pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Fri Dec 26 21:59:51 2025
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2025-12-26_230000.log
Parsed 2,206,583 log entries in 50s
Log start from 2025-12-26 23:00:00 to 2025-12-26 23:59:49

Global Stats

230 Number of unique normalized queries
229,123 Number of queries
1h47m59s Total query duration
2025-12-26 23:00:00 First query
2025-12-26 23:59:49 Last query
3,888 queries/s at 2025-12-26 23:30:04 Query peak

1h47m59s Total query duration
16s710ms Prepare/parse total duration
1m11s Bind total duration
1h46m30s 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
58 Total number of automatic analyzes

649 Number temporary file
171.47 MiB Max size of temporary file
7.88 MiB Average size of temporary file

7,061 Total number of sessions
15 sessions at 2025-12-26 23:54:32 Session peak
2d6h41m50s Total duration of sessions
27s887ms Average duration of sessions
32 Average queries per session
917ms Average queries duration per session
26s969ms Average idle time per session

7,062 Total number of connections
54 connections/s at 2025-12-26 23:03:48 Connection peak
3 Total number of databases

SQL Traffic

Key values

3,888 queries/s Query Peak
2025-12-26 23:30:04 Date

SELECT Traffic

Key values

1,901 queries/s Query Peak
2025-12-26 23:30:04 Date

INSERT/UPDATE/DELETE Traffic

Key values

167 queries/s Query Peak
2025-12-26 23:02:50 Date

Queries duration

Key values

1h47m59s 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)
Dec 26	23	229,123	0ms	35s378ms	27ms	3m31s	4m41s	4m58s

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Dec 26	23	53,915	26	0ms	0ms	0ms	0ms

Day	Hour	INSERT	UPDATE	DELETE	COPY FROM	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Dec 26	23	37,955	2,500	16	96	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Dec 26	23	46,859	81,019	1.73	46.01%

Day	Hour	Count	Average / Second
Dec 26	23	7,062	1.96/s

Day	Hour	Count	Average Duration	Average idle time
Dec 26	23	7,061	27s887ms	26s982ms

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Established Connections

Key values

54 connections Connection Peak
2025-12-26 23:03:48 Date

Connections per database

Key values

acaweb_fx Main Database
7,062 connections Total

Chart
Table

Database	User	Count
acaweb_fx		6,972
	postgres	6,581
	psql	391
socialmedia		90
	postgres	90

Connections per user

Key values

postgres Main User
7,062 connections Total

Chart
Table

User	Count
postgres	6,671
psql	391

Connections per host

Key values

192.168.0.74 Main host with 3996 connections
7,062 Total connections

Chart
Table

Host	Count
127.0.0.1	114
192.168.0.114	1
192.168.0.216	103
192.168.0.74	3,996
192.168.1.145	15
192.168.1.15	531
192.168.1.20	39
192.168.1.239	5
192.168.1.90	25
192.168.2.126	18
192.168.2.182	24
192.168.2.82	48
192.168.3.199	36
192.168.4.142	1,375
192.168.4.150	10
192.168.4.203	1
192.168.4.238	16
192.168.4.245	4
192.168.4.28	4
192.168.4.33	90
192.168.4.98	330
[local]	277

Simultaneous sessions

Key values

15 sessions Session Peak
2025-12-26 23:54:32 Date

Histogram of session times

Key values

5,663 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	5,663	80.20%
500ms-1s	340	4.82%
1s-30s	834	11.81%
30s-1m	145	2.05%
1m-10m	28	0.40%
10m-30m	31	0.44%
30m-1h	2	0.03%
1h-8h	18	0.25%
> 8h	0	0.00%

Sessions per database

Key values

acaweb_fx Main Database
7,061 sessions Total

Chart
Table

Database	User	Count	Total Duration	Average Duration
acaweb_fx	6,972	2d6h40m31s	28s231ms
socialmedia	89	1m19s	889ms

Sessions per user

Key values

postgres Main User
7,061 sessions Total

Chart
Table

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

Sessions per host

Key values

192.168.0.74 Main Host
7,061 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
127.0.0.1	114	14s78ms	123ms
192.168.0.114	1	5m	5m
192.168.0.216	103	2m12s	1s290ms
192.168.0.74	3,996	7h34m51s	6s829ms
192.168.1.145	15	5h34m12s	22m16s
192.168.1.15	531	4h54m10s	33s240ms
192.168.1.20	39	15h43m16s	24m11s
192.168.1.239	5	28ms	5ms
192.168.1.90	25	39s734ms	1s589ms
192.168.2.126	18	5s367ms	298ms
192.168.2.182	24	2s733ms	113ms
192.168.2.82	48	17s378ms	362ms
192.168.3.199	36	1s323ms	36ms
192.168.4.142	1,375	31m54s	1s392ms
192.168.4.150	10	20h8m38s	2h51s
192.168.4.203	1	239ms	239ms
192.168.4.238	16	20s836ms	1s302ms
192.168.4.245	4	43ms	10ms
192.168.4.28	4	20s405ms	5s101ms
192.168.4.33	89	1m19s	889ms
192.168.4.98	330	17s448ms	52ms
[local]	277	3m54s	848ms

Sessions per application

Key values

unknown Main Host
7,061 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	7,061	2d6h41m50s	27s887ms

Checkpoints Buffers

Key values

86,523 buffers Checkpoint Peak
2025-12-26 23:12:00 Date
209.922 seconds Highest write time
0.083 seconds Sync time

Checkpoints Wal files

Key values

46 files Wal files usage Peak
2025-12-26 23:12:00 Date

Checkpoints distance

Key values

1,483.88 Mo Distance Peak
2025-12-26 23:12:00 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Dec 26	23	143,290	2,041.231s	0.152s	2,041.886s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Dec 26	23	0	0	72	2,175	0.082s	0s

Day	Hour	Count	Avg time (sec)
Dec 26	23	0	0s

Day	Hour	Mean distance	Mean estimate
Dec 26	23	91,174.92 kB	424,587.85 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

184.76 MiB Temp Files size Peak
2025-12-26 23:50:07 Date

Number of temporary files

Key values

30 per second Temp Files Peak
2025-12-26 23:17:17 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Dec 26	23	649	4.99 GiB	7.88 MiB

↑ Back to the top of the Temporary Files Activity table

Queries generating the most temporary files (N)

