pgBadger :: PostgreSQL Log Analyzer

Global information

Generated on Thu Dec 18 17:02:05 2025
Log file: /home/postgres/pg_data/data/pg_log/postgresql-2025-12-18_180000.log, ..., /home/postgres/pg_data/data/pg_log/postgresql-2025-12-18_184517.log
Parsed 8,827,553 log entries in 3m4s
Log start from 2025-12-18 18:00:00 to 2025-12-18 19:00:00

Global Stats

352 Number of unique normalized queries
805,411 Number of queries
2h59m49s Total query duration
2025-12-18 18:00:00 First query
2025-12-18 19:00:00 Last query
5,855 queries/s at 2025-12-18 18:45:04 Query peak

2h59m49s Total query duration
1m4s Prepare/parse total duration
3m34s Bind total duration
2h55m10s 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

52 Total number of automatic vacuums
59 Total number of automatic analyzes

672 Number temporary file
171.27 MiB Max size of temporary file
7.62 MiB Average size of temporary file

27,290 Total number of sessions
11 sessions at 2025-12-18 18:42:12 Session peak
3d4h55m3s Total duration of sessions
10s146ms Average duration of sessions
29 Average queries per session
395ms Average queries duration per session
9s751ms Average idle time per session

27,294 Total number of connections
111 connections/s at 2025-12-18 18:33:37 Connection peak
3 Total number of databases

SQL Traffic

Key values

5,855 queries/s Query Peak
2025-12-18 18:45:04 Date

SELECT Traffic

Key values

2,856 queries/s Query Peak
2025-12-18 18:45:04 Date

INSERT/UPDATE/DELETE Traffic

Key values

167 queries/s Query Peak
2025-12-18 18:31:52 Date

Queries duration

Key values

2h59m49s 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 18	18	805,402	0ms	1m	13ms	5m34s	5m58s	7m33s
	19	9	0ms	1ms	0ms	3ms	3ms	3ms

Day	Hour	SELECT	COPY TO	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Dec 18	18	296,319	26	0ms	0ms	0ms	0ms
	19	5	0	0ms	0ms	0ms	0ms

Day	Hour	INSERT	UPDATE	DELETE	COPY FROM	Average Duration	Latency Percentile(90)	Latency Percentile(95)	Latency Percentile(99)
Dec 18	18	33,559	3,947	16	96	0ms	0ms	0ms	0ms
	19	0	0	0	0	0ms	0ms	0ms	0ms

Day	Hour	Prepare	Bind	Bind/Prepare	Percentage of prepare
Dec 18	18	164,463	368,723	2.24	47.04%
	19	0	5	5.00	0.00%

Day	Hour	Count	Average / Second
Dec 18	18	27,294	7.58/s
	19	0	0.00/s

Day	Hour	Count	Average Duration	Average idle time
Dec 18	18	27,290	10s146ms	9s761ms
	19	0	0ms	0ms

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Established Connections

Key values

111 connections Connection Peak
2025-12-18 18:33:37 Date

Connections per database

Key values

acaweb_fx Main Database
27,294 connections Total

Chart
Table

Database	User	Count
acaweb_fx		27,199
	postgres	26,811
	psql	388
socialmedia		95
	postgres	95

Connections per user

Key values

postgres Main User
27,294 connections Total

Chart
Table

User	Count
postgres	26,906
psql	388

Connections per host

Key values

192.168.1.15 Main host with 12679 connections
27,293 Total connections

Chart
Table

Host	Count
127.0.0.1	114
192.168.0.114	8
192.168.0.216	102
192.168.0.74	11,788
192.168.1.145	91
192.168.1.15	12,679
192.168.1.20	123
192.168.1.231	20
192.168.1.239	3
192.168.1.90	57
192.168.2.126	62
192.168.2.182	20
192.168.2.82	48
192.168.3.199	36
192.168.4.142	1,410
192.168.4.150	10
192.168.4.189	1
192.168.4.226	4
192.168.4.238	8
192.168.4.239	7
192.168.4.33	90
192.168.4.57	4
192.168.4.98	330
52.214.24.33	4
[local]	274

Simultaneous sessions

Key values

11 sessions Session Peak
2025-12-18 18:42:12 Date

Histogram of session times

Key values

24,540 0-500ms duration

Chart
Table

Range	Count	Percentage
0ms-500ms	24,540	89.92%
500ms-1s	451	1.65%
1s-30s	2,126	7.79%
30s-1m	58	0.21%
1m-10m	28	0.10%
10m-30m	71	0.26%
30m-1h	1	0.00%
1h-8h	15	0.05%
> 8h	0	0.00%

Sessions per database

Key values

acaweb_fx Main Database
27,290 sessions Total

Chart
Table

Database	User	Count	Total Duration	Average Duration
acaweb_fx	27,197	3d4h26m55s	10s119ms
socialmedia	93	28m8s	18s151ms

Sessions per user

Key values

postgres Main User
27,290 sessions Total

Chart
Table

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

Sessions per host

Key values

192.168.1.15 Main Host
27,290 sessions Total

Chart
Table

Host	Count	Total Duration	Average Duration
127.0.0.1	114	14s7ms	122ms
192.168.0.114	6	34m20s	5m43s
192.168.0.216	102	1m42s	1s8ms
192.168.0.74	11,786	7h59m28s	2s440ms
192.168.1.145	91	11h58m17s	7m53s
192.168.1.15	12,680	4h47m33s	1s360ms
192.168.1.20	123	20h48m26s	10m8s
192.168.1.231	20	9h53m53s	29m41s
192.168.1.239	3	21ms	7ms
192.168.1.90	57	36s965ms	648ms
192.168.2.126	62	6s346ms	102ms
192.168.2.182	20	44s972ms	2s248ms
192.168.2.82	48	24s968ms	520ms
192.168.3.199	36	1s413ms	39ms
192.168.4.142	1,410	29m17s	1s246ms
192.168.4.150	10	20h3m31s	2h21s
192.168.4.189	1	202ms	202ms
192.168.4.226	4	39ms	9ms
192.168.4.238	8	11s45ms	1s380ms
192.168.4.239	7	38s730ms	5s532ms
192.168.4.33	90	8m50s	5s890ms
192.168.4.57	4	34ms	8ms
192.168.4.98	330	17s874ms	54ms
52.214.24.33	4	2m13s	33s446ms
[local]	274	4m11s	917ms

Sessions per application

Key values

unknown Main Host
27,290 sessions Total

Chart
Table

Application	Count	Total Duration	Average Duration
unknown	27,290	3d4h55m3s	10s146ms

Checkpoints Buffers

Key values

11,510 buffers Checkpoint Peak
2025-12-18 18:05:21 Date
209.934 seconds Highest write time
0.023 seconds Sync time

Checkpoints Wal files

Key values

5 files Wal files usage Peak
2025-12-18 18:05:21 Date

Checkpoints distance

Key values

171.64 Mo Distance Peak
2025-12-18 18:10:21 Date

Checkpoints Activity

Day	Hour	Written buffers	Write time	Sync time	Total time
Dec 18	18	59,814	2,068.117s	0.093s	2,068.557s
	19	0	0s	0s	0s

Day	Hour	Added	Removed	Recycled	Synced files	Longest sync	Average sync
Dec 18	18	0	0	30	2,037	0.007s	0s
	19	0	0	0	0	0s	0s

Day	Hour	Count	Avg time (sec)
Dec 18	18	0	0s
	19	0	0s

Day	Hour	Mean distance	Mean estimate
Dec 18	18	41,673.75 kB	69,269.33 kB
	19	0.00 kB	0.00 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

184.94 MiB Temp Files size Peak
2025-12-18 18:50:07 Date

Number of temporary files

Key values

30 per second Temp Files Peak
2025-12-18 18:47:16 Date

Temporary Files Activity

Temp Files

Day	Hour	Count	Total size	Average size
Dec 18	18	672	5.00 GiB	7.62 MiB
	19	0	0	0

↑ Back to the top of the Temporary Files Activity table

Queries generating the most temporary files (N)

