-
Global information
- Generated on Mon Feb 16 09:59:40 2026
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-02-16_110000.log
- Parsed 1,584,915 log entries in 39s
- Log start from 2026-02-16 11:00:00 to 2026-02-16 11:59:38
-
Overview
Global Stats
- 366 Number of unique normalized queries
- 188,447 Number of queries
- 1h49m53s Total query duration
- 2026-02-16 11:00:00 First query
- 2026-02-16 11:59:38 Last query
- 4,708 queries/s at 2026-02-16 11:00:04 Query peak
- 1h49m53s Total query duration
- 7s1ms Prepare/parse total duration
- 44s889ms Bind total duration
- 1h49m1s Execute total duration
- 3 Number of events
- 2 Number of unique normalized events
- 2 Max number of times the same event was reported
- 0 Number of cancellation
- 38 Total number of automatic vacuums
- 56 Total number of automatic analyzes
- 893 Number temporary file
- 137.05 MiB Max size of temporary file
- 6.32 MiB Average size of temporary file
- 2,945 Total number of sessions
- 12 sessions at 2026-02-16 11:58:08 Session peak
- 3d4h17m46s Total duration of sessions
- 1m33s Average duration of sessions
- 63 Average queries per session
- 2s238ms Average queries duration per session
- 1m31s Average idle time per session
- 2,943 Total number of connections
- 28 connections/s at 2026-02-16 11:48:48 Connection peak
- 3 Total number of databases
SQL Traffic
Key values
- 4,708 queries/s Query Peak
- 2026-02-16 11:00:04 Date
SELECT Traffic
Key values
- 2,334 queries/s Query Peak
- 2026-02-16 11:00:04 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 214 queries/s Query Peak
- 2026-02-16 11:01:51 Date
Queries duration
Key values
- 1h49m53s 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
↑ Back to the top of the General Activity tableDay Hour Count Min duration Max duration Avg duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Feb 16 11 188,447 0ms 24s775ms 34ms 4m51s 5m13s 5m37s Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Feb 16 11 58,919 26 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Feb 16 11 23,720 2,570 17 96 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Feb 16 11 19,262 67,825 3.52 21.46% Day Hour Count Average / Second Feb 16 11 2,943 0.82/s Day Hour Count Average Duration Average idle time Feb 16 11 2,945 1m33s 1m31s -
Connections
Established Connections
Key values
- 28 connections Connection Peak
- 2026-02-16 11:48:48 Date
Connections per database
Key values
- acaweb_fx Main Database
- 2,943 connections Total
Connections per user
Key values
- postgres Main User
- 2,943 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 1259 connections
- 2,943 Total connections
Host Count 127.0.0.1 111 192.168.0.114 5 192.168.0.171 2 192.168.0.216 103 192.168.0.74 176 192.168.1.127 69 192.168.1.145 75 192.168.1.15 182 192.168.1.20 81 192.168.1.239 15 192.168.1.90 65 192.168.2.126 43 192.168.2.182 12 192.168.3.199 36 192.168.4.127 1 192.168.4.142 1,259 192.168.4.150 10 192.168.4.176 30 192.168.4.238 8 192.168.4.33 74 192.168.4.37 4 192.168.4.42 4 192.168.4.98 330 52.214.24.33 3 [local] 245 -
Sessions
Simultaneous sessions
Key values
- 12 sessions Session Peak
- 2026-02-16 11:58:08 Date
Histogram of session times
Key values
- 2,448 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 2,945 sessions Total
Sessions per user
Key values
- postgres Main User
- 2,945 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 2,945 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 111 14s733ms 132ms 182.165.1.54 1 1h44m43s 1h44m43s 192.168.0.114 5 30m21s 6m4s 192.168.0.216 103 1m42s 999ms 192.168.0.74 176 10h59m7s 3m44s 192.168.1.127 69 15s15ms 217ms 192.168.1.145 76 10h27m28s 8m15s 192.168.1.15 183 12h17m5s 4m1s 192.168.1.20 82 19h44m50s 14m26s 192.168.1.239 15 94ms 6ms 192.168.1.90 65 39s137ms 602ms 192.168.2.126 43 12s653ms 294ms 192.168.2.182 12 1s316ms 109ms 192.168.3.199 36 1s589ms 44ms 192.168.4.127 1 175ms 175ms 192.168.4.142 1,259 6m52s 327ms 192.168.4.150 10 20h13m59s 2h1m23s 192.168.4.176 30 12s669ms 422ms 192.168.4.238 8 10s431ms 1s303ms 192.168.4.33 74 2m42s 2s191ms 192.168.4.37 4 40ms 10ms 192.168.4.42 4 20s385ms 5s96ms 192.168.4.98 330 15s870ms 48ms 52.214.24.33 3 3m1s 1m [local] 245 3m27s 845ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 10,871 buffers Checkpoint Peak
