pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Tue Jan 13 08:00:06 2026
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-01-13_090000.log
Parsed 2,870,082 log entries in 1m4s
Log start from 2026-01-13 09:00:00 to 2026-01-13 09:59:08

Global Stats

305 Number of unique normalized queries
293,671 Number of queries
1h48m8s Total query duration
2026-01-13 09:00:00 First query
2026-01-13 09:59:08 Last query
5,428 queries/s at 2026-01-13 09:45:04 Query peak

1h48m8s Total query duration
8s465ms Prepare/parse total duration
53s832ms Bind total duration
1h47m6s 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

45 Total number of automatic vacuums
55 Total number of automatic analyzes

848 Number temporary file
589.83 MiB Max size of temporary file
6.80 MiB Average size of temporary file

3,575 Total number of sessions
12 sessions at 2026-01-13 09:56:13 Session peak
15d10h3m29s Total duration of sessions
6m12s Average duration of sessions
82 Average queries per session
1s815ms Average queries duration per session
6m10s Average idle time per session

3,571 Total number of connections
48 connections/s at 2026-01-13 09:05:15 Connection peak
3 Total number of databases

SQL Traffic

Key values

5,428 queries/s Query Peak
2026-01-13 09:45:04 Date

SELECT Traffic

Key values

2,658 queries/s Query Peak
2026-01-13 09:45:04 Date

INSERT/UPDATE/DELETE Traffic

Key values

176 queries/s Query Peak
2026-01-13 09:01:33 Date

Queries duration

Key values

1h48m8s Total query duration

Prepared queries ratio

Key values

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

General Activity

Day	Hour	Count	Min duration	Max duration	Avg duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Jan 13	09	293,671	0ms	42s905ms	21ms	3m51s	4m28s	5m13s

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Jan 13	09	94,268	26	0ms	0ms	0ms	0ms

Day	Hour	INSERT	UPDATE	DELETE	COPY FROM	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Jan 13	09	31,830	2,492	16	96	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Jan 13	09	24,577	115,913	4.72	17.40%

Day	Hour	Count	Average / Second
Jan 13	09	3,571	0.99/s

Day	Hour	Count	Average Duration	Average idle time
Jan 13	09	3,575	6m12s	6m10s

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Established Connections

Key values

48 connections Connection Peak
2026-01-13 09:05:15 Date

Connections per database

Key values

acaweb_fx Main Database
3,571 connections Total

Chart
Table

Database	User	Count
acaweb_fx		3,465
	postgres	3,078
	psql	387
socialmedia		106
	postgres	106

Connections per user

Key values

postgres Main User
3,571 connections Total

Chart
Table

User	Count
postgres	3,184
psql	387

Connections per host

Key values

192.168.4.142 Main host with 1257 connections
3,571 Total connections

Chart
Table

Host	Count
127.0.0.1	113
182.165.1.54	2
192.168.0.114	2
192.168.0.216	101
192.168.0.236	1
192.168.0.74	222
192.168.0.84	2
192.168.1.127	11
192.168.1.131	2
192.168.1.145	72
192.168.1.15	741
192.168.1.20	72
192.168.1.238	2
192.168.1.239	2
192.168.1.90	64
192.168.2.126	72
192.168.2.182	12
192.168.2.82	48
192.168.3.199	36
192.168.4.117	6
192.168.4.142	1,257
192.168.4.150	10
192.168.4.154	7
192.168.4.171	1
192.168.4.222	1
192.168.4.238	10
192.168.4.33	94
192.168.4.48	4
192.168.4.98	330
[local]	274

Simultaneous sessions

Key values

12 sessions Session Peak
2026-01-13 09:56:13 Date

Histogram of session times

Key values

2,847 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	2,847	79.64%
500ms-1s	172	4.81%
1s-30s	388	10.85%
30s-1m	40	1.12%
1m-10m	50	1.40%
10m-30m	44	1.23%
30m-1h	5	0.14%
1h-8h	13	0.36%
> 8h	16	0.45%

Sessions per database

Key values

acaweb_fx Main Database
3,575 sessions Total

Chart
Table

Database	User	Count	Total Duration	Average Duration
acaweb_fx	3,469	15d9h48m44s	6m23s
socialmedia	106	14m45s	8s352ms

Sessions per user

Key values

postgres Main User
3,575 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
3,575 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
127.0.0.1	113	12s74ms	106ms
182.165.1.54	2	23h17m6s	11h38m33s
192.168.0.114	2	11m18s	5m39s
192.168.0.216	101	54s652ms	541ms
192.168.0.74	224	1d17h29m43s	11m6s
192.168.0.84	2	23h59m19s	11h59m39s
192.168.1.127	11	2s709ms	246ms
192.168.1.131	2	23h59m18s	11h59m39s
192.168.1.145	72	2d19h19m16s	56m6s
192.168.1.15	742	2d14h30m41s	5m3s
192.168.1.20	74	3d10h35m15s	1h6m57s
192.168.1.238	2	23h59m27s	11h59m43s
192.168.1.239	2	12ms	6ms
192.168.1.90	64	35s621ms	556ms
192.168.2.126	72	16s979ms	235ms
192.168.2.182	12	1s46ms	87ms
192.168.2.82	48	14s513ms	302ms
192.168.3.199	36	1s420ms	39ms
192.168.4.117	6	67ms	11ms
192.168.4.142	1,257	9m37s	459ms
192.168.4.150	10	20h15m8s	2h1m30s
192.168.4.154	7	34s386ms	4s912ms
192.168.4.171	1	179ms	179ms
192.168.4.222	1	45s920ms	45s920ms
192.168.4.238	10	10s435ms	1s43ms
192.168.4.33	94	9m41s	6s187ms
192.168.4.48	4	35ms	8ms
192.168.4.98	330	17s558ms	53ms
[local]	274	3m26s	754ms

Sessions per application

Key values

unknown Main Host
3,575 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	3,575	15d10h3m29s	6m12s

Checkpoints Buffers

Key values

19,883 buffers Checkpoint Peak
2026-01-13 09:10:16 Date
209.930 seconds Highest write time
0.024 seconds Sync time

Checkpoints Wal files

Key values

10 files Wal files usage Peak
2026-01-13 09:10:16 Date

Checkpoints distance

Key values

314.88 Mo Distance Peak
2026-01-13 09:10:16 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Jan 13	09	68,876	2,017.749s	0.11s	2,018.176s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Jan 13	09	0	0	32	2,059	0.011s	0s

Day	Hour	Count	Avg time (sec)
Jan 13	09	0	0s

Day	Hour	Mean distance	Mean estimate
Jan 13	09	42,506.75 kB	108,248.58 kB

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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

589.83 MiB Temp Files size Peak
2026-01-13 09:13:53 Date

Number of temporary files

Key values

62 per second Temp Files Peak
2026-01-13 09:17:08 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Jan 13	09	848	5.63 GiB	6.80 MiB

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Queries generating the most temporary files (N)

Rank	Count	Total size	Min size	Max size	Avg size	Query
1	29	1.66 GiB	3.06 MiB	115.23 MiB	58.51 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = ? ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?; with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; Date: 2026-01-13 09:00:06 Duration: 0ms
2	25	208.70 MiB	8.34 MiB	8.36 MiB	8.35 MiB	jr.resultuid as resultuid, jr.direction as direction, jr.patternendtime as identified, jr.patternlengthbars as length, jr.patternstarttime as patternstarttime, case when jr.trendchangeid = ? then ? else ? end as trendchange, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, jp.patternname as pattern_name, dtt.timezone as timezone, ? as age, cps.pip, g.basegroupname from japsticks_results jr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = jr.symbolid inner join relevance_japsticks_results rar on rar.resultuid = jr.resultuid inner join symbols s on jr.symbolid = s.symbolid and s.nonliquid = ? inner join japsticks_patterns jp on jr.patternid = jp.id inner join downloadersymbolsettings dss on jr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where jr.gmttimefound > now() - interval ? and s.deleted = ? and (jr.simulation = ? or jr.simulation is null) and (rar.relevant = ?) --and (semicolon_age = ? or rar.age <= semicolon_age) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or jp.patternname in (...)) and (? = ? or jr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results order by symbolid, resultuid ) select * from results order by identified desc, length desc ; jr.resultuid AS resultuid, jr.direction AS direction, jr.patternendtime AS identified, jr.patternlengthbars AS length, jr.patternstarttime AS patternstarttime, case when jr.trendchangeid = 1 then 'Continuation' else 'Reversal' end AS trendchange, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, jp.patternname AS pattern_name, dtt.timezone AS timezone, 0 AS age, cps.pip, g.basegroupname FROM japsticks_results jr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = jr.symbolid INNER JOIN relevance_japsticks_results rar ON rar.resultuid = jr.resultuid INNER JOIN symbols s ON jr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN japsticks_patterns jp ON jr.patternid = jp.id INNER JOIN downloadersymbolsettings dss ON jr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE jr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (jr.simulation = 0 OR jr.simulation IS NULL) AND (rar.relevant = 1) --AND (semicolon_age = 0 OR rar.age <= semicolon_age) AND ($2 = 0 OR s.timegranularity in ($3)) AND ($4 = 0 OR s.exchange in ($5)) AND ($6 = 0 OR coalesce(bim.code, s.symbol) in ($7)) AND ($8 = 0 OR jp.patternname in ($9)) AND ($10 = 0 OR jr.patternlengthbars <= $11)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-01-13 09:00:57 Duration: 0ms
3	16	616.89 MiB	38.55 MiB	38.59 MiB	38.56 MiB	update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid; UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid; Date: 2026-01-13 09:01:14 Duration: 0ms
4	16	1.11 GiB	70.84 MiB	70.84 MiB	70.84 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid; with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; Date: 2026-01-13 09:01:18 Duration: 0ms
5	8	1013.99 MiB	126.72 MiB	126.78 MiB	126.75 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2026-01-13 09:02:18 Duration: 0ms
6	8	25.89 MiB	3.23 MiB	3.24 MiB	3.24 MiB	select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ?), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?)), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc; SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ($2 = 0 OR s.timegranularity in ($3, $4, $5, $6, $7, $8, $9)) AND ($10 = 0 OR s.exchange in ($11)) AND ($12 = 0 OR coalesce(bim.code, s.symbol) in ($13, $14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226, $227, $228, $229, $230, $231, $232, $233, $234, $235, $236, $237, $238, $239, $240, $241, $242, $243, $244, $245, $246, $247, $248, $249, $250, $251, $252, $253, $254, $255, $256, $257, $258, $259, $260, $261, $262, $263, $264, $265, $266, $267, $268, $269, $270, $271, $272, $273, $274, $275, $276, $277, $278, $279, $280, $281, $282, $283, $284, $285, $286, $287, $288, $289, $290, $291, $292, $293, $294, $295, $296, $297, $298, $299, $300, $301, $302, $303, $304, $305, $306, $307, $308, $309, $310, $311, $312, $313, $314, $315, $316, $317, $318, $319, $320, $321, $322)) AND ($323 = 0 OR ccr.patternlengthbars <= $324)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $325 OR relevant = 1) AND ($326 = 0 OR age <= $327) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2026-01-13 09:07:25 Duration: 0ms
7	4	352.34 MiB	84.79 MiB	89.22 MiB	88.08 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2026-01-13 09:02:06 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	126.78 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-13 09:47:15 ]
2	126.77 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-13 09:32:18 ]
3	126.76 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-13 09:50:33 ]
4	126.75 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-13 09:35:32 ]
5	126.75 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-13 09:02:18 ]
6	126.74 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-13 09:17:12 ]
7	126.73 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-13 09:20:33 ]
8	126.72 MiB	select updateresultsmaterializedview (); [ Date: 2026-01-13 09:05:33 ]
9	115.23 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-13 09:00:04 ]
10	95.45 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-13 09:20:06 ]
11	94.92 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-13 09:30:05 ]
12	93.17 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-13 09:30:04 ]
13	93.12 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-13 09:10:05 ]
14	92.64 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-13 09:20:04 ]
15	89.22 MiB	select updateageforrelevantresults (); [ Date: 2026-01-13 09:32:07 ]
16	89.18 MiB	select updateageforrelevantresults (); [ Date: 2026-01-13 09:47:06 ]
17	89.14 MiB	select updateageforrelevantresults (); [ Date: 2026-01-13 09:17:04 ]
18	87.79 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-13 09:50:04 ]
19	85.77 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2026-01-13 09:50:04 ]
20	84.79 MiB	select updateageforrelevantresults (); [ Date: 2026-01-13 09:02:06 ]