Rank	Count	Total size	Min size	Max size	Avg size	Query
1	30	1.66 GiB	3.83 MiB	171.27 MiB	56.52 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: 2025-12-18 18:50:07 Duration: 0ms
2	23	209.93 MiB	9.09 MiB	9.15 MiB	9.13 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: 2025-12-18 18:48:08 Duration: 0ms
3	22	82.01 MiB	3.73 MiB	3.73 MiB	3.73 MiB	select resultuid from relevance_fibonacci_results order by resultuid desc limit ?), fr as ( select a., rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp)))), results as ( select distinct on (symbolid) from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc; SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1), fr AS ( SELECT a., rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4, $5, $6, $7, $8, $9, $10)) AND ($11 = 0 OR s.exchange in ($12)) AND ($13 = 0 OR coalesce(bim.code, s.symbol) in ($14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226)) AND ($227 = 0 OR fr.pattern in ($228)) AND ($229 = 0 OR fr.patternlengthbars <= $230) AND ($231 = 0 OR ($232 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($233 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) FROM all_results WHERE (FALSE = $234 OR relevant = 1) AND ($235 = 0 OR age <= $236) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2025-12-18 18:46:20 Duration: 0ms
4	16	503.10 MiB	31.44 MiB	31.45 MiB	31.44 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: 2025-12-18 18:46:13 Duration: 0ms
5	16	1.10 GiB	70.62 MiB	70.63 MiB	70.63 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: 2025-12-18 18:46:16 Duration: 0ms
6	12	40.17 MiB	3.33 MiB	3.35 MiB	3.35 MiB	select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ?), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?)), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc; SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ($2 = 0 OR s.timegranularity in ($3, $4, $5, $6, $7, $8, $9)) AND ($10 = 0 OR s.exchange in ($11)) AND ($12 = 0 OR coalesce(bim.code, s.symbol) in ($13, $14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226, $227, $228, $229, $230, $231, $232, $233, $234, $235, $236, $237, $238, $239, $240, $241, $242, $243, $244, $245, $246, $247, $248, $249, $250, $251, $252, $253, $254, $255, $256, $257, $258, $259, $260, $261, $262, $263, $264, $265, $266, $267, $268, $269, $270, $271, $272, $273, $274, $275, $276, $277, $278, $279, $280, $281, $282, $283, $284, $285, $286, $287, $288, $289, $290, $291, $292, $293, $294, $295, $296, $297, $298, $299, $300, $301, $302, $303, $304, $305, $306, $307, $308, $309, $310, $311, $312, $313, $314, $315, $316, $317, $318, $319, $320, $321, $322)) AND ($323 = 0 OR ccr.patternlengthbars <= $324)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $325 OR relevant = 1) AND ($326 = 0 OR age <= $327) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC; Date: 2025-12-18 18:46:05 Duration: 0ms
7	8	954.94 MiB	119.33 MiB	119.40 MiB	119.37 MiB	select updateresultsmaterializedview (); select updateresultsmaterializedview (); Date: 2025-12-18 18:47:24 Duration: 0ms
8	4	232.82 MiB	58.14 MiB	58.29 MiB	58.20 MiB	select updateageforrelevantresults (); select updateageforrelevantresults (); Date: 2025-12-18 18:47:07 Duration: 0ms

Queries generating the largest temporary files

Rank	Size	Query
1	171.27 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: 2025-12-18 18:30:05 ]
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: 2025-12-18 18:40:05 ]
3	119.40 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-18 18:17:20 ]
4	119.38 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-18 18:32:22 ]
5	119.38 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-18 18:47:24 ]
6	119.37 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-18 18:20:33 ]
7	119.37 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-18 18:50:33 ]
8	119.36 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-18 18:35:32 ]
9	119.35 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-18 18:05:33 ]
10	119.33 MiB	select updateresultsmaterializedview (); [ Date: 2025-12-18 18:02:18 ]
11	115.09 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: 2025-12-18 18:20:04 ]
12	112.36 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: 2025-12-18 18:20:05 ]
13	105.22 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: 2025-12-18 18:00:06 ]
14	100.07 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: 2025-12-18 18:10:04 ]
15	85.02 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: 2025-12-18 18:10:05 ]
16	79.44 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: 2025-12-18 18:50:04 ]
17	71.34 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: 2025-12-18 18:50:05 ]
18	70.63 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: 2025-12-18 18:11:17 ]
19	70.63 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: 2025-12-18 18:16:17 ]
20	70.63 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: 2025-12-18 18:18:15 ]

Vacuums / Analyzes Distribution

Key values

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

Analyzes per table

Key values

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

Chart
Table

Table	Number of analyzes
acaweb_fx.public.solr_relevance_old	16
acaweb_fx.public.datafeeds_latestrun	5
acaweb_fx.pg_catalog.pg_attribute	5
acaweb_fx.public.relevance_keylevels_results	4
acaweb_fx.pg_catalog.pg_class	4
acaweb_fx.public.relevance_fibonacci_results	4
acaweb_fx.public.relevance_autochartist_results	4
acaweb_fx.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.pg_catalog.pg_depend	2
acaweb_fx.public.solr_imports	1
acaweb_fx.public.latest_candle_datetime_per_receng	1
acaweb_fx.public.relevance_consecutivecandles_results	1
acaweb_fx.public.symbollatestupdatetime	1
socialmedia.public.processstatevariables	1
acaweb_fx.public.t15	1
Total	59

Vacuums per table

Key values

public.solr_relevance_old (27) Main table vacuumed on database acaweb_fx
52 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	27	19	21,632	0	96	0	223	11,775	2,037	10,124,599
acaweb_fx.public.datafeeds_latestrun	5	0	603	0	11	0	0	75	13	81,208
acaweb_fx.pg_toast.pg_toast_2619	2	2	288	0	52	0	0	185	49	208,476
acaweb_fx.public.latest_t15_candle_view	2	2	186	0	6	0	0	12	0	1,860
acaweb_fx.public.relevance_keylevels_results	2	2	8,637	0	442	4	49	2,707	387	965,300
acaweb_fx.pg_catalog.pg_class	2	2	908	0	79	0	0	289	68	388,529
acaweb_fx.public.relevance_fibonacci_results	2	2	2,557	0	78	2	108	436	49	128,390
acaweb_fx.public.relevance_autochartist_results	2	2	7,152	0	221	2	464	1,706	191	522,843
acaweb_fx.pg_catalog.pg_index	1	1	106	0	12	0	0	27	11	83,466
acaweb_fx.public.autochartist_symbolupdates	1	1	26,338	0	4,158	5	36,892	8,857	6,955	2,896,237
acaweb_fx.pg_catalog.pg_attribute	1	1	792	0	165	0	67	355	145	847,831
acaweb_fx.pg_catalog.pg_depend	1	1	355	0	88	0	59	194	72	439,712
acaweb_fx.pg_catalog.pg_type	1	1	129	0	17	0	0	50	14	100,770
acaweb_fx.pg_catalog.pg_statistic	1	1	1,053	0	199	0	582	489	192	711,361
acaweb_fx.public.relevance_consecutivecandles_results	1	1	82	0	7	0	0	23	3	18,348
acaweb_fx.public.symbollatestupdatetime	1	1	2,114	0	330	0	547	1,541	266	754,014
Total	52	39	72,932	47,853	5,961	13	38,991	28,721	10,452	18,272,944

Tuples removed per table

Key values

public.solr_relevance_old (95307) Main table with removed tuples on database acaweb_fx
127898 tuples Total removed