Rank	Count	Total size	Min size	Max size	Avg size	Query
1	28	1.66 GiB	11.80 MiB	148.80 MiB	60.68 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = ? ), 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: 2025-12-26 23:00:08 Duration: 0ms
2	23	147.35 MiB	6.35 MiB	6.43 MiB	6.41 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: 2025-12-26 23:00:31 Duration: 0ms
3	16	600.50 MiB	37.53 MiB	37.53 MiB	37.53 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: 2025-12-26 23:01:12 Duration: 0ms
4	16	1.11 GiB	70.74 MiB	70.75 MiB	70.75 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: 2025-12-26 23:01:15 Duration: 0ms
5	8	971.72 MiB	118.82 MiB	122.14 MiB	121.46 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2025-12-26 23:02:11 Duration: 0ms
6	4	218.05 MiB	53.94 MiB	56.19 MiB	54.51 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2025-12-26 23:02:05 Duration: 0ms
7	1	171.47 MiB	171.47 MiB	171.47 MiB	171.47 MiB	select cleanupkeylevelsresults (?, ?, ?); select cleanupkeylevelsresults (30, 10, 30); Date: 2025-12-26 23:05:03 Duration: 0ms
8	1	67.44 MiB	67.44 MiB	67.44 MiB	67.44 MiB	select cleanuppowerstatstrumpet (?, ?); select cleanuppowerstatstrumpet (21, 3); Date: 2025-12-26 23:59:04 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	171.47 MiB	select cleanupkeylevelsresults (30, 10, 30); [ Date: 2025-12-26 23:05:03 ]
2	148.80 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: 2025-12-26 23:20:05 ]
3	148.16 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: 2025-12-26 23:30:06 ]
4	135.69 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: 2025-12-26 23:10:05 ]
5	122.14 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-26 23:47:11 ]
6	122.12 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-26 23:32:14 ]
7	122.12 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-26 23:50:32 ]
8	122.11 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-26 23:35:33 ]
9	122.10 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-26 23:17:21 ]
10	122.07 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-26 23:20:34 ]
11	120.24 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-26 23:02:11 ]
12	118.82 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-26 23:05:33 ]
13	117.84 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: 2025-12-26 23:00:06 ]
14	96.16 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: 2025-12-26 23:40:04 ]
15	79.03 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: 2025-12-26 23:50:05 ]
16	77.43 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2025-12-26 23:10:07 ]
17	76.70 MiB	with rankedmt4 as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select from rankedmt4 where r = 1 ), ok_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select , row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select , row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1; [ Date: 2025-12-26 23:40:04 ]
18	72.99 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: 2025-12-26 23:00:08 ]
19	72.76 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: 2025-12-26 23:50:05 ]
20	70.75 MiB	with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid; [ Date: 2025-12-26 23:11:24 ]

Vacuums / Analyzes Distribution

Key values

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

Analyzes per table

Key values

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

Chart
Table

Table	Number of analyzes
acaweb_fx.public.solr_relevance_old	16
acaweb_fx.pg_catalog.pg_attribute	6
acaweb_fx.public.datafeeds_latestrun	4
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.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
acaweb_fx.public.relevance_consecutivecandles_results	2
acaweb_fx.public.solr_imports	1
acaweb_fx.pg_catalog.pg_depend	1
acaweb_fx.public.latest_candle_datetime_per_receng	1
acaweb_fx.public.symbollatestupdatetime	1
acaweb_fx.public.variables	1
Total	58

Vacuums per table

Key values

public.solr_relevance_old (16) 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	16	16	13,371	0	59	0	0	9,126	1,193	5,479,560
acaweb_fx.public.datafeeds_latestrun	5	0	587	0	19	0	0	59	11	66,674
acaweb_fx.pg_toast.pg_toast_2619	2	2	349	0	71	0	0	228	65	275,616
acaweb_fx.public.autochartist_symbolupdates	2	2	55,129	0	6,414	0	73,066	18,532	6,106	3,633,338
acaweb_fx.pg_catalog.pg_attribute	2	2	1,594	0	360	0	134	734	283	1,657,029
acaweb_fx.public.relevance_keylevels_results	2	2	7,870	0	432	2	152	2,443	414	1,052,014
acaweb_fx.pg_catalog.pg_class	2	2	920	0	101	0	0	299	93	508,538
acaweb_fx.public.relevance_fibonacci_results	2	2	2,655	0	103	2	90	579	90	209,700
acaweb_fx.pg_catalog.pg_statistic	2	2	1,969	0	281	0	1,164	874	235	995,270
acaweb_fx.public.relevance_autochartist_results	2	2	7,041	0	306	0	464	1,717	290	701,811
acaweb_fx.pg_catalog.pg_index	1	1	88	0	11	0	0	26	10	74,934
acaweb_fx.public.solr_imports	1	1	52	0	3	0	0	6	2	15,945
acaweb_fx.public.patternresultsrelevance	1	1	591,937	0	69,786	0	78,118	175,404	66,143	260,927,032
acaweb_fx.public.latest_t15_candle_view	1	1	66	0	1	0	0	6	1	9,085
acaweb_fx.pg_catalog.pg_type	1	1	130	0	21	0	0	49	16	110,846
acaweb_fx.public.relevance_consecutivecandles_results	1	1	73	0	10	1	0	17	5	30,689
acaweb_fx.public.symbollatestupdatetime	1	0	1,435	0	404	0	561	1,217	403	1,064,488
acaweb_fx.public.variables	1	1	307	0	1	0	0	224	2	42,240
Total	45	39	685,573	649,855	78,383	5	153,749	211,540	75,362	276,854,809

Tuples removed per table

Key values

public.patternresultsrelevance (98708) Main table with removed tuples on database acaweb_fx
190260 tuples Total removed

Chart
Table

		Index	Tuples			Pages
Table	Vacuums	scans	removed	remain	not yet removable	removed	remain
acaweb_fx.public.patternresultsrelevance	1	1	98,708	2,727,824	0	0	137,350
acaweb_fx.public.solr_relevance_old	16	16	40,041	94,261	0	0	3,297
acaweb_fx.public.symbollatestupdatetime	1	0	18,565	88,062	10	0	1,714
acaweb_fx.public.autochartist_symbolupdates	2	2	13,614	123,954	121	0	81,382
acaweb_fx.public.variables	1	1	7,847	2	0	0	74
acaweb_fx.public.relevance_keylevels_results	2	2	3,545	25,515	0	0	558
acaweb_fx.pg_catalog.pg_attribute	2	2	2,998	21,722	0	39	480
acaweb_fx.public.relevance_autochartist_results	2	2	2,026	17,975	0	0	760
acaweb_fx.pg_catalog.pg_statistic	2	2	1,347	7,416	0	0	2,388
acaweb_fx.public.relevance_fibonacci_results	2	2	612	3,264	0	0	204
acaweb_fx.pg_catalog.pg_class	2	2	297	3,298	0	0	300
acaweb_fx.public.datafeeds_latestrun	5	0	257	103	33	0	80
acaweb_fx.pg_toast.pg_toast_2619	2	2	148	340	0	0	102
acaweb_fx.pg_catalog.pg_type	1	1	82	1,446	0	0	38
acaweb_fx.public.latest_t15_candle_view	1	1	66	14	0	0	1
acaweb_fx.public.solr_imports	1	1	52	1	0	0	2
acaweb_fx.public.relevance_consecutivecandles_results	1	1	42	300	0	0	7
acaweb_fx.pg_catalog.pg_index	1	1	13	813	0	0	22
Total	45	39	190,260	3,116,310	164	39	228,759