- 2026-02-16 11:36:53 Date
- 209.935 seconds Highest write time
- 0.015 seconds Sync time
Checkpoints Wal files
Key values
- 6 files Wal files usage Peak
- 2026-02-16 11:06:53 Date
Checkpoints distance
Key values
- 193.29 Mo Distance Peak
- 2026-02-16 11:06:53 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Feb 16 11 44,124 1,909.218s 0.054s 1,909.567s Day Hour Added Removed Recycled Synced files Longest sync Average sync Feb 16 11 0 0 24 1,868 0.011s 0s Day Hour Count Avg time (sec) Feb 16 11 0 0s Day Hour Mean distance Mean estimate Feb 16 11 32,759.92 kB 73,530.58 kB -
Temporary Files
Size of temporary files
Key values
- 182.04 MiB Temp Files size Peak
- 2026-02-16 11:00:07 Date
Number of temporary files
Key values
- 62 per second Temp Files Peak
- 2026-02-16 11:02:11 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Feb 16 11 893 5.52 GiB 6.32 MiB Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 61 266.52 MiB 4.36 MiB 4.39 MiB 4.37 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, $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, $323)) AND ($324 = 0 OR fr.pattern in ($325)) AND ($326 = 0 OR fr.patternlengthbars <= $327) AND ($328 = 0 OR ($329 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($330 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $331 OR relevant = 1) AND ($332 = 0 OR age <= $333) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2026-02-16 11:00:45 Duration: 0ms
2 28 1.65 GiB 3.83 MiB 118.72 MiB 60.37 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2026-02-16 11:10:08 Duration: 0ms
3 18 62.23 MiB 3.45 MiB 3.46 MiB 3.46 MiB jr.resultuid as resultuid, jr.direction as direction, jr.patternendtime as identified, jr.patternlengthbars as length, jr.patternstarttime as patternstarttime, case when jr.trendchangeid = ? then ? else ? end as trendchange, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, jp.patternname as pattern_name, dtt.timezone as timezone, ? as age, cps.pip, g.basegroupname from japsticks_results jr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = jr.symbolid inner join relevance_japsticks_results rar on rar.resultuid = jr.resultuid inner join symbols s on jr.symbolid = s.symbolid and s.nonliquid = ? inner join japsticks_patterns jp on jr.patternid = jp.id inner join downloadersymbolsettings dss on jr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where jr.gmttimefound > now() - interval ? and s.deleted = ? and (jr.simulation = ? or jr.simulation is null) and (rar.relevant = ?) --and (semicolon_age = ? or rar.age <= semicolon_age) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or jp.patternname in (...)) and (? = ? or jr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results order by symbolid, resultuid ) select * from results order by identified desc, length desc ;-
jr.resultuid AS resultuid, jr.direction AS direction, jr.patternendtime AS identified, jr.patternlengthbars AS length, jr.patternstarttime AS patternstarttime, case when jr.trendchangeid = 1 then 'Continuation' else 'Reversal' end AS trendchange, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, jp.patternname AS pattern_name, dtt.timezone AS timezone, 0 AS age, cps.pip, g.basegroupname FROM japsticks_results jr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = jr.symbolid INNER JOIN relevance_japsticks_results rar ON rar.resultuid = jr.resultuid INNER JOIN symbols s ON jr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN japsticks_patterns jp