Chart
Table

		Index	Tuples			Pages
Table	Vacuums	scans	removed	remain	not yet removable	removed	remain
acaweb_fx.public.solr_relevance_old	27	19	95,307	249,146	71,257	0	6,171
acaweb_fx.public.symbollatestupdatetime	1	1	18,088	89,531	190	0	1,714
acaweb_fx.public.autochartist_symbolupdates	1	1	5,997	50,341	45	0	40,691
acaweb_fx.public.relevance_keylevels_results	2	2	3,535	23,553	0	0	558
acaweb_fx.public.relevance_autochartist_results	2	2	1,468	18,024	0	0	760
acaweb_fx.pg_catalog.pg_attribute	1	1	1,162	10,932	0	21	240
acaweb_fx.pg_catalog.pg_depend	1	1	612	14,165	8	0	131
acaweb_fx.pg_catalog.pg_statistic	1	1	544	3,708	0	0	1,194
acaweb_fx.pg_catalog.pg_class	2	2	305	3,295	5	0	300
acaweb_fx.public.datafeeds_latestrun	5	0	273	70	0	0	80
acaweb_fx.public.relevance_fibonacci_results	2	2	199	2,839	0	0	204
acaweb_fx.pg_toast.pg_toast_2619	2	2	132	357	21	3	103
acaweb_fx.public.latest_t15_candle_view	2	2	103	49	21	0	2
acaweb_fx.public.relevance_consecutivecandles_results	1	1	97	261	0	0	7
acaweb_fx.pg_catalog.pg_type	1	1	64	1,444	0	0	38
acaweb_fx.pg_catalog.pg_index	1	1	12	815	2	0	22
Total	52	39	127,898	468,530	71,549	24	52,215

Pages removed per table

Key values

pg_catalog.pg_attribute (21) Main table with removed pages on database acaweb_fx
24 pages Total removed

Chart
Table

Table	Number of vacuums	Index scans	Tuples removed	Pages removed
acaweb_fx.pg_catalog.pg_attribute	1	1	1162	21
acaweb_fx.pg_toast.pg_toast_2619	2	2	132	3
acaweb_fx.pg_catalog.pg_index	1	1	12	0
acaweb_fx.public.datafeeds_latestrun	5	0	273	0
acaweb_fx.public.autochartist_symbolupdates	1	1	5997	0
acaweb_fx.pg_catalog.pg_depend	1	1	612	0
acaweb_fx.public.latest_t15_candle_view	2	2	103	0
acaweb_fx.public.relevance_keylevels_results	2	2	3535	0
acaweb_fx.pg_catalog.pg_class	2	2	305	0
acaweb_fx.public.relevance_fibonacci_results	2	2	199	0
acaweb_fx.pg_catalog.pg_type	1	1	64	0
acaweb_fx.pg_catalog.pg_statistic	1	1	544	0
acaweb_fx.public.relevance_consecutivecandles_results	1	1	97	0
acaweb_fx.public.symbollatestupdatetime	1	1	18088	0
acaweb_fx.public.relevance_autochartist_results	2	2	1468	0
acaweb_fx.public.solr_relevance_old	27	19	95307	0
Total	52	39	127,898	24

Autovacuum Activity

Vacuums / Analyzes

Day	Hour	VACUUMs	ANALYZEs
Dec 18	18	52	59
	19	0	0

↑ Back to the top of the Autovacuum Activity table

Locks by types

Key values

unknown Main Lock Type
0 locks Total

Chart
Table

Type of locks

NO DATASET

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

Most frequent waiting queries (N)

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

Queries that waited the most

Rank	Wait time	Query
NO DATASET

Queries by type

Key values

296,324 Total read queries
53,305 Total write queries

Chart
Table

Type	Count	Percentage
SELECT	296,324	36.79%
INSERT	33,559	4.17%
UPDATE	3,947	0.49%
DELETE	16	0.00%
COPY FROM	96	0.01%
COPY TO	26	0.00%
CTE	14,892	1.85%
DDL	23	0.00%
TCL	746	0.09%
CURSOR	0	0.00%
OTHERS	455,782	56.59%

Queries by database

Key values

unknown Main database
804,386 Requests
2h55m10s (unknown)
Main time consuming database

Chart
Table

Database	Request type	Count	Duration
acaweb_fx	Total	930	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	213	0ms
	select	102	0ms
	tcl	333	0ms
	update	40	0ms
socialmedia	Total	95	0ms
	select	90	0ms
	tcl	5	0ms
unknown	Total	804,386	2h55m10s
	copy from	16	0ms
	cte	14,788	0ms
	ddl	7	0ms
	insert	33,559	0ms
	others	52,865	0ms
	select	296,132	0ms
	tcl	408	0ms
	update	3,907	0ms

Queries by user

Key values

unknown Main user
804,386 Requests

Queries Chart
Table

User	Request type	Count	Duration
postgres	Total	1,025	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	213	0ms
	select	192	0ms
	tcl	338	0ms
	update	40	0ms
unknown	Total	804,386	2h55m10s
	copy from	16	0ms
	cte	14,788	0ms
	ddl	7	0ms
	insert	33,559	0ms
	others	52,865	0ms
	select	296,132	0ms
	tcl	408	0ms
	update	3,907	0ms

Duration by user

Key values

2h55m10s (unknown) Main time consuming user

Duration Chart
Table

User	Request type	Count	Duration
postgres	Total	1,025	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	213	0ms
	select	192	0ms
	tcl	338	0ms
	update	40	0ms
unknown	Total	804,386	2h55m10s
	copy from	16	0ms
	cte	14,788	0ms
	ddl	7	0ms
	insert	33,559	0ms
	others	52,865	0ms
	select	296,132	0ms
	tcl	408	0ms
	update	3,907	0ms

Queries by host

Key values

unknown Main host
805,411 Requests
2h55m10s (unknown)
Main time consuming host

Chart
Table

Host	Request type	Count	Duration
unknown	Total	805,411	2h55m10s
	copy from	96	0ms
	copy to	26	0ms
	cte	14,892	0ms
	ddl	23	0ms
	delete	16	0ms
	insert	33,559	0ms
	others	53,078	0ms
	select	296,324	0ms
	tcl	746	0ms
	update	3,947	0ms

Queries by application

Key values

unknown Main application
805,023 Requests
2h55m10s (unknown)
Main time consuming application

Chart
Table

Application	Request type	Count	Duration
psql	Total	388	0ms
	copy from	80	0ms
	copy to	26	0ms
	cte	104	0ms
	ddl	16	0ms
	delete	16	0ms
	others	4	0ms
	select	102	0ms
	update	40	0ms
unknown	Total	805,023	2h55m10s
	copy from	16	0ms
	cte	14,788	0ms
	ddl	7	0ms
	insert	33,559	0ms
	others	53,074	0ms
	select	296,222	0ms
	tcl	746	0ms
	update	3,907	0ms

Number of cancelled queries

Key values

0 per second Cancelled query Peak
2025-12-18 18:44:55 Date

Number of cancelled queries (5 minutes period)

NO DATASET

Histogram of query times

Key values

270,080 0-1ms duration

Chart
Table

Range	Count	Percentage
0-1ms	270,080	67.07%
1-5ms	123,648	30.70%
5-10ms	5,145	1.28%
10-25ms	1,292	0.32%
25-50ms	352	0.09%
50-100ms	248	0.06%
100-500ms	470	0.12%
500-1000ms	192	0.05%
1000-10000ms	951	0.24%
> 10000ms	326	0.08%

Slowest individual queries

Rank	Duration	Query
NO DATASET

Time consuming queries

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

0ms

3

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Dec 18	18	3	0ms	0ms

2

0ms

39

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 18	18	39	0ms	0ms

3

0ms

2

Details

0ms

select ft.ftrelid as table_id, srv.srvname as table_server, ft.ftoptions as table_options, pg_catalog.pg_get_userbyid(cls.relowner) AS "owner" from pg_catalog.pg_foreign_table ft left outer join pg_catalog.pg_foreign_server srv on ft.ftserver = srv.oid join pg_catalog.pg_class cls on ft.ftrelid = cls.oid where cls.relnamespace = ?::oid and pg_catalog.age(ft.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) order by table_id;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Dec 18	18	2	0ms	0ms

