname INNER JOIN symbols s ON ps.symbolid = s.symbolid WHERE ps.dayofweek = $1 AND ps.fromtime = $2 AND ps.symbolid = $3 ORDER BY ps.enddate DESC LIMIT 1;

Date: 2026-02-13 15:35:29 Duration: 1ms Database: postgres parameters: $1 = '5', $2 = '915', $3 = '515840243245614300'

Log levels

Key values

399,607 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	418	0.10%
DETAIL	93,426	23.38%
LOG	305,203	76.38%
STATEMENT	560	0.14%

Events distribution

Key values

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

Errors per 5 minutes

NO DATASET

Most Frequent Errors/Events

Key values

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

Rank	Times reported	Error
NO DATASET

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

Pages removed per tables

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