Pages removed per table

Key values

pg_catalog.pg_attribute (39) Main table with removed pages on database acaweb_fx
39 pages Total removed

Chart
Table

Table	Number of vacuums	Index scans	Tuples removed	Pages removed
acaweb_fx.pg_catalog.pg_attribute	2	2	2998	39
acaweb_fx.pg_catalog.pg_index	1	1	13	0
acaweb_fx.pg_toast.pg_toast_2619	2	2	148	0
acaweb_fx.public.autochartist_symbolupdates	2	2	13614	0
acaweb_fx.public.datafeeds_latestrun	5	0	257	0
acaweb_fx.public.solr_imports	1	1	52	0
acaweb_fx.public.patternresultsrelevance	1	1	98708	0
acaweb_fx.public.latest_t15_candle_view	1	1	66	0
acaweb_fx.public.relevance_keylevels_results	2	2	3545	0
acaweb_fx.pg_catalog.pg_class	2	2	297	0
acaweb_fx.public.relevance_fibonacci_results	2	2	612	0
acaweb_fx.pg_catalog.pg_type	1	1	82	0
acaweb_fx.pg_catalog.pg_statistic	2	2	1347	0
acaweb_fx.public.relevance_consecutivecandles_results	1	1	42	0
acaweb_fx.public.symbollatestupdatetime	1	0	18565	0
acaweb_fx.public.variables	1	1	7847	0
acaweb_fx.public.relevance_autochartist_results	2	2	2026	0
acaweb_fx.public.solr_relevance_old	16	16	40041	0
Total	45	39	190,260	39

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Dec 26	23	45	58

↑ 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

53,915 Total read queries
47,935 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	53,915	23.53%
INSERT	37,955	16.57%
UPDATE	2,500	1.09%
DELETE	16	0.01%
COPY FROM	96	0.04%
COPY TO	26	0.01%
CTE	6,664	2.91%
DDL	16	0.01%
TCL	662	0.29%
CURSOR	0	0.00%
OTHERS	127,273	55.55%

Queries by database

Key values

unknown Main database
228,095 Requests
1h46m30s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	938	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	220	0ms
	select	105	0ms
	tcl	331	0ms
	update	40	0ms
socialmedia	Total	90	0ms
	select	90	0ms
unknown	Total	228,095	1h46m30s
	copy from	16	0ms
	cte	6,560	0ms
	insert	37,955	0ms
	others	12,492	0ms
	select	53,720	0ms
	tcl	331	0ms
	update	2,460	0ms

Queries by user

Key values

unknown Main user
228,095 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	1,028	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	220	0ms
	select	195	0ms
	tcl	331	0ms
	update	40	0ms
unknown	Total	228,095	1h46m30s
	copy from	16	0ms
	cte	6,560	0ms
	insert	37,955	0ms
	others	12,492	0ms
	select	53,720	0ms
	tcl	331	0ms
	update	2,460	0ms

Duration by user

Key values

1h46m30s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	1,028	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	220	0ms
	select	195	0ms
	tcl	331	0ms
	update	40	0ms
unknown	Total	228,095	1h46m30s
	copy from	16	0ms
	cte	6,560	0ms
	insert	37,955	0ms
	others	12,492	0ms
	select	53,720	0ms
	tcl	331	0ms
	update	2,460	0ms

Queries by host

Key values

unknown Main host
229,123 Requests
1h46m30s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	229,123	1h46m30s
	copy from	96	0ms
	copy to	26	0ms
	cte	6,664	0ms
	ddl	16	0ms
	delete	16	0ms
	insert	37,955	0ms
	others	12,712	0ms
	select	53,915	0ms
	tcl	662	0ms
	update	2,500	0ms

Queries by application

Key values

unknown Main application
228,732 Requests
1h46m30s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
psql	Total	391	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	4	0ms
	select	105	0ms
	update	40	0ms
unknown	Total	228,732	1h46m30s
	copy from	16	0ms
	cte	6,560	0ms
	insert	37,955	0ms
	others	12,708	0ms
	select	53,810	0ms
	tcl	662	0ms
	update	2,460	0ms

Number of cancelled queries

Key values

0 per second Cancelled query Peak
2025-12-26 23:12:01 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

74,899 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	74,899	65.38%
1-5ms	34,133	29.79%
5-10ms	2,322	2.03%
10-25ms	832	0.73%
25-50ms	315	0.27%
50-100ms	182	0.16%
100-500ms	619	0.54%
500-1000ms	100	0.09%
1000-10000ms	1,038	0.91%
> 10000ms	121	0.11%

Slowest individual queries

Rank	Duration	Query
NO DATASET

Time consuming queries

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

0ms

2

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Dec 26	23	2	0ms	0ms

2

0ms

30

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
Dec 26	23	30	0ms	0ms

3

0ms

300

Details

0ms

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

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Dec 26	23	300	0ms	0ms

4

0ms

3,375

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 #4

Day	Hour	Count	Duration	Avg duration
Dec 26	23	3,375	0ms	0ms

5

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Dec 26	23	4	0ms	0ms

6

0ms

60

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Dec 26	23	60	0ms	0ms

7

0ms

1,893

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Dec 26	23	1,893	0ms	0ms

8

0ms

6

Details

0ms

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

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Dec 26	23	6	0ms	0ms

9

0ms

18

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Dec 26	23	18	0ms	0ms

10

0ms

239

Details

0ms

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

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Dec 26	23	239	0ms	0ms

11

0ms

33

Details

0ms

select * from ( select pricedatetime, open, high, low, close, volume, bsf from t60 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Dec 26	23	33	0ms	0ms