Vacuums / Analyzes Distribution

Key values

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

Analyzes per table

Key values

public.solr_relevance_old (17) Main table analyzed (database acaweb_fx)
55 analyzes Total

Chart
Table

Table	Number of analyzes
acaweb_fx.public.solr_relevance_old	17
acaweb_fx.pg_catalog.pg_attribute	5
acaweb_fx.public.relevance_keylevels_results	4
acaweb_fx.pg_catalog.pg_class	4
acaweb_fx.public.relevance_fibonacci_results	4
acaweb_fx.public.relevance_autochartist_results	4
acaweb_fx.public.datafeeds_latestrun	3
acaweb_fx.pg_catalog.pg_type	3
acaweb_fx.pg_catalog.pg_index	2
acaweb_fx.public.autochartist_symbolupdates	2
acaweb_fx.public.latest_t15_candle_view	2
socialmedia.public.processes	1
acaweb_fx.pg_catalog.pg_depend	1
acaweb_fx.public.latest_candle_datetime_per_receng	1
acaweb_fx.public.relevance_consecutivecandles_results	1
acaweb_fx.public.symbollatestupdatetime	1
Total	55

Vacuums per table

Key values

public.solr_relevance_old (24) Main table vacuumed on database acaweb_fx
45 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	24	15	17,198	0	99	0	0	8,624	1,822	8,105,852
acaweb_fx.public.datafeeds_latestrun	3	0	361	0	6	0	0	45	6	29,324
acaweb_fx.pg_toast.pg_toast_2619	2	2	265	0	31	0	0	179	32	144,496
acaweb_fx.public.relevance_keylevels_results	2	2	7,917	0	231	0	194	1,938	218	636,684
acaweb_fx.public.relevance_autochartist_results	2	2	6,941	0	165	2	488	1,375	151	420,167
acaweb_fx.pg_catalog.pg_class	2	2	940	0	97	0	0	312	92	488,127
acaweb_fx.public.relevance_fibonacci_results	2	2	2,603	0	42	0	98	449	28	124,218
acaweb_fx.pg_catalog.pg_index	1	1	105	0	12	0	0	28	11	83,016
acaweb_fx.pg_catalog.pg_type	1	1	131	0	20	0	0	48	14	100,886
acaweb_fx.public.autochartist_symbolupdates	1	1	24,692	0	2,920	4	38,231	6,724	5,391	2,089,954
acaweb_fx.public.solr_imports	1	1	49	0	1	0	0	6	0	833
acaweb_fx.pg_catalog.pg_statistic	1	1	1,000	0	204	0	582	466	195	718,966
acaweb_fx.pg_catalog.pg_attribute	1	1	798	0	156	0	67	365	123	760,856
acaweb_fx.public.latest_t15_candle_view	1	1	93	0	1	0	0	6	1	9,055
acaweb_fx.public.patternresultsage	1	1	328,255	0	23,927	0	60,814	49,381	23,718	102,078,046
Total	45	33	391,348	404,990	27,912	6	100,474	69,946	31,802	115,790,480

Tuples removed per table

Key values

public.patternresultsage (63316) Main table with removed tuples on database acaweb_fx
125560 tuples Total removed

Chart
Table

		Index	Tuples			Pages
Table	Vacuums	scans	removed	remain	not yet removable	removed	remain
acaweb_fx.public.patternresultsage	1	1	63,316	3,104,756	3,525	0	73,549
acaweb_fx.public.solr_relevance_old	24	15	52,192	187,860	52,875	0	4,604
acaweb_fx.public.autochartist_symbolupdates	1	1	4,901	48,149	56	0	40,691
acaweb_fx.pg_catalog.pg_attribute	1	1	1,402	10,871	137	0	264
acaweb_fx.public.relevance_keylevels_results	2	2	1,337	24,551	0	0	558
acaweb_fx.public.relevance_autochartist_results	2	2	718	17,042	0	0	760
acaweb_fx.pg_catalog.pg_statistic	1	1	550	3,712	0	0	1,194
acaweb_fx.pg_catalog.pg_class	2	2	329	3,305	7	0	300
acaweb_fx.public.relevance_fibonacci_results	2	2	284	3,220	0	0	204
acaweb_fx.public.datafeeds_latestrun	3	0	183	42	0	0	48
acaweb_fx.pg_toast.pg_toast_2619	2	2	121	341	4	0	96
acaweb_fx.pg_catalog.pg_type	1	1	93	1,449	3	0	38
acaweb_fx.public.latest_t15_candle_view	1	1	61	14	0	0	1
acaweb_fx.public.solr_imports	1	1	50	3	2	0	2
acaweb_fx.pg_catalog.pg_index	1	1	23	813	0	0	22
Total	45	33	125,560	3,406,128	56,609	0	122,331

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	23
acaweb_fx.pg_toast.pg_toast_2619	2	2	121
acaweb_fx.pg_catalog.pg_type	1	1	93
acaweb_fx.public.datafeeds_latestrun	3	0	183
acaweb_fx.public.autochartist_symbolupdates	1	1	4901
acaweb_fx.public.solr_imports	1	1	50
acaweb_fx.pg_catalog.pg_statistic	1	1	550
acaweb_fx.pg_catalog.pg_attribute	1	1	1402
acaweb_fx.public.latest_t15_candle_view	1	1	61
acaweb_fx.public.relevance_keylevels_results	2	2	1337
acaweb_fx.public.solr_relevance_old	24	15	52192
acaweb_fx.public.relevance_autochartist_results	2	2	718
acaweb_fx.pg_catalog.pg_class	2	2	329
acaweb_fx.public.patternresultsage	1	1	63316
acaweb_fx.public.relevance_fibonacci_results	2	2	284
Total	45	33	125,560

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Jan 13	09	45	55

↑ 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

94,268 Total read queries
47,003 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	94,268	32.10%
INSERT	31,830	10.84%
UPDATE	2,492	0.85%
DELETE	16	0.01%
COPY FROM	96	0.03%
COPY TO	26	0.01%
CTE	11,829	4.03%
DDL	16	0.01%
TCL	698	0.24%
CURSOR	0	0.00%
OTHERS	152,400	51.89%

Queries by database

Key values

unknown Main database
292,648 Requests
1h47m6s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	917	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	203	0ms
	select	102	0ms
	tcl	331	0ms
	update	39	0ms
socialmedia	Total	106	0ms
	others	11	0ms
	select	94	0ms
	tcl	1	0ms
unknown	Total	292,648	1h47m6s
	copy from	16	0ms
	cte	11,725	0ms
	insert	31,830	0ms
	others	5,351	0ms
	select	94,072	0ms
	tcl	366	0ms
	update	2,453	0ms

Queries by user

Key values

unknown Main user
292,648 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	1,023	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	214	0ms
	select	196	0ms
	tcl	332	0ms
	update	39	0ms
unknown	Total	292,648	1h47m6s
	copy from	16	0ms
	cte	11,725	0ms
	insert	31,830	0ms
	others	5,351	0ms
	select	94,072	0ms
	tcl	366	0ms
	update	2,453	0ms

Duration by user

Key values

1h47m6s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	1,023	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	214	0ms
	select	196	0ms
	tcl	332	0ms
	update	39	0ms
unknown	Total	292,648	1h47m6s
	copy from	16	0ms
	cte	11,725	0ms
	insert	31,830	0ms
	others	5,351	0ms
	select	94,072	0ms
	tcl	366	0ms
	update	2,453	0ms

Queries by host

Key values

unknown Main host
293,671 Requests
1h47m6s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	293,671	1h47m6s
	copy from	96	0ms
	copy to	26	0ms
	cte	11,829	0ms
	ddl	16	0ms
	delete	16	0ms
	insert	31,830	0ms
	others	5,565	0ms
	select	94,268	0ms
	tcl	698	0ms
	update	2,492	0ms

Queries by application

Key values

unknown Main application
293,284 Requests
1h47m6s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
psql	Total	387	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	4	0ms
	select	102	0ms
	update	39	0ms
unknown	Total	293,284	1h47m6s
	copy from	16	0ms
	cte	11,725	0ms
	insert	31,830	0ms
	others	5,561	0ms
	select	94,166	0ms
	tcl	698	0ms
	update	2,453	0ms

Number of cancelled queries

Key values

0 per second Cancelled query Peak
2026-01-13 09:29:01 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

106,608 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	106,608	72.60%
1-5ms	35,314	24.05%
5-10ms	2,189	1.49%
10-25ms	895	0.61%
25-50ms	316	0.22%
50-100ms	182	0.12%
100-500ms	359	0.24%
500-1000ms	115	0.08%
1000-10000ms	639	0.44%
> 10000ms	218	0.15%

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

3

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 13	09	3	0ms	0ms

2

0ms

56

Details

0ms

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

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Jan 13	09	56	0ms	0ms

3

0ms

1

Details

0ms

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

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Jan 13	09	1	0ms	0ms

4

0ms

81

Details

0ms

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

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Jan 13	09	81	0ms	0ms

5

0ms

2,276

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Jan 13	09	2,276	0ms	0ms

6

0ms

48

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Jan 13	09	48	0ms	0ms

7

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Jan 13	09	4	0ms	0ms

8

0ms

11

Details

0ms

set datestyle = iso;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Jan 13	09	11	0ms	0ms