4

0ms

10

Details

0ms

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

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Dec 18	18	10	0ms	0ms

5

0ms

2,276

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Dec 18	18	2,276	0ms	0ms

6

0ms

2

Details

0ms

select ind_head.indexrelid index_id, k col_idx, k <= indnkeyatts in_key, ind_head.indkey[k - 1] column_position, ind_head.indoption[k - 1] column_options, ind_head.indcollation[k - 1] as collation, colln.nspname as collation_schema, collname as collation_str, ind_head.indclass[k - 1] as opclass, case when opcdefault then null else opcn.nspname end as opclass_schema, case when opcdefault then null else opcname end as opclass_str, case when indexprs is null then null when ind_head.indkey[k - 1] = ? then chr(?) || pg_catalog.pg_get_indexdef(ind_head.indexrelid, k::int, true) else pg_catalog.pg_get_indexdef(ind_head.indexrelid, k::int, true) end as expression, amcanorder can_order from pg_catalog.pg_index ind_head join pg_catalog.pg_class ind_stor on ind_stor.oid = ind_head.indexrelid cross join unnest(ind_head.indkey) with ordinality u (u, k) left join pg_catalog.pg_collation on pg_collation.oid = ind_head.indcollation[k - 1] left join pg_catalog.pg_namespace colln on collnamespace = colln.oid cross join pg_catalog.pg_indexam_has_property(ind_stor.relam, ?) amcanorder left join pg_catalog.pg_opclass on pg_opclass.oid = ind_head.indclass[k - 1] left join pg_catalog.pg_namespace opcn on opcnamespace = opcn.oid where ind_stor.relnamespace = ?::oid and ind_stor.relkind in (...) and pg_catalog.age(ind_stor.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) order by index_id, k;

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Dec 18	18	2	0ms	0ms

7

0ms

48

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Dec 18	18	48	0ms	0ms

8

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Dec 18	18	4	0ms	0ms

9

0ms

1

Details

0ms

select distinct connamespace as schema_id from pg_catalog.pg_constraint f, pg_catalog.pg_class o where f.contype = ? and f.confrelid = o.oid and o.relnamespace in (...);

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Dec 18	18	1	0ms	0ms

10

0ms

3

Details

0ms

select oid from pg_catalog.pg_foreign_data_wrapper;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Dec 18	18	3	0ms	0ms

11

0ms

2

Details

0ms

select t.oid as type_id, t.xmin as type_state_number, t.typname as type_name, t.typtype as type_sub_kind, t.typcategory as type_category, t.typrelid as class_id, t.typbasetype as base_type_id, case when t.typtype in (...) then null else pg_catalog.format_type(t.typbasetype, t.typtypmod) end as type_def, t.typndims as dimensions_number, t.typdefault as default_expression, t.typnotnull as mandatory, pg_catalog.pg_get_userbyid(t.typowner) AS "owner" from pg_catalog.pg_type t left outer join pg_catalog.pg_class c on t.typrelid = c.oid where t.typnamespace = ?::oid and pg_catalog.age(t.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) and (t.typtype in (...) or c.relkind = ?::"char" or (t.typtype = ? and (t.typelem = ? or t.typcategory <> ?)) or t.typtype = ? and not t.typisdefined) order by ?;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Dec 18	18	2	0ms	0ms

12

0ms

2

Details

0ms

select t.relkind as table_kind, t.relname as table_name, t.oid as table_id, t.xmin as table_state_number, false as table_with_oids, t.reltablespace as tablespace_id, t.reloptions as options, t.relpersistence as persistence, ( select pg_catalog.array_agg(inhparent::bigint order by inhseqno)::varchar from pg_catalog.pg_inherits where t.oid = inhrelid) as ancestors, ( select pg_catalog.array_agg(inhrelid::bigint order by inhrelid)::varchar from pg_catalog.pg_inherits where t.oid = inhparent) as successors, t.relispartition as is_partition, pg_catalog.pg_get_partkeydef (t.oid) as partition_key, pg_catalog.pg_get_expr(t.relpartbound, t.oid) as partition_expression, t.relam am_id, pg_catalog.pg_get_userbyid(t.relowner) AS "owner" from pg_catalog.pg_class t where relnamespace = ?::oid and relkind in (...) and pg_catalog.age(t.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) order by table_kind, table_id;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Dec 18	18	2	0ms	0ms

13

0ms

1

Details

0ms

select count(*) as total_records from ourfavourites_findlatest_kl_base where "brokerid" = ?;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Dec 18	18	1	0ms	0ms

14

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 #14

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

15

0ms

373

Details

0ms

commit;

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Dec 18	18	373	0ms	0ms

16

0ms

452

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 #16

Day	Hour	Count	Duration	Avg duration
Dec 18	18	452	0ms	0ms

17

0ms

1

Details

0ms

select e.oid as id, e.xmin as state_number, extname as name, extversion as version, extnamespace as schema_id, nspname as schema_name, array ( select unnest from unnest(available_versions) where unnest > extversion) as available_updates from pg_catalog.pg_extension e join pg_namespace n on e.extnamespace = n.oid left join ( select name, array_agg(version) as available_versions from pg_available_extension_versions() group by name) v on e.extname = v.name where pg_catalog.age(e.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?);

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Dec 18	18	1	0ms	0ms

18

0ms

240

Details

0ms

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

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Dec 18	18	240	0ms	0ms

19

0ms

1

Details

0ms

select a.oid as access_method_id, a.xmin as state_number, a.amname as access_method_name, a.amhandler::oid as handler_id, pg_catalog.quote_ident(n.nspname) || ? || pg_catalog.quote_ident(p.proname) as handler_name, a.amtype as access_method_type from pg_am a join pg_proc p on a.amhandler::oid = p.oid join pg_namespace n on p.pronamespace = n.oid where pg_catalog.age(a.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?);

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Dec 18	18	1	0ms	0ms

20

0ms

1

Details

0ms

select t.oid as object_id, t.spcacl as acl from pg_catalog.pg_tablespace t union all select t.oid as object_id, t.datacl as acl from pg_catalog.pg_database t;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Dec 18	18	1	0ms	0ms

Most frequent queries (N)

Rank

Times executed

Total duration

Min duration

Max duration

Avg duration

Query

1

144,882

Details

0ms

select ?;

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Dec 18	18	144,879	0ms	0ms
	19	3	0ms	0ms

2

120,489

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 18	18	120,487	0ms	0ms
	19	2	0ms	0ms

3

26,181

Details

0ms

set extra_float_digits = ?;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Dec 18	18	26,181	0ms	0ms

4

26,159

Details

0ms

set application_name = ?;

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Dec 18	18	26,159	0ms	0ms

5

9,902

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Dec 18	18	9,902	0ms	0ms

6

8,400

Details

0ms

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

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Dec 18	18	8,400	0ms	0ms

7

7,655

Details

0ms

with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ) select a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, s.exchange, s.symbol, s.longname, s.shortname, breakout, dtt.timezone, patternstartprice, patternendprice, qtytp, newlevels.profit, newlevels.stop, newlevels.filtered, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern inner join rar_max rm on ? = ? left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid left join lateral calc_cp_signal (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Dec 18	18	7,655	0ms	0ms

8

6,891

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 t60 t where t.symbolid = ? and (bsf = ? or bsf is null) and pricedatetime >= ? and pricedatetime <= ? order by pricedatetime desc limit ?;

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Dec 18	18	6,891	0ms	0ms

9

6,389

Details

0ms

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

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Dec 18	18	6,389	0ms	0ms

10

5,438

Details

0ms

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

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Dec 18	18	5,438	0ms	0ms

11

4,066

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 #11

Day	Hour	Count	Duration	Avg duration
Dec 18	18	4,066	0ms	0ms

12

3,613

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 #12

Day	Hour	Count	Duration	Avg duration
Dec 18	18	3,613	0ms	0ms

13

3,519

Details

0ms

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

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Dec 18	18	3,519	0ms	0ms

14

3,294

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 18	18	3,294	0ms	0ms

15

2,425

Details

0ms

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

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Dec 18	18	2,425	0ms	0ms

16

2,276

Details

0ms

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

Times Reported Time consuming queries #16

Day	Hour	Count	Duration	Avg duration
Dec 18	18	2,276	0ms	0ms

17

1,275

Details

0ms

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

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Dec 18	18	1,275	0ms	0ms

18

838

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 18	18	838	0ms	0ms

19

838

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 18	18	838	0ms	0ms

20

548

Details

0ms

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

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Dec 18	18	548	0ms	0ms

Normalized slowest queries (N)