ON jr.patternid = jp.id INNER JOIN downloadersymbolsettings dss ON jr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE jr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (jr.simulation = 0 OR jr.simulation IS NULL) AND (rar.relevant = 1) --AND (semicolon_age = 0 OR rar.age <= semicolon_age) AND ($2 = 0 OR s.timegranularity in ($3)) AND ($4 = 0 OR s.exchange in ($5)) AND ($6 = 0 OR coalesce(bim.code, s.symbol) in ($7)) AND ($8 = 0 OR jp.patternname in ($9)) AND ($10 = 0 OR jr.patternlengthbars <= $11)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2026-02-16 11:02:52 Duration: 0ms
4 16 738.25 MiB 46.14 MiB 46.14 MiB 46.14 MiB update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2026-02-16 11:01:13 Duration: 0ms
5 16 1.22 GiB 78.33 MiB 78.33 MiB 78.33 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2026-02-16 11:01:17 Duration: 0ms
6 16 49.40 MiB 3.08 MiB 3.10 MiB 3.09 MiB select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ?), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?)), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;-
SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ($2 = 0 OR s.timegranularity in ($3, $4, $5, $6, $7, $8, $9)) AND ($10 = 0 OR s.exchange in ($11)) AND ($12 = 0 OR coalesce(bim.code, s.symbol) in ($13, $14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226, $227, $228, $229, $230, $231, $232, $233, $234, $235, $236, $237, $238, $239, $240, $241, $242, $243, $244, $245, $246, $247, $248, $249, $250, $251, $252, $253, $254, $255, $256, $257, $258, $259, $260, $261, $262, $263, $264, $265, $266, $267, $268, $269, $270, $271, $272, $273, $274, $275, $276, $277, $278, $279, $280, $281, $282, $283, $284, $285, $286, $287, $288, $289, $290, $291, $292, $293, $294, $295, $296, $297, $298, $299, $300, $301, $302, $303, $304, $305, $306, $307, $308, $309, $310, $311, $312, $313, $314, $315, $316, $317, $318, $319, $320, $321, $322)) AND ($323 = 0 OR ccr.patternlengthbars <= $324)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $325 OR relevant = 1) AND ($326 = 0 OR age <= $327) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2026-02-16 11:02:40 Duration: 0ms
7 8 1.07 GiB 137.00 MiB 137.05 MiB 137.02 MiB select updateresultsmaterializedview ();-
select updateresultsmaterializedview ();
Date: 2026-02-16 11:02:16 Duration: 0ms
8 4 360.65 MiB 90.09 MiB 90.22 MiB 90.16 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2026-02-16 11:02:06 Duration: 0ms
Queries generating the largest temporary files
Rank Size Query 1 137.05 MiB select updateresultsmaterializedview ();[ Date: 2026-02-16 11:32:15 ]
2 137.03 MiB select updateresultsmaterializedview ();[ Date: 2026-02-16 11:47:13 ]
3 137.02 MiB select updateresultsmaterializedview ();[ Date: 2026-02-16 11:35:32 ]
4 137.02 MiB select updateresultsmaterializedview ();[ Date: 2026-02-16 11:02:16 ]
5 137.02 MiB select updateresultsmaterializedview ();[ Date: 2026-02-16 11:50:33 ]
6 137.01 MiB select updateresultsmaterializedview ();[ Date: 2026-02-16 11:17:15 ]
7 137.00 MiB select updateresultsmaterializedview ();[ Date: 2026-02-16 11:20:33 ]
8 137.00 MiB select updateresultsmaterializedview ();[ Date: 2026-02-16 11:05:32 ]
9 118.72 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-02-16 11:40:05 ]
10 108.12 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-02-16 11:20:05 ]
11 102.78 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-02-16 11:50:04 ]
12 98.76 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-02-16 11:00:04 ]
13 96.12 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-02-16 11:10:06 ]
14 90.22 MiB select updateageforrelevantresults ();[ Date: 2026-02-16 11:02:06 ]
15 90.21 MiB select updateageforrelevantresults ();[ Date: 2026-02-16 11:32:06 ]
16 90.12 MiB select updateageforrelevantresults ();[ Date: 2026-02-16 11:47:05 ]