9

0ms

11

Details

0ms

set client_encoding to ?;

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Jan 13	09	11	0ms	0ms

10

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 #10

Day	Hour	Count	Duration	Avg duration
Jan 13	09	18	0ms	0ms

11

0ms

1

Details

0ms

insert into executionlogs (executionid, status, message, details, detailtype) values (?, ?, ?, ? 's Mission Systems segment provides command, control, communication and computer, intelligence, surveillance, and reconnaissance systems; radar, electro - optical / infrared, and acoustic sensors; electronic warfare systems; advanced communications and network systems; microelectronics; navigation and positioning sensors; maritime power, propulsion, and payload launch systems; cyber solutions; and intelligence processing systems. Its Space Systems segment offers satellites, spacecraft systems, subsystems, sensors, and payloads; ground systems; missile defense systems and interceptors; and launch vehicles and related propulsion systems. Northrop Grumman Corporation was founded in ? and is based in Falls Church, Virginia. ", " Address ": " ? Fairview Park Drive, Falls Church, VA, United States, ? ", " Phone ": " ? ? ? ", " WebURL ": " https: // www.northropgrumman.com ", " LogoURL ": " https: // eodhistoricaldata.com / img / logos / US / NOC.png ", " FullTimeEmployees ": ?, " UpdatedAt ": " ? - 01 - 13 ", " MarketCapitalization ": ?, " MarketCapitalizationMln ": ?.?, " EBITDA ": ?, " PERatio ": ?.?, " PEGRatio ": ?.?, " WallStreetTargetPrice ": ?.?, " BookValue ": ?.?, " DividendShare ": ?.?, " DividendYield ": ?.?, " EarningsShare ": ?.?, " EPSEstimateCurrentYear ": ?.?, " EPSEstimateNextYear ": ?.?, " EPSEstimateNextQuarter ": ?.?, " EPSEstimateCurrentQuarter ": ?.?, " MostRecentQuarter ": " ? - 09 - 30 ", " ProfitMargin ": ?.?, " OperatingMarginTTM ": ?.?, " ReturnOnAssetsTTM ": ?.?, " ReturnOnEquityTTM ": ?.?, " RevenueTTM ": ?, " RevenuePerShareTTM ": ?.?, " QuarterlyRevenueGrowthYOY ": ?.?, " GrossProfitTTM ": ?, " DilutedEpsTTM ": ?.?, " QuarterlyEarningsGrowthYOY ": ?.? }, " ? ": { " earningsimpactid ": ?, " sample_size ": ?, " impactcompany ": " CTAS ", " impactcompany_name ": " Cintas Corporation ", " impactcompany_sector ": " Industrials ", " impactcompany_industry ": " Specialty Business Services ", " opportunities ": [ { " forecastperiod_trading_days ": ?, " id ": " delta_gt_up ", " probability ": " ? % ", " delta_gt ": ?, " delta_gt_up ": ?, " trend_direction ": ?, " delta_sign ": " > ", " mean_mov ": " ?.? ", " mean_mov_percent ": " ? % ", " icon ": " https: // acarrows.s3.eu - west - 1.amazonaws.com / arrows / up.svg " } ], " Code ": " CTAS ", " Type ": " Common Stock ", " Name ": " Cintas Corporation ", " Exchange ": " NASDAQ ", " CurrencyCode ": " USD ", " CurrencyName ": " US Dollar ", " CurrencySymbol ": " $ ", " CountryName ": " USA ", " CountryISO ": " US ", " OpenFigi ": " BBG ? H ? YXF ? ", " ISIN ": " US ? ", " LEI ": " ? QVUQTTKMTE ? G ? ", " PrimaryTicker ": " CTAS.US ", " CUSIP ": " ? ", " CIK ": " ? ", " EmployerIdNumber ": " ? - 1188630 ", " FiscalYearEnd ": " May ", " IPODate ": " ? - 08 - 19 ", " InternationalDomestic ": " Domestic ", " Sector ": " Industrials ", " Industry ": " Specialty Business Services ", " GicSector ": " Industrials ", " GicGroup ": " Commercial & Professional Services ", " GicIndustry ": " Commercial Services & Supplies ", " GicSubIndustry ": " Diversified Support Services ", " HomeCategory ": " Domestic ", " IsDelisted ": false, " Description ": " Cintas Corporation engages in the provision of corporate identity uniforms and related business services primarily in the United States, Canada, and Latin America. It operates through Uniform Rental and Facility Services, First Aid and Safety Services, and All Other segments. The company rents and services uniforms and other garments, including flame resistant clothing, mats, mops and shop towels, and other ancillary items; and provides restroom cleaning services and supplies, as well as sells uniforms. In addition, the company offers first aid and safety services, and fire protection products and services. It provides its products and services through its distribution network and local delivery routes, or local representatives to small service and manufacturing companies, as well as major corporations. The company was founded in ? and is based in Cincinnati, Ohio. Cintas Corporation was formerly a subsidiary of Cintas Corporation. ", " Address ": " ? Cintas Boulevard, Cincinnati, OH, United States, ? - 5737 ", " Phone ": " ? ? ? ", " WebURL ": " https: // www.cintas.com ", " LogoURL ": " https: // eodhistoricaldata.com / img / logos / US / CTAS.png ", " FullTimeEmployees ": ?, " UpdatedAt ": " ? - 01 - 12 ", " MarketCapitalization ": ?, " MarketCapitalizationMln ": ?.?, " EBITDA ": ?, " PERatio ": ?.?, " PEGRatio ": ?.?, " WallStreetTargetPrice ": ?.?, " BookValue ": ?.?, " DividendShare ": ?.?, " DividendYield ": ?.?, " EarningsShare ": ?.?, " EPSEstimateCurrentYear ": ?.?, " EPSEstimateNextYear ": ?.?, " EPSEstimateNextQuarter ": ?, " EPSEstimateCurrentQuarter ": ?.?, " MostRecentQuarter ": " ? - 11 - 30 ", " ProfitMargin ": ?.?, " OperatingMarginTTM ": ?.?, " ReturnOnAssetsTTM ": ?.?, " ReturnOnEquityTTM ": ?.?, " RevenueTTM ": ?, " RevenuePerShareTTM ": ?.?, " QuarterlyRevenueGrowthYOY ": ?.?, " GrossProfitTTM ": ?, " DilutedEpsTTM ": ?.?, " QuarterlyEarningsGrowthYOY ": ?.? }, " ? ": { " earningsimpactid ": ?, " sample_size ": ?, " impactcompany ": " CHRW ", " impactcompany_name ": " CH Robinson Worldwide Inc ", " impactcompany_sector ": " Industrials ", " impactcompany_industry ": " Integrated Freight & Logistics ", " opportunities ": [], " Code ": " CHRW ", " Type ": " Common Stock ", " Name ": " CH Robinson Worldwide Inc ", " Exchange ": " NASDAQ ", " CurrencyCode ": " USD ", " CurrencyName ": " US Dollar ", " CurrencySymbol ": " $ ", " CountryName ": " USA ", " CountryISO ": " US ", " OpenFigi ": " BBG ? BTCH ? ", " ISIN ": " US ? W ? ", " LEI ": " ? WNWN ? L ? OVDHA ? ", " PrimaryTicker ": " CHRW.US ", " CUSIP ": " ? W ? ", " CIK ": " ? ", " EmployerIdNumber ": " ? - 1883630 ", " FiscalYearEnd ": " December ", " IPODate ": " ? - 10 - 15 ", " InternationalDomestic ": " Domestic ", " Sector ": " Industrials ", " Industry ": " Integrated Freight & Logistics ", " GicSector ": " Industrials ", " GicGroup ": " Transportation ", " GicIndustry ": " Air Freight & Logistics ", " GicSubIndustry ": " Air Freight & Logistics ", " HomeCategory ": " Domestic ", " IsDelisted ": false, " Description ": " C.H. Robinson Worldwide, Inc., together with its subsidiaries, provides freight transportation and related logistics and supply chain services in the United States and internationally. It operates in two segments, North American Surface Transportation and Global Forwarding. The company offers transportation and logistics services, such as truckload; less than truckload transportation brokerage services, which include the shipment of single or multiple pallets of freight; intermodal transportation that comprises the shipment service of freight in containers or trailers by a combination of truck and rail; and non - vessel operating common carrier and freight forwarding services, as well as organizes air shipments and provides door - to - door services. It also provides customs brokerage services; and other logistics services, such as fee - based managed, warehousing, and other services. In addition, the company is involved in the buying, selling, and / or marketing of fresh fruits, vegetables, and other value - added perishable items under the Robinson Fresh trade name. Further, the company offers transportation management and other surface transportation services. It provides its fresh produce to grocery retailers, restaurants, produce wholesalers, and foodservice distributors through a network of independent produce growers and suppliers. The company was founded in ? and is headquartered in Eden Prairie, Minnesota. ", " Address ": " ? Charlson Road, Eden Prairie, MN, United States, ? - 5076 ", " Phone ": " ? ? ? ", " WebURL ": " https: // www.chrobinson.com ", " LogoURL ": " https: // eodhistoricaldata.com / img / logos / US / CHRW.png ", " FullTimeEmployees ": ?, " UpdatedAt ": " ? - 01 - 12 ", " MarketCapitalization ": ?, " MarketCapitalizationMln ": ?.?, " EBITDA ": ?, " PERatio ": ?.?, " PEGRatio ": ?.?, " WallStreetTargetPrice ": ?.?, " BookValue ": ?.?, " DividendShare ": ?.?, " DividendYield ": ?.?, " EarningsShare ": ?.?, " EPSEstimateCurrentYear ": ?.?, " EPSEstimateNextYear ": ?.?, " EPSEstimateNextQuarter ": ?.?, " EPSEstimateCurrentQuarter ": ?.?, " MostRecentQuarter ": " ? - 09 - 30 ", " ProfitMargin ": ?.?, " OperatingMarginTTM ": ?.?, " ReturnOnAssetsTTM ": ?.?, " ReturnOnEquityTTM ": ?.?, " RevenueTTM ": ?, " RevenuePerShareTTM ": ?.?, " QuarterlyRevenueGrowthYOY ": ?.?, " GrossProfitTTM ": ?, " DilutedEpsTTM ": ?.?, " QuarterlyEarningsGrowthYOY ": ?.? }, " ? ": { " earningsimpactid ": ?, " sample_size ": ?, " impactcompany ": " CAT ", " impactcompany_name ": " Caterpillar Inc ", " impactcompany_sector ": " Industrials ", " impactcompany_industry ": " Machinery, Tools, Heavy Vehicles, Trains & Ships ", " opportunities ": [ { " forecastperiod_trading_days ": ?, " id ": " delta_gt_up ", " probability ": " ? % ", " delta_gt ": ?, " delta_gt_up ": ?, " trend_direction ": ?, " delta_sign ": " > ", " mean_mov ": " ?.? ", " mean_mov_percent ": " ? % ", " icon ": " https: // acarrows.s3.eu - west - 1.amazonaws.com / arrows / up.svg " } ], " Code ": " CAT ", " Type ": " Common Stock ", " Name ": " Caterpillar Inc ", " Exchange ": " NYSE ", " CurrencyCode ": " USD ", " CurrencyName ": " US Dollar ", " CurrencySymbol ": " $ ", " CountryName ": " USA ", " CountryISO ": " US ", " OpenFigi ": " BBG ? BF ? K ? ", " ISIN ": " US ? ", " LEI ": " WRJR ? GS ? GTRECRRTVX ? ", " PrimaryTicker ": " CAT.US ", " CUSIP ": " ? ", " CIK ": " ? ", " EmployerIdNumber ": " ? - 0602744 ", " FiscalYearEnd ": " December ", " IPODate ": " ? - 01 - 02 ", " InternationalDomestic ": " International / Domestic ", " Sector ": " Industrials ", " Industry ": " Farm & Heavy Construction Machinery ", " GicSector ": " i[...];