Rank

Min duration

Max duration

Avg duration

Times executed

Total duration

Query

1

0ms

3

Details

0ms

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

Times Reported Time consuming queries #1

Day	Hour	Count	Duration	Avg duration
Dec 18	18	3	0ms	0ms

2

0ms

39

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 18	18	39	0ms	0ms

3

0ms

2

Details

0ms

select ft.ftrelid as table_id, srv.srvname as table_server, ft.ftoptions as table_options, pg_catalog.pg_get_userbyid(cls.relowner) AS "owner" from pg_catalog.pg_foreign_table ft left outer join pg_catalog.pg_foreign_server srv on ft.ftserver = srv.oid join pg_catalog.pg_class cls on ft.ftrelid = cls.oid where cls.relnamespace = ?::oid and pg_catalog.age(ft.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) order by table_id;

Times Reported Time consuming queries #3

Day	Hour	Count	Duration	Avg duration
Dec 18	18	2	0ms	0ms

4

0ms

10

Details

0ms

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

Times Reported Time consuming queries #4

Day	Hour	Count	Duration	Avg duration
Dec 18	18	10	0ms	0ms

5

0ms

2,276

Details

0ms

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

Times Reported Time consuming queries #5

Day	Hour	Count	Duration	Avg duration
Dec 18	18	2,276	0ms	0ms

6

0ms

2

Details

0ms

select ind_head.indexrelid index_id, k col_idx, k <= indnkeyatts in_key, ind_head.indkey[k - 1] column_position, ind_head.indoption[k - 1] column_options, ind_head.indcollation[k - 1] as collation, colln.nspname as collation_schema, collname as collation_str, ind_head.indclass[k - 1] as opclass, case when opcdefault then null else opcn.nspname end as opclass_schema, case when opcdefault then null else opcname end as opclass_str, case when indexprs is null then null when ind_head.indkey[k - 1] = ? then chr(?) || pg_catalog.pg_get_indexdef(ind_head.indexrelid, k::int, true) else pg_catalog.pg_get_indexdef(ind_head.indexrelid, k::int, true) end as expression, amcanorder can_order from pg_catalog.pg_index ind_head join pg_catalog.pg_class ind_stor on ind_stor.oid = ind_head.indexrelid cross join unnest(ind_head.indkey) with ordinality u (u, k) left join pg_catalog.pg_collation on pg_collation.oid = ind_head.indcollation[k - 1] left join pg_catalog.pg_namespace colln on collnamespace = colln.oid cross join pg_catalog.pg_indexam_has_property(ind_stor.relam, ?) amcanorder left join pg_catalog.pg_opclass on pg_opclass.oid = ind_head.indclass[k - 1] left join pg_catalog.pg_namespace opcn on opcnamespace = opcn.oid where ind_stor.relnamespace = ?::oid and ind_stor.relkind in (...) and pg_catalog.age(ind_stor.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) order by index_id, k;

Times Reported Time consuming queries #6

Day	Hour	Count	Duration	Avg duration
Dec 18	18	2	0ms	0ms

7

0ms

48

Details

0ms

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

Times Reported Time consuming queries #7

Day	Hour	Count	Duration	Avg duration
Dec 18	18	48	0ms	0ms

8

0ms

4

Details

0ms

select updaterelevantforrelevantresults ();

Times Reported Time consuming queries #8

Day	Hour	Count	Duration	Avg duration
Dec 18	18	4	0ms	0ms

9

0ms

1

Details

0ms

select distinct connamespace as schema_id from pg_catalog.pg_constraint f, pg_catalog.pg_class o where f.contype = ? and f.confrelid = o.oid and o.relnamespace in (...);

Times Reported Time consuming queries #9

Day	Hour	Count	Duration	Avg duration
Dec 18	18	1	0ms	0ms

10

0ms

3

Details

0ms

select oid from pg_catalog.pg_foreign_data_wrapper;

Times Reported Time consuming queries #10

Day	Hour	Count	Duration	Avg duration
Dec 18	18	3	0ms	0ms

11

0ms

2

Details

0ms

select t.oid as type_id, t.xmin as type_state_number, t.typname as type_name, t.typtype as type_sub_kind, t.typcategory as type_category, t.typrelid as class_id, t.typbasetype as base_type_id, case when t.typtype in (...) then null else pg_catalog.format_type(t.typbasetype, t.typtypmod) end as type_def, t.typndims as dimensions_number, t.typdefault as default_expression, t.typnotnull as mandatory, pg_catalog.pg_get_userbyid(t.typowner) AS "owner" from pg_catalog.pg_type t left outer join pg_catalog.pg_class c on t.typrelid = c.oid where t.typnamespace = ?::oid and pg_catalog.age(t.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) and (t.typtype in (...) or c.relkind = ?::"char" or (t.typtype = ? and (t.typelem = ? or t.typcategory <> ?)) or t.typtype = ? and not t.typisdefined) order by ?;

Times Reported Time consuming queries #11

Day	Hour	Count	Duration	Avg duration
Dec 18	18	2	0ms	0ms

12

0ms

2

Details

0ms

select t.relkind as table_kind, t.relname as table_name, t.oid as table_id, t.xmin as table_state_number, false as table_with_oids, t.reltablespace as tablespace_id, t.reloptions as options, t.relpersistence as persistence, ( select pg_catalog.array_agg(inhparent::bigint order by inhseqno)::varchar from pg_catalog.pg_inherits where t.oid = inhrelid) as ancestors, ( select pg_catalog.array_agg(inhrelid::bigint order by inhrelid)::varchar from pg_catalog.pg_inherits where t.oid = inhparent) as successors, t.relispartition as is_partition, pg_catalog.pg_get_partkeydef (t.oid) as partition_key, pg_catalog.pg_get_expr(t.relpartbound, t.oid) as partition_expression, t.relam am_id, pg_catalog.pg_get_userbyid(t.relowner) AS "owner" from pg_catalog.pg_class t where relnamespace = ?::oid and relkind in (...) and pg_catalog.age(t.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) order by table_kind, table_id;

Times Reported Time consuming queries #12

Day	Hour	Count	Duration	Avg duration
Dec 18	18	2	0ms	0ms

13

0ms

1

Details

0ms

select count(*) as total_records from ourfavourites_findlatest_kl_base where "brokerid" = ?;

Times Reported Time consuming queries #13

Day	Hour	Count	Duration	Avg duration
Dec 18	18	1	0ms	0ms

14

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 #14

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

15

0ms

373

Details

0ms

commit;

Times Reported Time consuming queries #15

Day	Hour	Count	Duration	Avg duration
Dec 18	18	373	0ms	0ms

16

0ms

452

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 #16

Day	Hour	Count	Duration	Avg duration
Dec 18	18	452	0ms	0ms

17

0ms

1

Details

0ms

select e.oid as id, e.xmin as state_number, extname as name, extversion as version, extnamespace as schema_id, nspname as schema_name, array ( select unnest from unnest(available_versions) where unnest > extversion) as available_updates from pg_catalog.pg_extension e join pg_namespace n on e.extnamespace = n.oid left join ( select name, array_agg(version) as available_versions from pg_available_extension_versions() group by name) v on e.extname = v.name where pg_catalog.age(e.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?);