12

0ms

331

Details

0ms

commit;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Dec 26	23	331	0ms	0ms

13

0ms

2

Details

0ms

with pre_symbols as ( select s.symbolid, s.symbol, s.timegranularity, dss.downloadersymbol, dtt.timezone, s.exchange, s.longname 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 and brokerid = ? where dss.classname in (...) and (dss.downloadersymbol in (...) or s.symbol in (...)) and dss.enabled = ? and s.nonliquid = ? and s.deleted = ? ), report_symbols as ( select ps1.*, ps2.symbolid as price_symbol_id from pre_symbols ps1 inner join pre_symbols ps2 on ps1.symbol = ps2.symbol and ps1.downloadersymbol = ps2.downloadersymbol and ps2.timegranularity = ? ), rbr_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ) select bmr.resultuid as ruid, ? as direction, rs.symbol as sym, rs.downloadersymbol, rs.symbolid as sid, rs.timegranularity as tg, rs.timezone, rs.exchange as e, rs.longname, bmr.patternendtime as pet, lpi.latestpricedatetime as lpdt, bmr.patternlengthbars as l, bmr.breakout >= ? as complete, rbr.age as age from bigmovement_results bmr inner join report_symbols rs on rs.symbolid = bmr.symbolid inner join autochartist_symbolupdates lpi on lpi.symbolid = rs.price_symbol_id inner join rbr_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid where patternendtime >= (now() - ? * interval ?) -- results can't be more than ? days old and (bmr.resultuid > rm.resultuid or rbr.relevant = ?) ;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Dec 26	23	2	0ms	0ms

14

0ms

15

Details

0ms

select psd.symbolid, psd.hourlysymbolid as intervalsymbolid, s.symbol, dtt.timezone, dtt.absolutetimezoneoffset, psh.hour as index, psh.ave, psh.stddev, ((psh.ave - psh.stddev) / ?.?) as low, ((psh.ave + psh.stddev) / ?.?) as high, ee.timezone as exchangetimezone, ee.mon_t1start as exchangestart, ee.mon_t1end as exchangeend from powerstats_symboldata psd inner join powerstats_hourly psh on psd.hourlysymbolid = psh.symbolid inner join symbols s on psh.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join mat_ps_hourly_symbolid_max_enddate e on psh.enddate = e.enddate and psh.symbolid = e.symbolid inner join exchanges ee on ee.exchange = s.exchange where psd.symbolid = ? and dtt.dayofweek = ? order by hour asc;

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Dec 26	23	15	0ms	0ms

15

0ms

421

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 #15

Day	Hour	Count	Duration	Avg duration
Dec 26	23	421	0ms	0ms

16

0ms

2

Details

0ms

select (cast(substring(tz.gmoffset from ? for ?) as float) * ? + cast(substring(tz.gmoffset from ? for ?) as float)) / ? as offset from timezones tz where tz.timezone = ?;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Dec 26	23	2	0ms	0ms

17

0ms

239

Details

0ms

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

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Dec 26	23	239	0ms	0ms

18

0ms

51

Details

0ms

select * from ( select pricedatetime, open, high, low, close, volume, bsf from t30 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Dec 26	23	51	0ms	0ms

19

0ms

6

Details

0ms

select pid, datname, client_addr from pg_stat_activity where query ilike ? and pid <> pg_backend_pid() and state = ? and datname = ?;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Dec 26	23	6	0ms	0ms

20

0ms

30

Details

0ms

update executions set isrunning = false, has_results = false, response = ? where id = ?;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Dec 26	23	30	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

22,325

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Dec 26	23	22,325	0ms	0ms

2

14,457

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
Dec 26	23	14,457	0ms	0ms

3

8,308

Details

0ms

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

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Dec 26	23	8,308	0ms	0ms

4

6,818

Details

0ms

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

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Dec 26	23	6,818	0ms	0ms

5

6,416

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Dec 26	23	6,416	0ms	0ms

6

6,022

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Dec 26	23	6,022	0ms	0ms

7

6,003

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Dec 26	23	6,003	0ms	0ms

8

4,207

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 #8

Day	Hour	Count	Duration	Avg duration
Dec 26	23	4,207	0ms	0ms

9

4,116

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 #9

Day	Hour	Count	Duration	Avg duration
Dec 26	23	4,116	0ms	0ms

10

3,375

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 #10

Day	Hour	Count	Duration	Avg duration
Dec 26	23	3,375	0ms	0ms

11

3,254

Details

0ms

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

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Dec 26	23	3,254	0ms	0ms

12

2,980

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 #12

Day	Hour	Count	Duration	Avg duration
Dec 26	23	2,980	0ms	0ms

13

2,881

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 #13

Day	Hour	Count	Duration	Avg duration
Dec 26	23	2,881	0ms	0ms

14

1,893

Details

0ms

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

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Dec 26	23	1,893	0ms	0ms

15

1,226

Details

0ms

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

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Dec 26	23	1,226	0ms	0ms

16

1,144

Details

0ms

insert into t240 (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 #16

Day	Hour	Count	Duration	Avg duration
Dec 26	23	1,144	0ms	0ms

17

1,073

Details

0ms

select t.pricedatetime, t.open, t.high, t.low, t.close, t.volume, t.symbolid, dss.downloadersymbol as symbol, dss.classname as datafeed, t.bsf, t.sastdatetimewritten, t.sastdatetimereceived from t15 t inner join downloadersymbolsettings dss on t.symbolid = dss.symbolid where dss.classname = ? and dss.downloadersymbol in (...) and dss.downloadfrequency = ? and t.pricedatetime between ?::timestamp and ?::timestamp order by t.pricedatetime;

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Dec 26	23	1,073	0ms	0ms

18

695

Details

0ms

select downloadersymbol, spike_threshold from price_datafeed_spike_threshold where classname = ?;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Dec 26	23	695	0ms	0ms

19

695

Details

0ms

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

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Dec 26	23	695	0ms	0ms

20

691

Details

0ms

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

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Dec 26	23	691	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

2

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Dec 26	23	2	0ms	0ms

2

0ms

30

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
Dec 26	23	30	0ms	0ms

3

0ms

300

Details

0ms

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

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Dec 26	23	300	0ms	0ms

4

0ms

3,375

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 #4

Day	Hour	Count	Duration	Avg duration
Dec 26	23	3,375	0ms	0ms

5

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Dec 26	23	4	0ms	0ms

6

0ms

60

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Dec 26	23	60	0ms	0ms

7

0ms

1,893

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Dec 26	23	1,893	0ms	0ms

8

0ms

6

Details

0ms

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

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Dec 26	23	6	0ms	0ms

9

0ms

18

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Dec 26	23	18	0ms	0ms

10

0ms

239

Details

0ms

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

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Dec 26	23	239	0ms	0ms

11

0ms

33

Details

0ms

select * from ( select pricedatetime, open, high, low, close, volume, bsf from t60 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Dec 26	23	33	0ms	0ms