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Jan 13	09	1	0ms	0ms

12

0ms

349

Details

0ms

commit;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 13	09	349	0ms	0ms

13

0ms

283

Details

0ms

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

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Jan 13	09	283	0ms	0ms

14

0ms

236

Details

0ms

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

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Jan 13	09	236	0ms	0ms

15

0ms

236

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Jan 13	09	236	0ms	0ms

16

0ms

1

Details

0ms

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

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Jan 13	09	1	0ms	0ms

17

0ms

2

Details

0ms

insert into t15 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 13	09	2	0ms	0ms

18

0ms

11

Details

0ms

select updatedatafeedslatestrun (?);

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Jan 13	09	11	0ms	0ms

19

0ms

2

Details

0ms

insert into t15 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?.?, ?, ?, ?.?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Jan 13	09	2	0ms	0ms

20

0ms

4

Details

0ms

insert into t15 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 13	09	4	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

43,677

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 13	09	43,677	0ms	0ms

2

16,464

Details

0ms

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

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Jan 13	09	16,464	0ms	0ms

3

7,927

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
Jan 13	09	7,927	0ms	0ms

4

7,795

Details

0ms

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

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Jan 13	09	7,795	0ms	0ms

5

6,712

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 #5

Day	Hour	Count	Duration	Avg duration
Jan 13	09	6,712	0ms	0ms

6

6,285

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 #6

Day	Hour	Count	Duration	Avg duration
Jan 13	09	6,285	0ms	0ms

7

5,326

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 #7

Day	Hour	Count	Duration	Avg duration
Jan 13	09	5,326	0ms	0ms

8

5,126

Details

0ms

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

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Jan 13	09	5,126	0ms	0ms

9

3,550

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Jan 13	09	3,550	0ms	0ms

10

3,055

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 #10

Day	Hour	Count	Duration	Avg duration
Jan 13	09	3,055	0ms	0ms

11

2,796

Details

0ms

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

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Jan 13	09	2,796	0ms	0ms

12

2,458

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 13	09	2,458	0ms	0ms

13

2,422

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Jan 13	09	2,422	0ms	0ms

14

2,277

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 #14

Day	Hour	Count	Duration	Avg duration
Jan 13	09	2,277	0ms	0ms

15

2,276

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 #15

Day	Hour	Count	Duration	Avg duration
Jan 13	09	2,276	0ms	0ms

16

1,953

Details

0ms

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

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Jan 13	09	1,953	0ms	0ms

17

1,848

Details

0ms

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

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 13	09	1,848	0ms	0ms

18

1,623

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 #18

Day	Hour	Count	Duration	Avg duration
Jan 13	09	1,623	0ms	0ms

19

1,110

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 #19

Day	Hour	Count	Duration	Avg duration
Jan 13	09	1,110	0ms	0ms

20

739

Details

0ms

with rar_max as ( select resultuid from relevance_fibonacci_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, 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, ? - errormargin as rq, ? - 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, 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, newlevels.filtered 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 inner join rar_max rm on ? = ? left outer join relevance_fibonacci_results rar on a.resultuid = rar.resultuid left join currencypips cps on cps.symbol = s.symbol left join lateral calc_fib_signal_filter (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
Jan 13	09	739	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

3

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Jan 13	09	3	0ms	0ms

2

0ms

56

Details

0ms

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

Times Reported Time consuming queries #2

Day	Hour	Count	Duration	Avg duration
Jan 13	09	56	0ms	0ms

3

0ms

1

Details

0ms

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

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Jan 13	09	1	0ms	0ms

4

0ms

81

Details

0ms

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

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Jan 13	09	81	0ms	0ms

5

0ms

2,276

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Jan 13	09	2,276	0ms	0ms

6

0ms

48

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Jan 13	09	48	0ms	0ms

7

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Jan 13	09	4	0ms	0ms

8

0ms

11

Details

0ms

set datestyle = iso;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Jan 13	09	11	0ms	0ms

9

0ms

11

Details

0ms

set client_encoding to ?;