Times Reported Time consuming queries #17

Day	Hour	Count	Duration	Avg duration
Dec 18	18	1	0ms	0ms

18

0ms

240

Details

0ms

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

Times Reported Time consuming queries #18

Day	Hour	Count	Duration	Avg duration
Dec 18	18	240	0ms	0ms

19

0ms

1

Details

0ms

select a.oid as access_method_id, a.xmin as state_number, a.amname as access_method_name, a.amhandler::oid as handler_id, pg_catalog.quote_ident(n.nspname) || ? || pg_catalog.quote_ident(p.proname) as handler_name, a.amtype as access_method_type from pg_am a join pg_proc p on a.amhandler::oid = p.oid join pg_namespace n on p.pronamespace = n.oid where pg_catalog.age(a.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?);

Times Reported Time consuming queries #19

Day	Hour	Count	Duration	Avg duration
Dec 18	18	1	0ms	0ms

20

0ms

1

Details

0ms

select t.oid as object_id, t.spcacl as acl from pg_catalog.pg_tablespace t union all select t.oid as object_id, t.datacl as acl from pg_catalog.pg_database t;

Times Reported Time consuming queries #20

Day	Hour	Count	Duration	Avg duration
Dec 18	18	1	0ms	0ms

Time consuming prepare


Date: 2025-12-18 18:57:17
Duration: 26ms
Database: postgres
Date: 2025-12-18 18:42:10
Duration: 17ms
Database: postgres
Date: 2025-12-18 18:02:28
Duration: 18ms
Database: postgres
Date: 2025-12-18 18:31:43
Duration: 11ms
Database: postgres
Date: 2025-12-18 18:00:33
Duration: 3ms
Database: postgres
Date: 2025-12-18 18:02:36
Duration: 3ms
Database: postgres
Date: 2025-12-18 18:51:21
Duration: 10ms
Database: postgres
Date: 2025-12-18 18:30:04
Duration: 5ms
Database: postgres
Date: 2025-12-18 18:47:25
Duration: 3ms
Database: postgres
Date: 2025-12-18 18:01:44
Duration: 0ms
Database: postgres
Date: 2025-12-18 18:32:02
Duration: 5ms
Database: postgres
Date: 2025-12-18 18:21:01
Duration: 7ms
Database: postgres
Date: 2025-12-18 18:11:49
Duration: 0ms
Database: postgres
Date: 2025-12-18 18:36:44
Duration: 6ms
Database: postgres
Date: 2025-12-18 18:00:04
Duration: 3ms
Database: postgres
Date: 2025-12-18 18:12:26
Duration: 1ms
Database: postgres
Date: 2025-12-18 18:11:45
Duration: 3ms
Database: postgres
Date: 2025-12-18 18:20:03
Duration: 2ms
Database: postgres
Date: 2025-12-18 18:10:03
Duration: 0ms
Database: postgres
Date: 2025-12-18 18:41:20
Duration: 2ms
Database: postgres

Time consuming bind

Rank

Total duration

Times executed

Min duration

Max duration

Avg duration

Query

1

1m48s

140,622

Details

0ms

47ms

0ms

SELECT ;

Times Reported Time consuming bind #1

Day	Hour	Count	Duration	Avg duration
Dec 18	18	140,620	1m48s	0ms
	19	2	0ms	0ms

SELECT ;

Date: 2025-12-18 18:00:03 Duration: 47ms Database: postgres parameters: $1 = '558', $2 = '0', $3 = '0', $4 = 'AUDSGD', $5 = 'AUDSGD'
SELECT ;

Date: 2025-12-18 18:20:35 Duration: 32ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840249414796300'
SELECT ;

Date: 2025-12-18 18:02:49 Duration: 30ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840233385428300'

2

1m33s

13,803

Details

0ms

63ms

6ms

WITH rar_max as ( ;

Times Reported Time consuming bind #2

Day	Hour	Count	Duration	Avg duration
	18	13,803	1m33s	6ms

WITH rar_max as ( ;

Date: 2025-12-18 18:56:52 Duration: 63ms Database: postgres parameters: $1 = '558', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '160', $13 = 'AUDSGD', $14 = 'CHFSGD', $15 = 'EURDKK', $16 = 'EURHKD', $17 = 'EURNOK', $18 = 'EURPLN', $19 = 'EURSEK', $20 = 'EURSGD', $21 = 'EURTRY', $22 = 'EURZAR', $23 = 'GBPDKK', $24 = 'GBPNOK', $25 = 'GBPSEK', $26 = 'GBPSGD', $27 = 'NOKJPY', $28 = 'NOKSEK', $29 = 'SEKJPY', $30 = 'SGDJPY', $31 = 'USDCNH', $32 = 'USDCZK', $33 = 'USDDKK', $34 = 'USDHKD', $35 = 'USDHUF', $36 = 'USDMXN', $37 = 'USDNOK', $38 = 'USDPLN', $39 = 'USDRUB', $40 = 'USDSEK', $41 = 'USDTHB', $42 = 'USDTRY', $43 = 'USDZAR', $44 = 'AUDUSD', $45 = 'EURUSD', $46 = 'GBPUSD', $47 = 'USDCAD', $48 = 'USDCHF', $49 = 'USDJPY', $50 = 'AUDCAD', $51 = 'AUDCHF', $52 = 'AUDJPY', $53 = 'AUDNZD', $54 = 'CADCHF', $55 = 'CADJPY', $56 = 'CHFJPY', $57 = 'EURAUD', $58 = 'EURCAD', $59 = 'EURCHF', $60 = 'EURGBP', $61 = 'EURJPY', $62 = 'EURNZD', $63 = 'GBPAUD', $64 = 'GBPCAD', $65 = 'GBPCHF', $66 = 'GBPJPY', $67 = 'GBPNZD', $68 = 'NZDCAD', $69 = 'NZDCHF', $70 = 'NZDJPY', $71 = 'NZDUSD', $72 = 'USDSGD', $73 = 'AUS200', $74 = 'DE30', $75 = 'ES35', $76 = 'F40', $77 = 'HK50', $78 = 'IT40', $79 = 'JP225', $80 = 'STOXX50', $81 = 'UK100', $82 = 'US2000', $83 = 'US30', $84 = 'US500', $85 = 'CHINA50', $86 = 'USTEC', $87 = 'XAGEUR', $88 = 'XAGUSD', $89 = 'XAUUSD', $90 = 'XAUEUR', $91 = 'XPDUSD', $92 = 'XPTUSD', $93 = 'AUDSGD', $94 = 'CHFSGD', $95 = 'EURDKK', $96 = 'EURHKD', $97 = 'EURNOK', $98 = 'EURPLN', $99 = 'EURSEK', $100 = 'EURSGD', $101 = 'EURTRY', $102 = 'EURZAR', $103 = 'GBPDKK', $104 = 'GBPNOK', $105 = 'GBPSEK', $106 = 'GBPSGD', $107 = 'NOKJPY', $108 = 'NOKSEK', $109 = 'SEKJPY', $110 = 'SGDJPY', $111 = 'USDCNH', $112 = 'USDCZK', $113 = 'USDDKK', $114 = 'USDHKD', $115 = 'USDHUF', $116 = 'USDMXN', $117 = 'USDNOK', $118 = 'USDPLN', $119 = 'USDRUB', $120 = 'USDSEK', $121 = 'USDTHB', $122 = 'USDTRY', $123 = 'USDZAR', $124 = 'AUDUSD', $125 = 'EURUSD', $126 = 'GBPUSD', $127 = 'USDCAD', $128 = 'USDCHF', $129 = 'USDJPY', $130 = 'AUDCAD', $131 = 'AUDCHF', $132 = 'AUDJPY', $133 = 'AUDNZD', $134 = 'CADCHF', $135 = 'CADJPY', $136 = 'CHFJPY', $137 = 'EURAUD', $138 = 'EURCAD', $139 = 'EURCHF', $140 = 'EURGBP', $141 = 'EURJPY', $142 = 'EURNZD', $143 = 'GBPAUD', $144 = 'GBPCAD', $145 = 'GBPCHF', $146 = 'GBPJPY', $147 = 'GBPNZD', $148 = 'NZDCAD', $149 = 'NZDCHF', $150 = 'NZDJPY', $151 = 'NZDUSD', $152 = 'USDSGD', $153 = 'AUS200', $154 = 'DE30', $155 = 'ES35', $156 = 'F40', $157 = 'HK50', $158 = 'IT40', $159 = 'JP225', $160 = 'STOXX50', $161 = 'UK100', $162 = 'US2000', $163 = 'US30', $164 = 'US500', $165 = 'CHINA50', $166 = 'USTEC', $167 = 'XAGEUR', $168 = 'XAGUSD', $169 = 'XAUUSD', $170 = 'XAUEUR', $171 = 'XPDUSD', $172 = 'XPTUSD', $173 = '700', $174 = '700', $175 = 't', $176 = '10', $177 = '10'
WITH rar_max as ( ;