12

0ms

331

Details

0ms

commit;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Dec 26	23	331	0ms	0ms

13

0ms

2

Details

0ms

with pre_symbols as ( select s.symbolid, s.symbol, s.timegranularity, dss.downloadersymbol, dtt.timezone, s.exchange, s.longname 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 and brokerid = ? where dss.classname in (...) and (dss.downloadersymbol in (...) or s.symbol in (...)) and dss.enabled = ? and s.nonliquid = ? and s.deleted = ? ), report_symbols as ( select ps1.*, ps2.symbolid as price_symbol_id from pre_symbols ps1 inner join pre_symbols ps2 on ps1.symbol = ps2.symbol and ps1.downloadersymbol = ps2.downloadersymbol and ps2.timegranularity = ? ), rbr_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ) select bmr.resultuid as ruid, ? as direction, rs.symbol as sym, rs.downloadersymbol, rs.symbolid as sid, rs.timegranularity as tg, rs.timezone, rs.exchange as e, rs.longname, bmr.patternendtime as pet, lpi.latestpricedatetime as lpdt, bmr.patternlengthbars as l, bmr.breakout >= ? as complete, rbr.age as age from bigmovement_results bmr inner join report_symbols rs on rs.symbolid = bmr.symbolid inner join autochartist_symbolupdates lpi on lpi.symbolid = rs.price_symbol_id inner join rbr_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid where patternendtime >= (now() - ? * interval ?) -- results can't be more than ? days old and (bmr.resultuid > rm.resultuid or rbr.relevant = ?) ;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Dec 26	23	2	0ms	0ms

14

0ms

15

Details

0ms

select psd.symbolid, psd.hourlysymbolid as intervalsymbolid, s.symbol, dtt.timezone, dtt.absolutetimezoneoffset, psh.hour as index, psh.ave, psh.stddev, ((psh.ave - psh.stddev) / ?.?) as low, ((psh.ave + psh.stddev) / ?.?) as high, ee.timezone as exchangetimezone, ee.mon_t1start as exchangestart, ee.mon_t1end as exchangeend from powerstats_symboldata psd inner join powerstats_hourly psh on psd.hourlysymbolid = psh.symbolid inner join symbols s on psh.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join mat_ps_hourly_symbolid_max_enddate e on psh.enddate = e.enddate and psh.symbolid = e.symbolid inner join exchanges ee on ee.exchange = s.exchange where psd.symbolid = ? and dtt.dayofweek = ? order by hour asc;

Times Reported Time consuming queries #14

Day	Hour	Count	Duration	Avg duration
Dec 26	23	15	0ms	0ms

15

0ms

421

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 #15

Day	Hour	Count	Duration	Avg duration
Dec 26	23	421	0ms	0ms

16

0ms

2

Details

0ms

select (cast(substring(tz.gmoffset from ? for ?) as float) * ? + cast(substring(tz.gmoffset from ? for ?) as float)) / ? as offset from timezones tz where tz.timezone = ?;

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Dec 26	23	2	0ms	0ms

17

0ms

239

Details

0ms

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

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Dec 26	23	239	0ms	0ms

18

0ms

51

Details

0ms

select * from ( select pricedatetime, open, high, low, close, volume, bsf from t30 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Dec 26	23	51	0ms	0ms

19

0ms

6

Details

0ms

select pid, datname, client_addr from pg_stat_activity where query ilike ? and pid <> pg_backend_pid() and state = ? and datname = ?;

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Dec 26	23	6	0ms	0ms

20

0ms

30

Details

0ms

update executions set isrunning = false, has_results = false, response = ? where id = ?;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Dec 26	23	30	0ms	0ms

Time consuming prepare


Date: 2025-12-26 23:11:50
Duration: 15ms
Database: postgres
Date: 2025-12-26 23:11:50
Duration: 12ms
Database: postgres
Date: 2025-12-26 23:17:03
Duration: 2ms
Database: postgres
Date: 2025-12-26 23:37:27
Duration: 9ms
Database: postgres
Date: 2025-12-26 23:16:11
Duration: 2ms
Database: postgres
Date: 2025-12-26 23:37:27
Duration: 10ms
Database: postgres
Date: 2025-12-26 23:17:51
Duration: 2ms
Database: postgres
Date: 2025-12-26 23:16:16
Duration: 1ms
Database: postgres
Date: 2025-12-26 23:55:58
Duration: 0ms
Database: postgres
Date: 2025-12-26 23:47:16
Duration: 0ms
Database: postgres
Date: 2025-12-26 23:06:47
Duration: 9ms
Database: postgres
Date: 2025-12-26 23:56:58
Duration: 3ms
Database: postgres
Date: 2025-12-26 23:00:58
Duration: 0ms
Database: postgres
Date: 2025-12-26 23:31:01
Duration: 2ms
Database: postgres
Date: 2025-12-26 23:13:49
Duration: 2ms
Database: postgres
Date: 2025-12-26 23:32:00
Duration: 8ms
Database: postgres
Date: 2025-12-26 23:00:03
Duration: 3ms
Database: postgres
Date: 2025-12-26 23:10:05
Duration: 3ms
Database: postgres
Date: 2025-12-26 23:13:48
Duration: 3ms
Database: postgres
Date: 2025-12-26 23:37:40
Duration: 1ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

44s720ms

5,591

Details

0ms

55ms

7ms

WITH rar_max as ( ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Dec 26	23	5,591	44s720ms	7ms

WITH rar_max as ( ;

Date: 2025-12-26 23:11:20 Duration: 55ms Database: postgres parameters: $1 = '607396695309806301', $2 = '607396695309806301', $3 = '607396695309806301'
WITH rar_max as ( ;

Date: 2025-12-26 23:32:05 Duration: 42ms Database: postgres parameters: $1 = '607374047038271301', $2 = '607374047038271301', $3 = '607374047038271301'
WITH rar_max as ( ;