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Jan 13	09	11	0ms	0ms

10

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 #10

Day	Hour	Count	Duration	Avg duration
Jan 13	09	18	0ms	0ms

11

0ms

1

Details

0ms

insert into executionlogs (executionid, status, message, details, detailtype) values (?, ?, ?, ? 's Mission Systems segment provides command, control, communication and computer, intelligence, surveillance, and reconnaissance systems; radar, electro - optical / infrared, and acoustic sensors; electronic warfare systems; advanced communications and network systems; microelectronics; navigation and positioning sensors; maritime power, propulsion, and payload launch systems; cyber solutions; and intelligence processing systems. Its Space Systems segment offers satellites, spacecraft systems, subsystems, sensors, and payloads; ground systems; missile defense systems and interceptors; and launch vehicles and related propulsion systems. Northrop Grumman Corporation was founded in ? and is based in Falls Church, Virginia. ", " Address ": " ? Fairview Park Drive, Falls Church, VA, United States, ? ", " Phone ": " ? ? ? ", " WebURL ": " https: // www.northropgrumman.com ", " LogoURL ": " https: // eodhistoricaldata.com / img / logos / US / NOC.png ", " FullTimeEmployees ": ?, " UpdatedAt ": " ? - 01 - 13 ", " MarketCapitalization ": ?, " MarketCapitalizationMln ": ?.?, " EBITDA ": ?, " PERatio ": ?.?, " PEGRatio ": ?.?, " WallStreetTargetPrice ": ?.?, " BookValue ": ?.?, " DividendShare ": ?.?, " DividendYield ": ?.?, " EarningsShare ": ?.?, " EPSEstimateCurrentYear ": ?.?, " EPSEstimateNextYear ": ?.?, " EPSEstimateNextQuarter ": ?.?, " EPSEstimateCurrentQuarter ": ?.?, " MostRecentQuarter ": " ? - 09 - 30 ", " ProfitMargin ": ?.?, " OperatingMarginTTM ": ?.?, " ReturnOnAssetsTTM ": ?.?, " ReturnOnEquityTTM ": ?.?, " RevenueTTM ": ?, " RevenuePerShareTTM ": ?.?, " QuarterlyRevenueGrowthYOY ": ?.?, " GrossProfitTTM ": ?, " DilutedEpsTTM ": ?.?, " QuarterlyEarningsGrowthYOY ": ?.? }, " ? ": { " earningsimpactid ": ?, " sample_size ": ?, " impactcompany ": " CTAS ", " impactcompany_name ": " Cintas Corporation ", " impactcompany_sector ": " Industrials ", " impactcompany_industry ": " Specialty Business Services ", " opportunities ": [ { " forecastperiod_trading_days ": ?, " id ": " delta_gt_up ", " probability ": " ? % ", " delta_gt ": ?, " delta_gt_up ": ?, " trend_direction ": ?, " delta_sign ": " > ", " mean_mov ": " ?.? ", " mean_mov_percent ": " ? % ", " icon ": " https: // acarrows.s3.eu - west - 1.amazonaws.com / arrows / up.svg " } ], " Code ": " CTAS ", " Type ": " Common Stock ", " Name ": " Cintas Corporation ", " Exchange ": " NASDAQ ", " CurrencyCode ": " USD ", " CurrencyName ": " US Dollar ", " CurrencySymbol ": " $ ", " CountryName ": " USA ", " CountryISO ": " US ", " OpenFigi ": " BBG ? H ? YXF ? ", " ISIN ": " US ? ", " LEI ": " ? QVUQTTKMTE ? G ? ", " PrimaryTicker ": " CTAS.US ", " CUSIP ": " ? ", " CIK ": " ? ", " EmployerIdNumber ": " ? - 1188630 ", " FiscalYearEnd ": " May ", " IPODate ": " ? - 08 - 19 ", " InternationalDomestic ": " Domestic ", " Sector ": " Industrials ", " Industry ": " Specialty Business Services ", " GicSector ": " Industrials ", " GicGroup ": " Commercial & Professional Services ", " GicIndustry ": " Commercial Services & Supplies ", " GicSubIndustry ": " Diversified Support Services ", " HomeCategory ": " Domestic ", " IsDelisted ": false, " Description ": " Cintas Corporation engages in the provision of corporate identity uniforms and related business services primarily in the United States, Canada, and Latin America. It operates through Uniform Rental and Facility Services, First Aid and Safety Services, and All Other segments. The company rents and services uniforms and other garments, including flame resistant clothing, mats, mops and shop towels, and other ancillary items; and provides restroom cleaning services and supplies, as well as sells uniforms. In addition, the company offers first aid and safety services, and fire protection products and services. It provides its products and services through its distribution network and local delivery routes, or local representatives to small service and manufacturing companies, as well as major corporations. The company was founded in ? and is based in Cincinnati, Ohio. Cintas Corporation was formerly a subsidiary of Cintas Corporation. ", " Address ": " ? Cintas Boulevard, Cincinnati, OH, United States, ? - 5737 ", " Phone ": " ? ? ? ", " WebURL ": " https: // www.cintas.com ", " LogoURL ": " https: // eodhistoricaldata.com / img / logos / US / CTAS.png ", " FullTimeEmployees ": ?, " UpdatedAt ": " ? - 01 - 12 ", " MarketCapitalization ": ?, " MarketCapitalizationMln ": ?.?, " EBITDA ": ?, " PERatio ": ?.?, " PEGRatio ": ?.?, " WallStreetTargetPrice ": ?.?, " BookValue ": ?.?, " DividendShare ": ?.?, " DividendYield ": ?.?, " EarningsShare ": ?.?, " EPSEstimateCurrentYear ": ?.?, " EPSEstimateNextYear ": ?.?, " EPSEstimateNextQuarter ": ?, " EPSEstimateCurrentQuarter ": ?.?, " MostRecentQuarter ": " ? - 11 - 30 ", " ProfitMargin ": ?.?, " OperatingMarginTTM ": ?.?, " ReturnOnAssetsTTM ": ?.?, " ReturnOnEquityTTM ": ?.?, " RevenueTTM ": ?, " RevenuePerShareTTM ": ?.?, " QuarterlyRevenueGrowthYOY ": ?.?, " GrossProfitTTM ": ?, " DilutedEpsTTM ": ?.?, " QuarterlyEarningsGrowthYOY ": ?.? }, " ? ": { " earningsimpactid ": ?, " sample_size ": ?, " impactcompany ": " CHRW ", " impactcompany_name ": " CH Robinson Worldwide Inc ", " impactcompany_sector ": " Industrials ", " impactcompany_industry ": " Integrated Freight & Logistics ", " opportunities ": [], " Code ": " CHRW ", " Type ": " Common Stock ", " Name ": " CH Robinson Worldwide Inc ", " Exchange ": " NASDAQ ", " CurrencyCode ": " USD ", " CurrencyName ": " US Dollar ", " CurrencySymbol ": " $ ", " CountryName ": " USA ", " CountryISO ": " US ", " OpenFigi ": " BBG ? BTCH ? ", " ISIN ": " US ? W ? ", " LEI ": " ? WNWN ? L ? OVDHA ? ", " PrimaryTicker ": " CHRW.US ", " CUSIP ": " ? W ? ", " CIK ": " ? ", " EmployerIdNumber ": " ? - 1883630 ", " FiscalYearEnd ": " December ", " IPODate ": " ? - 10 - 15 ", " InternationalDomestic ": " Domestic ", " Sector ": " Industrials ", " Industry ": " Integrated Freight & Logistics ", " GicSector ": " Industrials ", " GicGroup ": " Transportation ", " GicIndustry ": " Air Freight & Logistics ", " GicSubIndustry ": " Air Freight & Logistics ", " HomeCategory ": " Domestic ", " IsDelisted ": false, " Description ": " C.H. Robinson Worldwide, Inc., together with its subsidiaries, provides freight transportation and related logistics and supply chain services in the United States and internationally. It operates in two segments, North American Surface Transportation and Global Forwarding. The company offers transportation and logistics services, such as truckload; less than truckload transportation brokerage services, which include the shipment of single or multiple pallets of freight; intermodal transportation that comprises the shipment service of freight in containers or trailers by a combination of truck and rail; and non - vessel operating common carrier and freight forwarding services, as well as organizes air shipments and provides door - to - door services. It also provides customs brokerage services; and other logistics services, such as fee - based managed, warehousing, and other services. In addition, the company is involved in the buying, selling, and / or marketing of fresh fruits, vegetables, and other value - added perishable items under the Robinson Fresh trade name. Further, the company offers transportation management and other surface transportation services. It provides its fresh produce to grocery retailers, restaurants, produce wholesalers, and foodservice distributors through a network of independent produce growers and suppliers. The company was founded in ? and is headquartered in Eden Prairie, Minnesota. ", " Address ": " ? Charlson Road, Eden Prairie, MN, United States, ? - 5076 ", " Phone ": " ? ? ? ", " WebURL ": " https: // www.chrobinson.com ", " LogoURL ": " https: // eodhistoricaldata.com / img / logos / US / CHRW.png ", " FullTimeEmployees ": ?, " UpdatedAt ": " ? - 01 - 12 ", " MarketCapitalization ": ?, " MarketCapitalizationMln ": ?.?, " EBITDA ": ?, " PERatio ": ?.?, " PEGRatio ": ?.?, " WallStreetTargetPrice ": ?.?, " BookValue ": ?.?, " DividendShare ": ?.?, " DividendYield ": ?.?, " EarningsShare ": ?.?, " EPSEstimateCurrentYear ": ?.?, " EPSEstimateNextYear ": ?.?, " EPSEstimateNextQuarter ": ?.?, " EPSEstimateCurrentQuarter ": ?.?, " MostRecentQuarter ": " ? - 09 - 30 ", " ProfitMargin ": ?.?, " OperatingMarginTTM ": ?.?, " ReturnOnAssetsTTM ": ?.?, " ReturnOnEquityTTM ": ?.?, " RevenueTTM ": ?, " RevenuePerShareTTM ": ?.?, " QuarterlyRevenueGrowthYOY ": ?.?, " GrossProfitTTM ": ?, " DilutedEpsTTM ": ?.?, " QuarterlyEarningsGrowthYOY ": ?.? }, " ? ": { " earningsimpactid ": ?, " sample_size ": ?, " impactcompany ": " CAT ", " impactcompany_name ": " Caterpillar Inc ", " impactcompany_sector ": " Industrials ", " impactcompany_industry ": " Machinery, Tools, Heavy Vehicles, Trains & Ships ", " opportunities ": [ { " forecastperiod_trading_days ": ?, " id ": " delta_gt_up ", " probability ": " ? % ", " delta_gt ": ?, " delta_gt_up ": ?, " trend_direction ": ?, " delta_sign ": " > ", " mean_mov ": " ?.? ", " mean_mov_percent ": " ? % ", " icon ": " https: // acarrows.s3.eu - west - 1.amazonaws.com / arrows / up.svg " } ], " Code ": " CAT ", " Type ": " Common Stock ", " Name ": " Caterpillar Inc ", " Exchange ": " NYSE ", " CurrencyCode ": " USD ", " CurrencyName ": " US Dollar ", " CurrencySymbol ": " $ ", " CountryName ": " USA ", " CountryISO ": " US ", " OpenFigi ": " BBG ? BF ? K ? ", " ISIN ": " US ? ", " LEI ": " WRJR ? GS ? GTRECRRTVX ? ", " PrimaryTicker ": " CAT.US ", " CUSIP ": " ? ", " CIK ": " ? ", " EmployerIdNumber ": " ? - 0602744 ", " FiscalYearEnd ": " December ", " IPODate ": " ? - 01 - 02 ", " InternationalDomestic ": " International / Domestic ", " Sector ": " Industrials ", " Industry ": " Farm & Heavy Construction Machinery ", " GicSector ": " i[...];

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Jan 13	09	1	0ms	0ms

12

0ms

349

Details

0ms

commit;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Jan 13	09	349	0ms	0ms

13

0ms

283

Details

0ms

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

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Jan 13	09	283	0ms	0ms

14

0ms

236

Details

0ms

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

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Jan 13	09	236	0ms	0ms

15

0ms

236

Details

0ms

select system_identifier from pg_control_system ();

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Jan 13	09	236	0ms	0ms

16

0ms

1

Details

0ms

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

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Jan 13	09	1	0ms	0ms

17

0ms

2

Details

0ms

insert into t15 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Jan 13	09	2	0ms	0ms

18

0ms

11

Details

0ms

select updatedatafeedslatestrun (?);

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Jan 13	09	11	0ms	0ms

19

0ms

2

Details

0ms

insert into t15 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?.?, ?, ?, ?.?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Jan 13	09	2	0ms	0ms

20

0ms

4

Details

0ms

insert into t15 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Jan 13	09	4	0ms	0ms

Time consuming prepare


Date: 2026-01-13 09:05:10
Duration: 20ms
Database: postgres
Date: 2026-01-13 09:05:10
Duration: 14ms
Database: postgres
Date: 2026-01-13 09:46:17
Duration: 4ms
Database: postgres
Date: 2026-01-13 09:01:26
Duration: 1ms
Database: postgres
Date: 2026-01-13 09:05:15
Duration: 5ms
Database: postgres
Date: 2026-01-13 09:40:55
Duration: 0ms
Database: postgres
Date: 2026-01-13 09:15:59
Duration: 1ms
Database: postgres
Date: 2026-01-13 09:01:19
Duration: 1ms
Database: postgres
Date: 2026-01-13 09:26:57
Duration: 1ms
Database: postgres
Date: 2026-01-13 09:01:23
Duration: 0ms
Database: postgres
Date: 2026-01-13 09:10:03
Duration: 3ms
Database: postgres
Date: 2026-01-13 09:06:43
Duration: 7ms
Database: postgres
Date: 2026-01-13 09:05:15
Duration: 10ms
Database: postgres
Date: 2026-01-13 09:06:36
Duration: 4ms
Database: postgres
Date: 2026-01-13 09:13:23
Duration: 0ms
Database: postgres
Date: 2026-01-13 09:10:55
Duration: 1ms
Database: postgres
Date: 2026-01-13 09:04:35
Duration: 5ms
Database: postgres
Date: 2026-01-13 09:30:05
Duration: 3ms
Database: postgres
Date: 2026-01-13 09:00:02
Duration: 3ms
Database: postgres
Date: 2026-01-13 09:09:20
Duration: 0ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

32s648ms

10,794

Details

0ms

62ms

3ms

WITH rar_max as ( ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Jan 13	09	10,794	32s648ms	3ms

WITH rar_max as ( ;