Date: 2025-12-18 18:51:15 Duration: 58ms Database: postgres parameters: $1 = '607345736198978303', $2 = '607345736198978303', $3 = '607345736198978303'
WITH rar_max as ( ;

Date: 2025-12-18 18:21:33 Duration: 51ms Database: postgres parameters: $1 = 't', $2 = '621', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '1', $14 = 'EURUSD', $15 = '0', $16 = '', $17 = '0', $18 = '0', $19 = '0', $20 = '0', $21 = '0', $22 = 't', $23 = '10', $24 = '10'

3

3s422ms

144,763

Details

0ms

12ms

0ms

select 1;

Times Reported Time consuming bind #3

Day	Hour	Count	Duration	Avg duration
	18	144,760	3s422ms	0ms
	19	3	0ms	0ms

select 1;

Date: 2025-12-18 18:21:40 Duration: 12ms Database: postgres
select 1;

Date: 2025-12-18 18:26:43 Duration: 11ms Database: postgres
select 1;

Date: 2025-12-18 18:47:44 Duration: 10ms Database: postgres

4

2s801ms

1,403

Details

0ms

12ms

1ms

SELECT symbolid, ;

Times Reported Time consuming bind #4

Day	Hour	Count	Duration	Avg duration
	18	1,403	2s801ms	1ms

SELECT symbolid, ;

Date: 2025-12-18 18:31:14 Duration: 12ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'USDJPY.ID', $4 = 'USDJPY.FX'
SELECT symbolid, ;

Date: 2025-12-18 18:31:36 Duration: 12ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'GTi12', $4 = 'GBPUSD'
SELECT symbolid, ;

Date: 2025-12-18 18:01:58 Duration: 11ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'GBPJPY', $4 = 'GBPJPY.FX', $5 = 'GBPJPY.ID'

5

1s324ms

838

Details

1ms

9ms

1ms

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

Times Reported Time consuming bind #5

Day	Hour	Count	Duration	Avg duration
	18	838	1s324ms	1ms

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

Date: 2025-12-18 18:16:16 Duration: 9ms Database: postgres parameters: $1 = 'ATFX'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2025-12-18 18:01:26 Duration: 5ms Database: postgres parameters: $1 = 'PEPPERSTONEMT5'
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;

Date: 2025-12-18 18:01:28 Duration: 3ms Database: postgres parameters: $1 = 'BDSWISS'

6

809ms

94

Details

4ms

28ms

8ms

WITH last_candle AS ( ;

Times Reported Time consuming bind #6

Day	Hour	Count	Duration	Avg duration
	18	94	809ms	8ms

WITH last_candle AS ( ;

Date: 2025-12-18 18:32:03 Duration: 28ms Database: postgres parameters: $1 = '538', $2 = '538'
WITH last_candle AS ( ;

Date: 2025-12-18 18:52:02 Duration: 28ms Database: postgres parameters: $1 = '558', $2 = '558'
WITH last_candle AS ( ;

Date: 2025-12-18 18:32:02 Duration: 28ms Database: postgres parameters: $1 = '558', $2 = '558'

7

712ms

70

Details

0ms

25ms

10ms

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

Times Reported Time consuming bind #7

Day	Hour	Count	Duration	Avg duration
	18	70	712ms	10ms

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

Date: 2025-12-18 18:12:26 Duration: 25ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;

Date: 2025-12-18 18:32:03 Duration: 21ms Database: postgres parameters: $1 = '489', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;

Date: 2025-12-18 18:34:03 Duration: 20ms Database: postgres parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'

8

531ms

23

Details

0ms

45ms

23ms

with wh_patitioned as ( ;

Times Reported Time consuming bind #8

Day	Hour	Count	Duration	Avg duration
	18	23	531ms	23ms

with wh_patitioned as ( ;

Date: 2025-12-18 18:41:23 Duration: 45ms 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: 2025-12-18 18:41:20 Duration: 44ms 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: 2025-12-18 18:17:13 Duration: 44ms Database: postgres parameters: $1 = '621', $2 = '621', $3 = '621', $4 = '621', $5 = '621', $6 = '621', $7 = '621', $8 = '621', $9 = '621'

9

318ms

6,389

Details

0ms

2ms

0ms

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

Times Reported Time consuming bind #9

Day	Hour	Count	Duration	Avg duration
	18	6,389	318ms	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: 2025-12-18 18:00:43 Duration: 2ms Database: postgres parameters: $1 = '2025-12-18 18:30:00', $2 = '7.415e-06', $3 = '7.465e-06', $4 = '7.355e-06', $5 = '7.44e-06', $6 = '265', $7 = '515840249472059300', $8 = '0', $9 = '2025-12-18 18:00:43.325', $10 = '2025-12-18 18:00:43.221', $11 = '7.415e-06', $12 = '7.465e-06', $13 = '7.355e-06', $14 = '7.44e-06', $15 = '265', $16 = '0', $17 = '2025-12-18 18:00:43.325', $18 = '2025-12-18 18:00:43.221'
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: 2025-12-18 18:01:44 Duration: 0ms Database: postgres parameters: $1 = '2025-12-18 17:45:00', $2 = '1.771905', $3 = '1.773235', $4 = '1.77178', $5 = '1.77258', $6 = '1920', $7 = '515840230459049300', $8 = '0', $9 = '2025-12-18 18:01:44.636', $10 = '2025-12-18 18:01:42.545', $11 = '1.771905', $12 = '1.773235', $13 = '1.77178', $14 = '1.77258', $15 = '1920', $16 = '0', $17 = '2025-12-18 18:01:44.636', $18 = '2025-12-18 18:01:42.545'
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: 2025-12-18 18:41:58 Duration: 0ms Database: postgres parameters: $1 = '2025-12-18 18:15:00', $2 = '48306.55', $3 = '48334', $4 = '48265.7', $5 = '48289', $6 = '7526', $7 = '515840248000537300', $8 = '0', $9 = '2025-12-18 18:41:58.972', $10 = '2025-12-18 18:41:58.828', $11 = '48306.55', $12 = '48334', $13 = '48265.7', $14 = '48289', $15 = '7526', $16 = '0', $17 = '2025-12-18 18:41:58.972', $18 = '2025-12-18 18:41:58.828'

10

305ms

3,519

Details

0ms

3ms

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
	18	3,519	305ms	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: 2025-12-18 18:30:36 Duration: 3ms Database: postgres parameters: $1 = '2025-12-18 18:00:00', $2 = '1.17262', $3 = '1.17452', $4 = '1.17252', $5 = '1.17372', $6 = '8926', $7 = '515840245852399300', $8 = '0', $9 = '2025-12-18 18:30:36.31', $10 = '2025-12-18 18:30:36.31', $11 = '1.17262', $12 = '1.17452', $13 = '1.17252', $14 = '1.17372', $15 = '8926', $16 = '0', $17 = '2025-12-18 18:30:36.31', $18 = '2025-12-18 18:30:36.31'
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: 2025-12-18 18:30:59 Duration: 0ms Database: postgres parameters: $1 = '2025-12-18 18:00:00', $2 = '387.505', $3 = '387.605', $4 = '387.125', $5 = '387.425', $6 = '2996', $7 = '515840243930982300', $8 = '0', $9 = '2025-12-18 18:30:59.787', $10 = '2025-12-18 18:30:59.786', $11 = '387.505', $12 = '387.605', $13 = '387.125', $14 = '387.425', $15 = '2996', $16 = '0', $17 = '2025-12-18 18:30:59.787', $18 = '2025-12-18 18:30:59.786'
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: 2025-12-18 18:00:34 Duration: 0ms Database: postgres parameters: $1 = '2025-12-18 17:30:00', $2 = '1.17224', $3 = '1.17312', $4 = '1.17151', $5 = '1.17263', $6 = '11279', $7 = '515840245852399300', $8 = '0', $9 = '2025-12-18 18:00:34.897', $10 = '2025-12-18 18:00:34.866', $11 = '1.17224', $12 = '1.17312', $13 = '1.17151', $14 = '1.17263', $15 = '11279', $16 = '0', $17 = '2025-12-18 18:00:34.897', $18 = '2025-12-18 18:00:34.866'