Date: 2025-12-26 23:07:11 Duration: 41ms Database: postgres parameters: $1 = 't', $2 = '958', $3 = '3', $4 = '60', $5 = '240', $6 = '1440', $7 = '0', $8 = '', $9 = '50', $10 = 'AUDCAD', $11 = 'AUDJPY', $12 = 'AUDUSD', $13 = 'EURAUD', $14 = 'EURCHF', $15 = 'EURGBP', $16 = 'EURJPY', $17 = 'EURMXN', $18 = 'EURUSD', $19 = 'GBPJPY', $20 = 'GBPUSD', $21 = 'NZDUSD', $22 = 'USDCAD', $23 = 'USDCHF', $24 = 'USDJPY', $25 = 'USDMXN', $26 = 'BTCUSD', $27 = 'ETHUSD', $28 = 'LTCUSD', $29 = 'AAPL.US', $30 = 'AMD.US', $31 = 'AMZN.US', $32 = 'BABA.US', $33 = 'BRK.B.US', $34 = 'GOOG.US', $35 = 'INTC.US', $36 = 'META.US', $37 = 'MSFT.US', $38 = 'NFLX.US', $39 = 'NKE.US', $40 = 'NVDA.US', $41 = 'PYPL.US', $42 = 'TSLA.US', $43 = 'V.US', $44 = 'Cocoa', $45 = 'Coffee', $46 = 'NatGas', $47 = 'SpotBrent', $48 = 'XAGUSD', $49 = 'XAUUSD', $50 = 'AUS200', $51 = 'EUSTX50', $52 = 'FRA40', $53 = 'GER40', $54 = 'HK50', $55 = 'JPN225', $56 = 'NAS100', $57 = 'UK100', $58 = 'US30', $59 = 'US500', $60 = '0', $61 = '', $62 = '0', $63 = '0', $64 = '0', $65 = '500', $66 = '500', $67 = 't', $68 = '10', $69 = '10'

2

19s12ms

22,073

Details

0ms

22ms

0ms

SELECT ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	23	22,073	19s12ms	0ms

SELECT ;

Date: 2025-12-26 23:56:33 Duration: 22ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840248627636300'
SELECT ;

Date: 2025-12-26 23:11:20 Duration: 22ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840249414067300'
SELECT ;

Date: 2025-12-26 23:11:20 Duration: 22ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840233399863300'

3

2s758ms

1,354

Details

0ms

6ms

2ms

SELECT symbolid, ;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	23	1,354	2s758ms	2ms

SELECT symbolid, ;

Date: 2025-12-26 23:15:47 Duration: 6ms Database: postgres parameters: $1 = 'ATFX', $2 = '15', $3 = 'XAGUSD', $4 = 'XAUUSD'
SELECT symbolid, ;

Date: 2025-12-26 23:17:03 Duration: 3ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'BTCXAU', $4 = 'BTCZAR'
SELECT symbolid, ;

Date: 2025-12-26 23:16:17 Duration: 3ms Database: postgres parameters: $1 = 'AXIORY', $2 = '15', $3 = 'USDHKD', $4 = 'USDILS'

4

1s138ms

695

Details

1ms

3ms

1ms

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

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	23	695	1s138ms	1ms

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

Date: 2025-12-26 23:16:11 Duration: 3ms Database: postgres parameters: $1 = 'FPMARKETS'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2025-12-26 23:48:00 Duration: 3ms Database: postgres parameters: $1 = 'PEPPERSTONEMT5'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2025-12-26 23:00:55 Duration: 2ms Database: postgres parameters: $1 = 'MILLENNIUMPF'

5

648ms

16

Details

28ms

56ms

40ms

with sym_info as ( ;

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	23	16	648ms	40ms

with sym_info as ( ;

Date: 2025-12-26 23:06:47 Duration: 56ms 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: 2025-12-26 23:51:42 Duration: 46ms 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: 2025-12-26 23:21:44 Duration: 45ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'

6

635ms

90

Details

4ms

15ms

7ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	23	90	635ms	7ms

WITH last_candle AS ( ;

Date: 2025-12-26 23:48:01 Duration: 15ms Database: postgres parameters: $1 = '958', $2 = '958'
WITH last_candle AS ( ;

Date: 2025-12-26 23:32:00 Duration: 14ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2025-12-26 23:48:00 Duration: 12ms Database: postgres parameters: $1 = '558', $2 = '558'

7

601ms

22,206

Details

0ms

6ms

0ms

select 1;

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	23	22,206	601ms	0ms

select 1;

Date: 2025-12-26 23:31:00 Duration: 6ms Database: postgres
select 1;

Date: 2025-12-26 23:14:21 Duration: 5ms Database: postgres
select 1;

Date: 2025-12-26 23:46:44 Duration: 3ms Database: postgres

8

478ms

72

Details

0ms

19ms

6ms

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

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	23	72	478ms	6ms

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

Date: 2025-12-26 23:38:00 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: 2025-12-26 23:19:23 Duration: 18ms 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: 2025-12-26 23:52:14 Duration: 18ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

9

430ms

17

Details

0ms

47ms

25ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	23	17	430ms	25ms

with wh_patitioned as ( ;

Date: 2025-12-26 23:00:02 Duration: 47ms 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: 2025-12-26 23:40:02 Duration: 46ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
with wh_patitioned as ( ;

Date: 2025-12-26 23:50:00 Duration: 35ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'

10

293ms

4,207

Details

0ms

1ms

0ms

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

Times Reported Time consuming bind #10

Day	Hour	Count	Duration	Avg duration
	23	4,207	293ms	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: 2025-12-26 23:46:56 Duration: 1ms Database: postgres parameters: $1 = '2025-12-26 22:30:00', $2 = '77.878', $3 = '78.5495', $4 = '77.7535', $5 = '78.4315', $6 = '10343', $7 = '515840230624503300', $8 = '0', $9 = '2025-12-26 23:46:56.136', $10 = '2025-12-26 23:46:56.104', $11 = '77.878', $12 = '78.5495', $13 = '77.7535', $14 = '78.4315', $15 = '10343', $16 = '0', $17 = '2025-12-26 23:46:56.136', $18 = '2025-12-26 23:46:56.104'
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: 2025-12-26 23:41:42 Duration: 0ms Database: postgres parameters: $1 = '2025-12-24 04:30:00', $2 = '8750.4', $3 = '8757.95', $4 = '8746.9', $5 = '8752.05', $6 = '2741', $7 = '515840248015340300', $8 = '0', $9 = '2025-12-26 23:41:42.143', $10 = '2025-12-26 23:41:42.102', $11 = '8750.4', $12 = '8757.95', $13 = '8746.9', $14 = '8752.05', $15 = '2741', $16 = '0', $17 = '2025-12-26 23:41:42.143', $18 = '2025-12-26 23:41:42.102'
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: 2025-12-26 23:32:58 Duration: 0ms Database: postgres parameters: $1 = '2025-12-26 22:30:00', $2 = '25642.1', $3 = '25649.35', $4 = '25627.72', $5 = '25637.4', $6 = '8697', $7 = '515840248039147300', $8 = '0', $9 = '2025-12-26 23:32:58.063', $10 = '2025-12-26 23:32:57.323', $11 = '25642.1', $12 = '25649.35', $13 = '25627.72', $14 = '25637.4', $15 = '8697', $16 = '0', $17 = '2025-12-26 23:32:58.064', $18 = '2025-12-26 23:32:57.323'