Date: 2026-01-13 09:10:57 Duration: 62ms Database: postgres parameters: $1 = 't', $2 = '627', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '213', $14 = '#ADBE', $15 = '#ALVG', $16 = '#AMZN', $17 = '#APPL', $18 = '#BA', $19 = '#BABA', $20 = '#BAYGn', $21 = '#BMWG', $22 = '#BNPP', $23 = '#CAT', $24 = '#CBKG', $25 = '#DAIGn', $26 = '#DIS', $27 = '#EA', $28 = '#FB', $29 = '#FDX', $30 = '#GE', $31 = '#GM', $32 = '#GOOGL', $33 = '#GS', $34 = '#INTC', $35 = '#JPM', $36 = '#KO', $37 = '#META', $38 = '#MSFT', $39 = '#NFLX', $40 = '#TSLA', $41 = '#VOWG', $42 = '#WMT', $43 = '#XOM', $44 = 'AUDCAD', $45 = 'AUDCHF', $46 = 'AUDJPY', $47 = 'AUDNZD', $48 = 'AUDUSD', $49 = 'AUS_200', $50 = 'BTCEUR', $51 = 'BTCGBP', $52 = 'BTCUSD', $53 = 'CADCHF', $54 = 'CADJPY', $55 = 'CHFJPY', $56 = 'CL_BRENT', $57 = 'DASHUSD', $58 = 'EOSUSD', $59 = 'ESP_35', $60 = 'ETHEUR', $61 = 'ETHGBP', $62 = 'ETHUSD', $63 = 'EURAUD', $64 = 'EURCAD', $65 = 'EURCHF', $66 = 'EURGBP', $67 = 'EURJPY', $68 = 'EURMXN', $69 = 'EURNOK', $70 = 'EURNZD', $71 = 'EURPLN', $72 = 'EURSEK', $73 = 'EURTRY', $74 = 'EURUSD', $75 = 'EUR_50', $76 = 'FRA_40', $77 = 'GBPAUD', $78 = 'GBPCAD', $79 = 'GBPCHF', $80 = 'GBPJPY', $81 = 'GBPNZD', $82 = 'GBPUSD', $83 = 'GBPZAR', $84 = 'GBR_100', $85 = 'HKDJPY', $86 = 'HKG_50', $87 = 'IOTAUSD', $88 = 'LTCEUR', $89 = 'LTCUSD', $90 = 'NAS100', $91 = 'NEOUSD', $92 = 'NOKJPY', $93 = 'NZDCAD', $94 = 'NZDCHF', $95 = 'NZDJPY', $96 = 'NZDUSD', $97 = 'OMGUSD', $98 = 'SPX500', $99 = 'TRXUSD', $100 = 'US30', $101 = 'USDCAD', $102 = 'USDCHF', $103 = 'USDCNH', $104 = 'USDDKK', $105 = 'USDJPY', $106 = 'USDMXN', $107 = 'USDNOK', $108 = 'USDPLN', $109 = 'USDSEK', $110 = 'USDSGD', $111 = 'USDZAR', $112 = 'USOIL', $113 = 'XAGUSD', $114 = 'XAUEUR', $115 = 'XAUUSD', $116 = 'XMRUSD', $117 = 'XPTUSD', $118 = 'XRPUSD', $119 = 'ZARJPY', $120 = 'ZECUSD', $121 = 'AUDCAD', $122 = 'AUDCHF', $123 = 'AUDJPY', $124 = 'AUDNZD', $125 = 'AUDUSD', $126 = 'CADCHF', $127 = 'CADJPY', $128 = 'CHFJPY', $129 = 'EURAUD', $130 = 'EURCAD', $131 = 'EURCHF', $132 = 'EURGBP', $133 = 'EURJPY', $134 = 'EURMXN', $135 = 'EURNOK', $136 = 'EURNZD', $137 = 'EURPLN', $138 = 'EURSEK', $139 = 'EURTRY', $140 = 'EURUSD', $141 = 'GBPAUD', $142 = 'GBPCAD', $143 = 'GBPCHF', $144 = 'GBPJPY', $145 = 'GBPNZD', $146 = 'GBPUSD', $147 = 'GBPZAR', $148 = 'HKDJPY', $149 = 'NOKJPY', $150 = 'NZDCAD', $151 = 'NZDCHF', $152 = 'NZDJPY', $153 = 'NZDUSD', $154 = 'USDCAD', $155 = 'USDCHF', $156 = 'USDCNH', $157 = 'USDDKK', $158 = 'USDJPY', $159 = 'USDMXN', $160 = 'USDNOK', $161 = 'USDPLN', $162 = 'USDSEK', $163 = 'USDSGD', $164 = 'USDZAR', $165 = 'ZARJPY', $166 = 'BTCEUR', $167 = 'BTCGBP', $168 = 'BTCUSD', $169 = 'DASHUSD', $170 = 'EOSUSD', $171 = 'ETHEUR', $172 = 'ETHGBP', $173 = 'ETHUSD', $174 = 'IOTAUSD', $175 = 'LTCEUR', $176 = 'LTCUSD', $177 = 'NEOUSD', $178 = 'OMGUSD', $179 = 'TRXUSD', $180 = 'XMRUSD', $181 = 'XRPUSD', $182 = 'ZECUSD', $183 = 'XAGUSD', $184 = 'XAUEUR', $185 = 'XAUUSD', $186 = 'XPTUSD', $187 = 'CL_BRENT', $188 = 'USOIL', $189 = '#ALVG', $190 = '#BAYGn', $191 = '#BMWG', $192 = '#BNPP', $193 = '#CBKG', $194 = '#DAIGn', $195 = '#VOWG', $196 = 'AUS_200', $197 = 'ESP_35', $198 = 'EUR_50', $199 = 'FRA_40', $200 = 'GBR_100', $201 = 'HKG_50', $202 = 'NAS100', $203 = 'SPX500', $204 = 'US30', $205 = '#ADBE', $206 = '#AMZN', $207 = '#APPL', $208 = '#BA', $209 = '#BABA', $210 = '#CAT', $211 = '#DIS', $212 = '#EA', $213 = '#FB', $214 = '#FDX', $215 = '#GE', $216 = '#GM', $217 = '#GOOGL', $218 = '#GS', $219 = '#INTC', $220 = '#JPM', $221 = '#KO', $222 = '#MSFT', $223 = '#NFLX', $224 = '#TSLA', $225 = '#WMT', $226 = '#XOM', $227 = '0', $228 = '', $229 = '0', $230 = '0', $231 = '0', $232 = '700', $233 = '700', $234 = 't', $235 = '10', $236 = '10'
WITH rar_max as ( ;

Date: 2026-01-13 09:16:17 Duration: 46ms Database: postgres parameters: $1 = '627', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '213', $13 = '#ADBE', $14 = '#ALVG', $15 = '#AMZN', $16 = '#APPL', $17 = '#BA', $18 = '#BABA', $19 = '#BAYGn', $20 = '#BMWG', $21 = '#BNPP', $22 = '#CAT', $23 = '#CBKG', $24 = '#DAIGn', $25 = '#DIS', $26 = '#EA', $27 = '#FB', $28 = '#FDX', $29 = '#GE', $30 = '#GM', $31 = '#GOOGL', $32 = '#GS', $33 = '#INTC', $34 = '#JPM', $35 = '#KO', $36 = '#META', $37 = '#MSFT', $38 = '#NFLX', $39 = '#TSLA', $40 = '#VOWG', $41 = '#WMT', $42 = '#XOM', $43 = 'AUDCAD', $44 = 'AUDCHF', $45 = 'AUDJPY', $46 = 'AUDNZD', $47 = 'AUDUSD', $48 = 'AUS_200', $49 = 'BTCEUR', $50 = 'BTCGBP', $51 = 'BTCUSD', $52 = 'CADCHF', $53 = 'CADJPY', $54 = 'CHFJPY', $55 = 'CL_BRENT', $56 = 'DASHUSD', $57 = 'EOSUSD', $58 = 'ESP_35', $59 = 'ETHEUR', $60 = 'ETHGBP', $61 = 'ETHUSD', $62 = 'EURAUD', $63 = 'EURCAD', $64 = 'EURCHF', $65 = 'EURGBP', $66 = 'EURJPY', $67 = 'EURMXN', $68 = 'EURNOK', $69 = 'EURNZD', $70 = 'EURPLN', $71 = 'EURSEK', $72 = 'EURTRY', $73 = 'EURUSD', $74 = 'EUR_50', $75 = 'FRA_40', $76 = 'GBPAUD', $77 = 'GBPCAD', $78 = 'GBPCHF', $79 = 'GBPJPY', $80 = 'GBPNZD', $81 = 'GBPUSD', $82 = 'GBPZAR', $83 = 'GBR_100', $84 = 'HKDJPY', $85 = 'HKG_50', $86 = 'IOTAUSD', $87 = 'LTCEUR', $88 = 'LTCUSD', $89 = 'NAS100', $90 = 'NEOUSD', $91 = 'NOKJPY', $92 = 'NZDCAD', $93 = 'NZDCHF', $94 = 'NZDJPY', $95 = 'NZDUSD', $96 = 'OMGUSD', $97 = 'SPX500', $98 = 'TRXUSD', $99 = 'US30', $100 = 'USDCAD', $101 = 'USDCHF', $102 = 'USDCNH', $103 = 'USDDKK', $104 = 'USDJPY', $105 = 'USDMXN', $106 = 'USDNOK', $107 = 'USDPLN', $108 = 'USDSEK', $109 = 'USDSGD', $110 = 'USDZAR', $111 = 'USOIL', $112 = 'XAGUSD', $113 = 'XAUEUR', $114 = 'XAUUSD', $115 = 'XMRUSD', $116 = 'XPTUSD', $117 = 'XRPUSD', $118 = 'ZARJPY', $119 = 'ZECUSD', $120 = 'AUDCAD', $121 = 'AUDCHF', $122 = 'AUDJPY', $123 = 'AUDNZD', $124 = 'AUDUSD', $125 = 'CADCHF', $126 = 'CADJPY', $127 = 'CHFJPY', $128 = 'EURAUD', $129 = 'EURCAD', $130 = 'EURCHF', $131 = 'EURGBP', $132 = 'EURJPY', $133 = 'EURMXN', $134 = 'EURNOK', $135 = 'EURNZD', $136 = 'EURPLN', $137 = 'EURSEK', $138 = 'EURTRY', $139 = 'EURUSD', $140 = 'GBPAUD', $141 = 'GBPCAD', $142 = 'GBPCHF', $143 = 'GBPJPY', $144 = 'GBPNZD', $145 = 'GBPUSD', $146 = 'GBPZAR', $147 = 'HKDJPY', $148 = 'NOKJPY', $149 = 'NZDCAD', $150 = 'NZDCHF', $151 = 'NZDJPY', $152 = 'NZDUSD', $153 = 'USDCAD', $154 = 'USDCHF', $155 = 'USDCNH', $156 = 'USDDKK', $157 = 'USDJPY', $158 = 'USDMXN', $159 = 'USDNOK', $160 = 'USDPLN', $161 = 'USDSEK', $162 = 'USDSGD', $163 = 'USDZAR', $164 = 'ZARJPY', $165 = 'BTCEUR', $166 = 'BTCGBP', $167 = 'BTCUSD', $168 = 'DASHUSD', $169 = 'EOSUSD', $170 = 'ETHEUR', $171 = 'ETHGBP', $172 = 'ETHUSD', $173 = 'IOTAUSD', $174 = 'LTCEUR', $175 = 'LTCUSD', $176 = 'NEOUSD', $177 = 'OMGUSD', $178 = 'TRXUSD', $179 = 'XMRUSD', $180 = 'XRPUSD', $181 = 'ZECUSD', $182 = 'XAGUSD', $183 = 'XAUEUR', $184 = 'XAUUSD', $185 = 'XPTUSD', $186 = 'CL_BRENT', $187 = 'USOIL', $188 = '#ALVG', $189 = '#BAYGn', $190 = '#BMWG', $191 = '#BNPP', $192 = '#CBKG', $193 = '#DAIGn', $194 = '#VOWG', $195 = 'AUS_200', $196 = 'ESP_35', $197 = 'EUR_50', $198 = 'FRA_40', $199 = 'GBR_100', $200 = 'HKG_50', $201 = 'NAS100', $202 = 'SPX500', $203 = 'US30', $204 = '#ADBE', $205 = '#AMZN', $206 = '#APPL', $207 = '#BA', $208 = '#BABA', $209 = '#CAT', $210 = '#DIS', $211 = '#EA', $212 = '#FB', $213 = '#FDX', $214 = '#GE', $215 = '#GM', $216 = '#GOOGL', $217 = '#GS', $218 = '#INTC', $219 = '#JPM', $220 = '#KO', $221 = '#MSFT', $222 = '#NFLX', $223 = '#TSLA', $224 = '#WMT', $225 = '#XOM', $226 = '500', $227 = '500', $228 = 't', $229 = '10', $230 = '10'
WITH rar_max as ( ;