11

282ms

8

Details

27ms

44ms

35ms

with sym_info as ( ;

Times Reported Time consuming bind #11

Day	Hour	Count	Duration	Avg duration
	18	8	282ms	35ms

with sym_info as ( ;

Date: 2025-12-18 18:36:44 Duration: 44ms 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: 2025-12-18 18:06:42 Duration: 44ms 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: 2025-12-18 18:36:55 Duration: 43ms Database: postgres parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'

12

211ms

2,276

Details

0ms

2ms

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
	18	2,276	211ms	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: 2025-12-18 18:01:31 Duration: 2ms Database: postgres parameters: $1 = '2025-12-17 22:00:00', $2 = '147.25', $3 = '147.405', $4 = '146.77', $5 = '146.985', $6 = '1407', $7 = '515840249417025300', $8 = '0', $9 = '2025-12-18 18:01:31.07', $10 = '2025-12-18 18:01:31.069', $11 = '147.25', $12 = '147.405', $13 = '146.77', $14 = '146.985', $15 = '1407', $16 = '0', $17 = '2025-12-18 18:01:31.07', $18 = '2025-12-18 18:01:31.069'
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: 2025-12-18 18:00:55 Duration: 0ms Database: postgres parameters: $1 = '2025-12-18 17:00:00', $2 = '49360.1', $3 = '49540.1', $4 = '49222.6', $5 = '49435.1', $6 = '5385', $7 = '515840232462312300', $8 = '0', $9 = '2025-12-18 18:00:55.348', $10 = '2025-12-18 18:00:55.348', $11 = '49360.1', $12 = '49540.1', $13 = '49222.6', $14 = '49435.1', $15 = '5385', $16 = '0', $17 = '2025-12-18 18:00:55.348', $18 = '2025-12-18 18:00:55.348'
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: 2025-12-18 18:11:58 Duration: 0ms Database: postgres parameters: $1 = '2025-12-18 17:00:00', $2 = '48229.25', $3 = '48370', $4 = '48077.4', $5 = '48343', $6 = '30630', $7 = '515840248000890300', $8 = '0', $9 = '2025-12-18 18:11:58.979', $10 = '2025-12-18 18:11:58.802', $11 = '48229.25', $12 = '48370', $13 = '48077.4', $14 = '48343', $15 = '30630', $16 = '0', $17 = '2025-12-18 18:11:58.979', $18 = '2025-12-18 18:11:58.802'

13

139ms

26,151

Details

0ms

5ms

0ms

SET application_name = 'PostgreSQL JDBC Driver';

Times Reported Time consuming bind #13

Day	Hour	Count	Duration	Avg duration
	18	26,151	139ms	0ms

SET application_name = 'PostgreSQL JDBC Driver';

Date: 2025-12-18 18:49:15 Duration: 5ms Database: postgres
SET application_name = 'PostgreSQL JDBC Driver';

Date: 2025-12-18 18:17:04 Duration: 3ms Database: postgres
SET application_name = 'PostgreSQL JDBC Driver';

Date: 2025-12-18 18:35:10 Duration: 3ms Database: postgres

14

129ms

26,181

Details

0ms

2ms

0ms

SET extra_float_digits = 3;

Times Reported Time consuming bind #14

Day	Hour	Count	Duration	Avg duration
	18	26,181	129ms	0ms

SET extra_float_digits = 3;

Date: 2025-12-18 18:22:06 Duration: 2ms Database: postgres
SET extra_float_digits = 3;

Date: 2025-12-18 18:56:24 Duration: 1ms Database: postgres
SET extra_float_digits = 3;

Date: 2025-12-18 18:27:05 Duration: 1ms Database: postgres

15

111ms

181

Details

0ms

1ms

0ms

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

Times Reported Time consuming bind #15

Day	Hour	Count	Duration	Avg duration
	18	181	111ms	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: 2025-12-18 18:11:46 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: 2025-12-18 18:11:49 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: 2025-12-18 18:11:47 Duration: 1ms Database: postgres

16

88ms

1

Details

88ms

select * from ourfavourites_findlatest_ekl_base where "brokerid" = 621 LIMIT 1000 OFFSET 0;

Times Reported Time consuming bind #16

Day	Hour	Count	Duration	Avg duration
	18	1	88ms	88ms

select * from ourfavourites_findlatest_ekl_base where "brokerid" = 621 LIMIT 1000 OFFSET 0;

Date: 2025-12-18 18:17:40 Duration: 88ms Database: postgres

17

69ms

1

Details

69ms

select * from ourfavourites_findlatest_cp_base where "brokerid" = 621 LIMIT 1000 OFFSET 0;

Times Reported Time consuming bind #17

Day	Hour	Count	Duration	Avg duration
	18	1	69ms	69ms

select * from ourfavourites_findlatest_cp_base where "brokerid" = 621 LIMIT 1000 OFFSET 0;

Date: 2025-12-18 18:17:38 Duration: 69ms Database: postgres

18

65ms

1

Details

65ms

select * from ourfavourites_findlatest_kl_base where "brokerid" = 621 LIMIT 1000 OFFSET 0;

Times Reported Time consuming bind #18

Day	Hour	Count	Duration	Avg duration
	18	1	65ms	65ms

select * from ourfavourites_findlatest_kl_base where "brokerid" = 621 LIMIT 1000 OFFSET 0;

Date: 2025-12-18 18:17:39 Duration: 65ms Database: postgres

19

61ms

61

Details

0ms

1ms

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

Times Reported Time consuming bind #19

Day	Hour	Count	Duration	Avg duration
	18	61	61ms	1ms

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

Date: 2025-12-18 18:50:35 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'USDSGD', $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: 2025-12-18 18:02:43 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'XAUUSD.a', $3 = '558'
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;

Date: 2025-12-18 18:32:03 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'USTEC', $3 = '558'

20

61ms

11

Details

4ms

6ms

5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Times Reported Time consuming bind #20

Day	Hour	Count	Duration	Avg duration
	18	11	61ms	5ms

SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2025-12-18 18:31:36 Duration: 6ms Database: postgres parameters: $1 = '689', $2 = '689'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2025-12-18 18:12:01 Duration: 6ms Database: postgres parameters: $1 = '958', $2 = '958'
SELECT DISTINCT ON (basegroupname, symbol) ;

Date: 2025-12-18 18:31:43 Duration: 5ms Database: postgres parameters: $1 = '667', $2 = '667'

Log levels

Key values

1,764,591 Log entries

Chart
Table

Type	Count	Percentage
CONTEXT	413	0.02%
DETAIL	342,305	19.40%
LOG	1,421,316	80.55%
STATEMENT	557	0.03%

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

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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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General Activity

Connections

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Temporary Files

Size of temporary files

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Temporary Files Activity

Queries generating the most temporary files (N)

Queries generating the largest temporary files

Vacuums

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Analyzes per table

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Tuples removed per table

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Pages removed per table

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Autovacuum Activity

Locks

Locks by types

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Type of locks

Most frequent waiting queries (N)

Queries that waited the most

Queries

Queries by type

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Queries by database

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Queries by user

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Duration by user