11

277ms

6,416

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
	23	6,416	277ms	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: 2025-12-26 23:00:47 Duration: 0ms Database: postgres parameters: $1 = '2025-12-26 22:45:00', $2 = '2.315635', $3 = '2.315855', $4 = '2.314985', $5 = '2.315205', $6 = '1210', $7 = '605679104892478300', $8 = '0', $9 = '2025-12-26 23:00:47.391', $10 = '2025-12-26 23:00:46.82', $11 = '2.315635', $12 = '2.315855', $13 = '2.314985', $14 = '2.315205', $15 = '1210', $16 = '0', $17 = '2025-12-26 23:00:47.391', $18 = '2025-12-26 23:00:46.82'
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: 2025-12-26 23:16:16 Duration: 0ms Database: postgres parameters: $1 = '2025-12-26 23:45:00', $2 = '156.4925', $3 = '156.532', $4 = '156.4795', $5 = '156.4945', $6 = '692', $7 = '515840249375237300', $8 = '0', $9 = '2025-12-26 23:16:16.788', $10 = '2025-12-26 23:16:16.664', $11 = '156.4925', $12 = '156.532', $13 = '156.4795', $14 = '156.4945', $15 = '692', $16 = '0', $17 = '2025-12-26 23:16:16.788', $18 = '2025-12-26 23:16:16.664'
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: 2025-12-26 23:56:57 Duration: 0ms Database: postgres parameters: $1 = '2025-12-26 23:15:00', $2 = '25634.15', $3 = '25637.03', $4 = '25625.03', $5 = '25626.4', $6 = '1218', $7 = '515840248038958300', $8 = '0', $9 = '2025-12-26 23:56:57.044', $10 = '2025-12-26 23:56:56.975', $11 = '25634.15', $12 = '25637.03', $13 = '25625.03', $14 = '25626.4', $15 = '1218', $16 = '0', $17 = '2025-12-26 23:56:57.044', $18 = '2025-12-26 23:56:56.975'

12

267ms

3,375

Details

0ms

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

Times Reported Time consuming bind #12

Day	Hour	Count	Duration	Avg duration
	23	3,375	267ms	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: 2025-12-26 23:01:00 Duration: 0ms Database: postgres parameters: $1 = '2025-12-26 22:00:00', $2 = '10.78505', $3 = '10.78505', $4 = '10.75767', $5 = '10.76021', $6 = '1856', $7 = '515840243926435300', $8 = '0', $9 = '2025-12-26 23:01:00.124', $10 = '2025-12-26 23:01:00.123', $11 = '10.78505', $12 = '10.78505', $13 = '10.75767', $14 = '10.76021', $15 = '1856', $16 = '0', $17 = '2025-12-26 23:01:00.124', $18 = '2025-12-26 23:01:00.123'
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Date: 2025-12-26 23:01:01 Duration: 0ms Database: postgres parameters: $1 = '2025-12-26 22:00:00', $2 = '198.319', $3 = '198.394', $4 = '198.285', $5 = '198.315', $6 = '3037', $7 = '515840233454208300', $8 = '0', $9 = '2025-12-26 23:01:01.058', $10 = '2025-12-26 23:01:01.057', $11 = '198.319', $12 = '198.394', $13 = '198.285', $14 = '198.315', $15 = '3037', $16 = '0', $17 = '2025-12-26 23:01:01.058', $18 = '2025-12-26 23:01:01.057'
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: 2025-12-26 23:00:03 Duration: 0ms Database: postgres parameters: $1 = '2025-12-26 22:00:00', $2 = '17.8852', $3 = '17.89', $4 = '17.8731', $5 = '17.88', $6 = '658', $7 = '515840248019510300', $8 = '0', $9 = '2025-12-26 23:00:03.2', $10 = '2025-12-26 23:00:02.995', $11 = '17.8852', $12 = '17.89', $13 = '17.8731', $14 = '17.88', $15 = '658', $16 = '0', $17 = '2025-12-26 23:00:03.2', $18 = '2025-12-26 23:00:02.995'

13

112ms

1,144

Details

0ms

INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;

Times Reported Time consuming bind #13

Day	Hour	Count	Duration	Avg duration
	23	1,144	112ms	0ms

INSERT INTO T240 (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: 2025-12-26 23:16:56 Duration: 0ms Database: postgres parameters: $1 = '2025-12-24 16:00:00', $2 = '0.99', $3 = '1', $4 = '0.98', $5 = '0.995', $6 = '358', $7 = '515840249451775300', $8 = '0', $9 = '2025-12-26 23:16:56.809', $10 = '2025-12-26 23:16:56.808', $11 = '0.99', $12 = '1', $13 = '0.98', $14 = '0.995', $15 = '358', $16 = '0', $17 = '2025-12-26 23:16:56.809', $18 = '2025-12-26 23:16:56.808'
INSERT INTO T240 (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: 2025-12-26 23:31:58 Duration: 0ms Database: postgres parameters: $1 = '2025-12-24 16:00:00', $2 = '86.91', $3 = '87.955', $4 = '86.635', $5 = '87.795', $6 = '1445', $7 = '515840249458607300', $8 = '0', $9 = '2025-12-26 23:31:58.399', $10 = '2025-12-26 23:31:58.398', $11 = '86.91', $12 = '87.955', $13 = '86.635', $14 = '87.795', $15 = '1445', $16 = '0', $17 = '2025-12-26 23:31:58.399', $18 = '2025-12-26 23:31:58.398'
INSERT INTO T240 (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: 2025-12-26 23:47:07 Duration: 0ms Database: postgres parameters: $1 = '2025-12-26 16:00:00', $2 = '114.65', $3 = '114.725', $4 = '113.315', $5 = '113.52', $6 = '2177', $7 = '515840249439594300', $8 = '0', $9 = '2025-12-26 23:47:07.67', $10 = '2025-12-26 23:47:06.798', $11 = '114.65', $12 = '114.725', $13 = '113.315', $14 = '113.52', $15 = '2177', $16 = '0', $17 = '2025-12-26 23:47:07.67', $18 = '2025-12-26 23:47:06.798'