Date: 2026-01-13 09:07:16 Duration: 44ms Database: postgres parameters: $1 = 't', $2 = '667', $3 = '0', $4 = '0', $5 = '0', $6 = '', $7 = '0', $8 = '', $9 = '0', $10 = '', $11 = '0', $12 = '0', $13 = '0', $14 = '0', $15 = '0', $16 = 't', $17 = '0', $18 = '0'

2

11s381ms

29,105

Details

0ms

28ms

0ms

SELECT ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	09	29,105	11s381ms	0ms

SELECT ;

Date: 2026-01-13 09:05:15 Duration: 28ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840249425077300'
SELECT ;

Date: 2026-01-13 09:05:45 Duration: 27ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840233373828300'
SELECT ;

Date: 2026-01-13 09:05:10 Duration: 25ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '515840243249981300'

3

2s899ms

1,224

Details

0ms

17ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	09	1,224	2s899ms	2ms

SELECT symbolid, ;

Date: 2026-01-13 09:15:55 Duration: 17ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'ADAUSD'
SELECT symbolid, ;

Date: 2026-01-13 09:46:17 Duration: 6ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'GBPJPY', $4 = 'EURJPY', $5 = 'EURUSD'
SELECT symbolid, ;

Date: 2026-01-13 09:46:15 Duration: 4ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'EURJPY', $4 = 'EURJPY.ID', $5 = 'EURJPY.FX', $6 = 'EURNZD.FX'

4

1s128ms

189

Details

0ms

26ms

5ms

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

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	09	189	1s128ms	5ms

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

Date: 2026-01-13 09:00:45 Duration: 26ms Database: postgres parameters: $1 = '489', $2 = '489'
select distinct s.statsid as statsid, sy.exchange as name;

Date: 2026-01-13 09:10:54 Duration: 21ms Database: postgres parameters: $1 = '489', $2 = '489'
select distinct s.statsid as statsid, sy.exchange as name;

Date: 2026-01-13 09:00:45 Duration: 20ms Database: postgres parameters: $1 = '489', $2 = '489'

5

867ms

520

Details

1ms

2ms

1ms

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

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	09	520	867ms	1ms

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

Date: 2026-01-13 09:46:25 Duration: 2ms Database: postgres parameters: $1 = 'MILLENNIUMPF'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-01-13 09:45:40 Duration: 2ms Database: postgres parameters: $1 = 'PEPPERSTONE'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2026-01-13 09:15:50 Duration: 2ms Database: postgres parameters: $1 = 'BDSWISS'

6

727ms

43,553

Details

0ms

8ms

0ms

select 1;

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	09	43,553	727ms	0ms

select 1;

Date: 2026-01-13 09:17:03 Duration: 8ms Database: postgres
select 1;

Date: 2026-01-13 09:05:45 Duration: 3ms Database: postgres
select 1;

Date: 2026-01-13 09:05:10 Duration: 2ms Database: postgres

7

670ms

8,854

Details

0ms

5ms

0ms

select category, ;

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	09	8,854	670ms	0ms

select category, ;

Date: 2026-01-13 09:01:26 Duration: 5ms Database: postgres parameters: $1 = '606605126049202307', $2 = 'symbol', $3 = 'US30', $4 = 'US500', $5 = 'US2000', $6 = 'USTEC', $7 = 'JP225', $8 = 'UK100', $9 = 'AUS200', $10 = 'CHINA50', $11 = 'DE30', $12 = 'HK50', $13 = 'F40', $14 = 'STOXX50', $15 = 'US2000', $16 = 'IT40', $17 = 'US500', $18 = 'US30', $19 = 'USTEC', $20 = 'CHINA50', $21 = 'AUS200', $22 = 'UK100', $23 = 'JP225', $24 = 'ES35', $25 = 'DE30', $26 = 'STOXX50', $27 = 'HK50', $28 = 'F40', $29 = 'ES35', $30 = 'IT40', $31 = '606605126049202307', $32 = 'symbol', $33 = 'US30', $34 = 'US500', $35 = 'US2000', $36 = 'USTEC', $37 = 'JP225', $38 = 'UK100', $39 = 'AUS200', $40 = 'CHINA50', $41 = 'DE30', $42 = 'HK50', $43 = 'F40', $44 = 'STOXX50', $45 = 'US2000', $46 = 'IT40', $47 = 'US500', $48 = 'US30', $49 = 'USTEC', $50 = 'CHINA50', $51 = 'AUS200', $52 = 'UK100', $53 = 'JP225', $54 = 'ES35', $55 = 'DE30', $56 = 'STOXX50', $57 = 'HK50', $58 = 'F40', $59 = 'ES35', $60 = 'IT40'
select category, ;

Date: 2026-01-13 09:00:45 Duration: 1ms Database: postgres parameters: $1 = '515852059297940307', $2 = 'symbol', $3 = 'META', $4 = 'AAPL', $5 = 'GOOG', $6 = 'CISCO', $7 = 'CMCSA', $8 = 'MSFT', $9 = 'AMAZON', $10 = 'INTEL', $11 = 'BAIDU', $12 = 'NVIDIA', $13 = 'PEP', $14 = 'JD', $15 = 'NFLX', $16 = 'NTES', $17 = 'META', $18 = 'MSFT', $19 = 'AAPL', $20 = 'INTEL', $21 = 'NVIDIA', $22 = 'AMAZON', $23 = 'GOOG', $24 = 'CISCO', $25 = 'NFLX', $26 = 'JD', $27 = 'PEP', $28 = 'CMCSA', $29 = 'BAIDU', $30 = 'NTES'
select category, ;

Date: 2026-01-13 09:01:14 Duration: 1ms Database: postgres parameters: $1 = '604104683406582307', $2 = 'symbol', $3 = 'AUDJPY', $4 = 'CADJPY', $5 = 'GBPJPY', $6 = 'NZDJPY', $7 = 'CHFJPY', $8 = 'EURJPY', $9 = 'GBPAUD', $10 = 'GBPNZD', $11 = 'EURNZD', $12 = 'EURAUD', $13 = 'GBPCAD', $14 = 'EURGBP', $15 = 'EURCAD', $16 = 'GBPCAD', $17 = 'USDSGD', $18 = 'CADJPY', $19 = 'EURNZD', $20 = 'CADCHF', $21 = 'AUDNZD', $22 = 'EURCAD', $23 = 'GBPCHF', $24 = 'AUDJPY', $25 = 'NZDUSD', $26 = 'NZDJPY', $27 = 'EURCHF', $28 = 'EURJPY', $29 = 'AUDCHF', $30 = 'GBPJPY', $31 = 'GBPCHF', $32 = 'NZDCHF', $33 = 'AUDCAD', $34 = 'NZDCAD', $35 = 'NZDCAD', $36 = 'GBPAUD', $37 = 'CHFJPY', $38 = 'GBPNZD', $39 = 'EURAUD', $40 = 'USDSGD', $41 = 'AUDCAD', $42 = 'NZDUSD', $43 = 'AUDCHF', $44 = 'EURCHF', $45 = 'CADCHF', $46 = 'NZDCHF', $47 = 'AUDNZD', $48 = 'EURGBP', $49 = '604104683406582307', $50 = 'symbol', $51 = 'AUDJPY', $52 = 'CADJPY', $53 = 'GBPJPY', $54 = 'NZDJPY', $55 = 'CHFJPY', $56 = 'EURJPY', $57 = 'GBPAUD', $58 = 'GBPNZD', $59 = 'EURNZD', $60 = 'EURAUD', $61 = 'GBPCAD', $62 = 'EURGBP', $63 = 'EURCAD', $64 = 'GBPCAD', $65 = 'USDSGD', $66 = 'CADJPY', $67 = 'EURNZD', $68 = 'CADCHF', $69 = 'AUDNZD', $70 = 'EURCAD', $71 = 'GBPCHF', $72 = 'AUDJPY', $73 = 'NZDUSD', $74 = 'NZDJPY', $75 = 'EURCHF', $76 = 'EURJPY', $77 = 'AUDCHF', $78 = 'GBPJPY', $79 = 'GBPCHF', $80 = 'NZDCHF', $81 = 'AUDCAD', $82 = 'NZDCAD', $83 = 'NZDCAD', $84 = 'GBPAUD', $85 = 'CHFJPY', $86 = 'GBPNZD', $87 = 'EURAUD', $88 = 'USDSGD', $89 = 'AUDCAD', $90 = 'NZDUSD', $91 = 'AUDCHF', $92 = 'EURCHF', $93 = 'CADCHF', $94 = 'NZDCHF', $95 = 'AUDNZD', $96 = 'EURGBP'

8

592ms

24

Details

0ms

56ms

24ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	09	24	592ms	24ms

with wh_patitioned as ( ;

Date: 2026-01-13 09:04:35 Duration: 56ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2026-01-13 09:41:02 Duration: 40ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2026-01-13 09:10:01 Duration: 36ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'

9

553ms

50

Details

0ms

20ms

11ms

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

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	09	50	553ms	11ms

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

Date: 2026-01-13 09:47:05 Duration: 20ms 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: 2026-01-13 09:57:34 Duration: 19ms 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: 2026-01-13 09:31:28 Duration: 19ms Database: postgres parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

10

312ms

466

Details

0ms

1ms

0ms

SELECT absolutetimezoneoffset;

Times Reported Time consuming bind #10

Day	Hour	Count	Duration	Avg duration
	09	466	312ms	0ms

SELECT absolutetimezoneoffset;

Date: 2026-01-13 09:01:23 Duration: 1ms Database: postgres parameters: $1 = '972', $2 = 'Metals'
SELECT absolutetimezoneoffset;

Date: 2026-01-13 09:10:57 Duration: 1ms Database: postgres parameters: $1 = '538', $2 = 'Shares EU'
SELECT absolutetimezoneoffset;

Date: 2026-01-13 09:10:56 Duration: 1ms Database: postgres parameters: $1 = '538', $2 = 'Shares EU'