14

65ms

144

Details

0ms

5ms

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 #14

Day	Hour	Count	Duration	Avg duration
	23	144	65ms	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: 2025-12-26 23:13:49 Duration: 5ms 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: 2025-12-26 23:13:50 Duration: 1ms Database: postgres
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;

Date: 2025-12-26 23:13:49 Duration: 0ms Database: postgres

15

64ms

474

Details

0ms

INSERT INTO T1440_underlying (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
	23	474	64ms	0ms

INSERT INTO T1440_underlying (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: 2025-12-26 23:00:04 Duration: 0ms Database: postgres parameters: $1 = '2025-12-26 00:00:00', $2 = '0.1270555', $3 = '0.127513', $4 = '0.120684', $5 = '0.1222195', $6 = '111197', $7 = '515840249471903300', $8 = '0', $9 = '2025-12-26 23:00:04.578', $10 = '2025-12-26 23:00:04.578', $11 = '0.1270555', $12 = '0.127513', $13 = '0.120684', $14 = '0.1222195', $15 = '111197', $16 = '0', $17 = '2025-12-26 23:00:04.578', $18 = '2025-12-26 23:00:04.578'
INSERT INTO T1440_underlying (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: 2025-12-26 23:16:13 Duration: 0ms Database: postgres parameters: $1 = '2025-12-26 00:00:00', $2 = '0.5839', $3 = '0.58425', $4 = '0.5818', $5 = '0.58325', $6 = '31511', $7 = '515840249465415300', $8 = '0', $9 = '2025-12-26 23:16:13.095', $10 = '2025-12-26 23:16:13.095', $11 = '0.5839', $12 = '0.58425', $13 = '0.5818', $14 = '0.58325', $15 = '31511', $16 = '0', $17 = '2025-12-26 23:16:13.095', $18 = '2025-12-26 23:16:13.095'
INSERT INTO T1440_underlying (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: 2025-12-26 23:46:25 Duration: 0ms Database: postgres parameters: $1 = '2025-12-26 00:00:00', $2 = '4490.9', $3 = '4550.025', $4 = '4483.76', $5 = '4531.205', $6 = '881248', $7 = '515840249391588300', $8 = '0', $9 = '2025-12-26 23:46:25.646', $10 = '2025-12-26 23:46:25.645', $11 = '4490.9', $12 = '4550.025', $13 = '4483.76', $14 = '4531.205', $15 = '881248', $16 = '0', $17 = '2025-12-26 23:46:25.646', $18 = '2025-12-26 23:46:25.645'

16

50ms

1

Details

50ms

with maxwhid as ( ;

Times Reported Time consuming bind #16

Day	Hour	Count	Duration	Avg duration
	23	1	50ms	50ms

with maxwhid as ( ;

Date: 2025-12-26 23:11:45 Duration: 50ms Database: postgres parameters: $1 = '335', $2 = '621', $3 = '637', $4 = '642', $5 = '660', $6 = '666', $7 = '643', $8 = '630', $9 = '680', $10 = '641', $11 = '431', $12 = '622', $13 = '489', $14 = '529', $15 = '576', $16 = '665', $17 = '667', $18 = '558', $19 = '620', $20 = '125', $21 = '488', $22 = '567', $23 = '689', $24 = '700', $25 = '758', $26 = '763', $27 = '765', $28 = '817', $29 = '914', $30 = '972'

17

37ms

8

Details

2ms

9ms

4ms

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

Times Reported Time consuming bind #17

Day	Hour	Count	Duration	Avg duration
	23	8	37ms	4ms

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

Date: 2025-12-26 23:13:48 Duration: 9ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'
WITH pre_symbols AS ( /* find relevant symbols */ ;

Date: 2025-12-26 23:13:48 Duration: 7ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'
WITH pre_symbols AS ( /* find relevant symbols */ ;

Date: 2025-12-26 23:13:48 Duration: 7ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'

18

32ms

6,003

Details

0ms

2ms

0ms

SET application_name = 'PostgreSQL JDBC Driver';

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	23	6,003	32ms	0ms

SET application_name = 'PostgreSQL JDBC Driver';

Date: 2025-12-26 23:26:55 Duration: 2ms Database: postgres
SET application_name = 'PostgreSQL JDBC Driver';

Date: 2025-12-26 23:35:57 Duration: 2ms Database: postgres
SET application_name = 'PostgreSQL JDBC Driver';

Date: 2025-12-26 23:15:39 Duration: 1ms Database: postgres

19

27ms

31

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 #19

Day	Hour	Count	Duration	Avg duration
	23	31	27ms	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: 2025-12-26 23:21:53 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'EURAUD', $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: 2025-12-26 23:16:20 Duration: 1ms Database: postgres parameters: $1 = '538', $2 = 'XAUUSDb', $3 = '538'
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2025-12-26 23:16:29 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'NOKSEK', $3 = '558'

20

26ms

6,022

Details

0ms

SET extra_float_digits = 3;

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	23	6,022	26ms	0ms

SET extra_float_digits = 3;

Date: 2025-12-26 23:40:30 Duration: 0ms Database: postgres
SET extra_float_digits = 3;

Date: 2025-12-26 23:30:55 Duration: 0ms Database: postgres
SET extra_float_digits = 3;

Date: 2025-12-26 23:26:55 Duration: 0ms Database: postgres

Log levels

Key values

473,211 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	472	0.10%
DETAIL	93,140	19.68%
LOG	378,986	80.09%
STATEMENT	613	0.13%

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

Key values

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

Key values

Connections per user

Key values

Connections per host

Key values

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

Key values

Checkpoints Activity

Checkpoint causes

Key values

Temporary Files

Size of temporary files

Key values

Number of temporary files

Key values

Temporary Files Activity

Queries generating the most temporary files (N)

Queries generating the largest temporary files

Vacuums

Vacuums / Analyzes Distribution

Key values

Analyzes per table

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Vacuums per table

Key values

Tuples removed per table

Key values

Pages removed per table

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Autovacuum Activity

Locks

Locks by types

Key values

Type of locks

Most frequent waiting queries (N)

Queries that waited the most

Queries

Queries by type

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Queries by database

Key values

Queries by user

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Duration by user