11

280ms

6,285

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 #11

Day	Hour	Count	Duration	Avg duration
	09	6,285	280ms	0ms

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

Date: 2026-01-13 09:16:16 Duration: 0ms Database: postgres parameters: $1 = '2026-01-13 09:00:00', $2 = '2.019485', $3 = '2.02021', $4 = '2.019295', $5 = '2.02014', $6 = '780', $7 = '515840230400034300', $8 = '0', $9 = '2026-01-13 09:16:16.494', $10 = '2026-01-13 09:16:16.209', $11 = '2.019485', $12 = '2.02021', $13 = '2.019295', $14 = '2.02014', $15 = '780', $16 = '0', $17 = '2026-01-13 09:16:16.494', $18 = '2026-01-13 09:16:16.209'
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-01-13 09:30:43 Duration: 0ms Database: postgres parameters: $1 = '2026-01-13 09:15:00', $2 = '9.17462', $3 = '9.17901', $4 = '9.1728', $5 = '9.17542', $6 = '1539', $7 = '515840243231237300', $8 = '0', $9 = '2026-01-13 09:30:43.585', $10 = '2026-01-13 09:30:43.128', $11 = '9.17462', $12 = '9.17901', $13 = '9.1728', $14 = '9.17542', $15 = '1539', $16 = '0', $17 = '2026-01-13 09:30:43.585', $18 = '2026-01-13 09:30:43.128'
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-01-13 09:46:48 Duration: 0ms Database: postgres parameters: $1 = '2026-01-13 09:30:00', $2 = '4583.86', $3 = '4587.145', $4 = '4579.695', $5 = '4580.4', $6 = '2117', $7 = '515840230628558300', $8 = '0', $9 = '2026-01-13 09:46:48.094', $10 = '2026-01-13 09:46:47.972', $11 = '4583.86', $12 = '4587.145', $13 = '4579.695', $14 = '4580.4', $15 = '2117', $16 = '0', $17 = '2026-01-13 09:46:48.095', $18 = '2026-01-13 09:46:47.972'

12

266ms

8

Details

28ms

44ms

33ms

with sym_info as ( ;

Times Reported Time consuming bind #12

Day	Hour	Count	Duration	Avg duration
	09	8	266ms	33ms

with sym_info as ( ;

Date: 2026-01-13 09:06:55 Duration: 44ms Database: postgres parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'
with sym_info as ( ;

Date: 2026-01-13 09:06:43 Duration: 42ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
with sym_info as ( ;

Date: 2026-01-13 09:36:44 Duration: 37ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'

13

266ms

39

Details

4ms

13ms

6ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #13

Day	Hour	Count	Duration	Avg duration
	09	39	266ms	6ms

WITH last_candle AS ( ;

Date: 2026-01-13 09:16:00 Duration: 13ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-01-13 09:16:00 Duration: 12ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2026-01-13 09:06:36 Duration: 12ms Database: postgres parameters: $1 = '558', $2 = '558'

14

255ms

3,550

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 #14

Day	Hour	Count	Duration	Avg duration
	09	3,550	255ms	0ms

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

Date: 2026-01-13 09:30:39 Duration: 0ms Database: postgres parameters: $1 = '2026-01-13 09:00:00', $2 = '6.97301', $3 = '6.97476', $4 = '6.97224', $5 = '6.97364', $6 = '4543', $7 = '515840245890098300', $8 = '0', $9 = '2026-01-13 09:30:39.583', $10 = '2026-01-13 09:30:39.582', $11 = '6.97301', $12 = '6.97476', $13 = '6.97224', $14 = '6.97364', $15 = '4543', $16 = '0', $17 = '2026-01-13 09:30:39.583', $18 = '2026-01-13 09:30:39.582'
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-01-13 09:31:05 Duration: 0ms Database: postgres parameters: $1 = '2026-01-13 09:00:00', $2 = '0.535105', $3 = '0.535145', $4 = '0.534655', $5 = '0.535005', $6 = '1910', $7 = '515840230422390300', $8 = '0', $9 = '2026-01-13 09:31:05.756', $10 = '2026-01-13 09:31:05.756', $11 = '0.535105', $12 = '0.535145', $13 = '0.534655', $14 = '0.535005', $15 = '1910', $16 = '0', $17 = '2026-01-13 09:31:05.756', $18 = '2026-01-13 09:31:05.756'
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-01-13 09:30:45 Duration: 0ms Database: postgres parameters: $1 = '2026-01-13 09:00:00', $2 = '3929.87', $3 = '3933.25', $4 = '3927.15', $5 = '3931.04', $6 = '7730', $7 = '515840233928148300', $8 = '0', $9 = '2026-01-13 09:30:45.351', $10 = '2026-01-13 09:30:45.351', $11 = '3929.87', $12 = '3933.25', $13 = '3927.15', $14 = '3931.04', $15 = '7730', $16 = '0', $17 = '2026-01-13 09:30:45.351', $18 = '2026-01-13 09:30:45.351'

15

177ms

2,276

Details

0ms

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

Times Reported Time consuming bind #15

Day	Hour	Count	Duration	Avg duration
	09	2,276	177ms	0ms

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

Date: 2026-01-13 09:01:59 Duration: 0ms Database: postgres parameters: $1 = '2026-01-13 09:00:00', $2 = '96793', $3 = '97038', $4 = '96267.5', $5 = '96702.5', $6 = '3160', $7 = '515840249400042300', $8 = '0', $9 = '2026-01-13 09:01:59.23', $10 = '2026-01-13 09:01:59.23', $11 = '96793', $12 = '97038', $13 = '96267.5', $14 = '96702.5', $15 = '3160', $16 = '0', $17 = '2026-01-13 09:01:59.23', $18 = '2026-01-13 09:01:59.23'
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-01-13 09:02:12 Duration: 0ms Database: postgres parameters: $1 = '2026-01-12 20:00:00', $2 = '17660.7', $3 = '17674.7', $4 = '17658.7', $5 = '17666', $6 = '933', $7 = '500991628288378200', $8 = '0', $9 = '2026-01-13 09:02:12.022', $10 = '2026-01-13 09:02:11.897', $11 = '17660.7', $12 = '17674.7', $13 = '17658.7', $14 = '17666', $15 = '933', $16 = '0', $17 = '2026-01-13 09:02:12.022', $18 = '2026-01-13 09:02:11.897'
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2026-01-13 09:11:30 Duration: 0ms Database: postgres parameters: $1 = '2026-01-12 21:00:00', $2 = '328.48', $3 = '329.45', $4 = '328.14', $5 = '328.15', $6 = '1489', $7 = '515840247899857300', $8 = '0', $9 = '2026-01-13 09:11:30.737', $10 = '2026-01-13 09:11:30.669', $11 = '328.48', $12 = '329.45', $13 = '328.14', $14 = '328.15', $15 = '1489', $16 = '0', $17 = '2026-01-13 09:11:30.737', $18 = '2026-01-13 09:11:30.669'

16

79ms

204

Details

0ms

2ms

0ms

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

Times Reported Time consuming bind #16

Day	Hour	Count	Duration	Avg duration
	09	204	79ms	0ms

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

Date: 2026-01-13 09:13:22 Duration: 2ms Database: postgres
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2026-01-13 09:13:23 Duration: 0ms Database: postgres
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2026-01-13 09:13:25 Duration: 0ms Database: postgres

17

72ms

76

Details

0ms

1ms

0ms

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 #17

Day	Hour	Count	Duration	Avg duration
	09	76	72ms	0ms

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

Date: 2026-01-13 09:00:09 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'USDSEK', $3 = '558'
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2026-01-13 09:16:12 Duration: 1ms Database: postgres parameters: $1 = '621', $2 = 'USDJPY', $3 = '621'
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2026-01-13 09:31:23 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'XAUUSD', $3 = '558'

18

64ms

12

Details

3ms

9ms

5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	09	12	64ms	5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-13 09:01:22 Duration: 9ms Database: postgres parameters: $1 = '627', $2 = '627'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-13 09:06:04 Duration: 6ms Database: postgres parameters: $1 = '667', $2 = '667'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2026-01-13 09:10:51 Duration: 6ms Database: postgres parameters: $1 = '627', $2 = '627'

19

57ms

36

Details

1ms

2ms

1ms

WITH rcr_max as ( ;

Times Reported Time consuming bind #19

Day	Hour	Count	Duration	Avg duration
	09	36	57ms	1ms

WITH rcr_max as ( ;

Date: 2026-01-13 09:09:20 Duration: 2ms Database: postgres parameters: $1 = '607493406785649305', $2 = '607493406785649305', $3 = '607493406785649305'
WITH rcr_max as ( ;

Date: 2026-01-13 09:01:31 Duration: 2ms Database: postgres parameters: $1 = '607493406785649305', $2 = '607493406785649305', $3 = '607493406785649305'
WITH rcr_max as ( ;

Date: 2026-01-13 09:06:23 Duration: 2ms Database: postgres parameters: $1 = '607495052574499305', $2 = '607495052574499305', $3 = '607495052574499305'

20

47ms

932

Details

0ms

select distinct category;

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	09	932	47ms	0ms

select distinct category;

Date: 2026-01-13 09:48:48 Duration: 0ms Database: postgres parameters: $1 = '601729875347685307', $2 = '601729875347685307'
select distinct category;

Date: 2026-01-13 09:50:05 Duration: 0ms Database: postgres parameters: $1 = '515852059305993307', $2 = '515852059305993307'
select distinct category;

Date: 2026-01-13 09:10:57 Duration: 0ms Database: postgres parameters: $1 = '601729875347685307', $2 = '601729875347685307'

Log levels

Key values

581,491 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	644	0.11%
DETAIL	134,180	23.08%
LOG	445,875	76.68%
STATEMENT	792	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

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SELECT Traffic

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INSERT/UPDATE/DELETE Traffic

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Queries duration

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Prepared queries ratio

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General Activity

Connections

Established Connections

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Connections per database

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Connections per user

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Connections per host

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Sessions

Simultaneous sessions

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Histogram of session times

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Sessions per database

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Sessions per user

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Sessions per host

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Sessions per application

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Checkpoints / Restartpoints

Checkpoints Buffers

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Checkpoints Wal files

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Checkpoints distance

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Checkpoints Activity

Checkpoint causes

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Temporary Files

Size of temporary files

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Number of temporary files

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Temporary Files Activity

Queries generating the most temporary files (N)

Queries generating the largest temporary files

Vacuums

Vacuums / Analyzes Distribution

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Analyzes per table

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Vacuums per table

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Tuples removed per table

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Pages removed per table

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Pages removed per tables

Autovacuum Activity

Locks

Locks by types

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Type of locks

Most frequent waiting queries (N)

Queries that waited the most

Queries

Queries by type

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Queries by database

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Queries by user

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