17 90.09 MiB select updateageforrelevantresults ();[ Date: 2026-02-16 11:17:05 ]
18 88.18 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-02-16 11:30:03 ]
19 87.84 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-02-16 11:00:05 ]
20 86.88 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-02-16 11:20:07 ]
-
Vacuums
Vacuums / Analyzes Distribution
Key values
- 0 sec Highest CPU-cost vacuum
Table
Database - Date
- 0 sec Highest CPU-cost analyze
Table
Database - Date
Analyzes per table
Key values
- public.solr_relevance_old (16) Main table analyzed (database acaweb_fx)
- 56 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 16 acaweb_fx.pg_catalog.pg_attribute 8 acaweb_fx.public.relevance_keylevels_results 4 acaweb_fx.pg_catalog.pg_class 4 acaweb_fx.pg_catalog.pg_type 4 acaweb_fx.public.relevance_autochartist_results 4 acaweb_fx.public.datafeeds_latestrun 3 acaweb_fx.public.relevance_fibonacci_results 3 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.pg_catalog.pg_depend 2 acaweb_fx.pg_catalog.pg_index 1 acaweb_fx.public.autochartist_symbolupdates 1 acaweb_fx.public.solr_imports 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.symbollatestupdatetime 1 acaweb_fx.pg_catalog.pg_rewrite 1 Total 56 Vacuums per table
Key values
- public.solr_relevance_old (16) Main table vacuumed on database acaweb_fx
- 38 vacuums Total
Index Buffer usage Skipped WAL usage Table Vacuums scans hits misses dirtied pins frozen records full page bytes acaweb_fx.public.solr_relevance_old 16 16 13,002 0 62 0 0 9,091 1,152 5,382,484 acaweb_fx.public.datafeeds_latestrun 4 0 480 0 7 0 0 40 6 37,004 acaweb_fx.pg_catalog.pg_attribute 3 3 2,688 0 297 0 201 1,168 290 1,880,907 acaweb_fx.pg_toast.pg_toast_2619 2 2 271 0 57 0 0 210 56 206,954 acaweb_fx.pg_catalog.pg_type 2 2 308 0 42 0 0 133 33 184,725 acaweb_fx.public.relevance_keylevels_results 2 2 7,678 0 224 0 144 2,165 209 719,194 acaweb_fx.public.relevance_autochartist_results 2 2 6,575 0 222 2 472 1,209 451 1,225,399 acaweb_fx.pg_catalog.pg_class 2 2 920 0 96 0 0 304 96 538,090 acaweb_fx.public.relevance_fibonacci_results 2 2 2,314 0 141 1 82 388 111 335,061 acaweb_fx.public.autochartist_symbolupdates 1 1 22,878 0 1,555 4 38,259 6,115 1,536 875,247 acaweb_fx.pg_catalog.pg_statistic 1 1 1,003 0 184 0 594 473 171 649,242 acaweb_fx.public.latest_t15_candle_view 1 1 93 0 1 0 0 6 1 9,019 Total 38 34 58,210 46,846 2,888 7 39,752 21,302 4,112 12,043,326 Tuples removed per table
Key values
- public.solr_relevance_old (53824) Main table with removed tuples on database acaweb_fx
- 69623 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 16 16 53,824 94,664 0 0 3,214 acaweb_fx.pg_catalog.pg_attribute 3 3 6,259 32,325 0 27 777 acaweb_fx.public.autochartist_symbolupdates 1 1 5,099 49,558 4 0 40,691 acaweb_fx.public.relevance_keylevels_results 2 2 1,659 25,721 0 0 558 acaweb_fx.public.relevance_autochartist_results 2 2 650 15,937 0 0 760 acaweb_fx.pg_catalog.pg_statistic 1 1 590 3,775 0 0 1,194 acaweb_fx.pg_catalog.pg_type 2 2 567 2,894 0 0 86 acaweb_fx.pg_catalog.pg_class 2 2 318 3,298 0 0 300 acaweb_fx.public.relevance_fibonacci_results 2 2 262 2,989 0 0 204 acaweb_fx.public.datafeeds_latestrun 4 0 189 82 26 0 64 acaweb_fx.pg_toast.pg_toast_2619 2 2 153 339 3 0 106 acaweb_fx.public.latest_t15_candle_view 1 1 53 14 0 0 1 Total 38 34 69,623 231,596 33 27 47,955 Pages removed per table
Key values
- pg_catalog.pg_attribute (27) Main table with removed pages on database acaweb_fx
- 27 pages Total removed
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_catalog.pg_attribute 3 3 6259 27 acaweb_fx.pg_toast.pg_toast_2619 2 2 153 0 acaweb_fx.pg_catalog.pg_type 2 2 567 0 acaweb_fx.public.autochartist_symbolupdates 1 1 5099 0 acaweb_fx.public.datafeeds_latestrun 4 0 189 0 acaweb_fx.pg_catalog.pg_statistic 1 1 590 0 acaweb_fx.public.latest_t15_candle_view 1 1 53 0 acaweb_fx.public.relevance_keylevels_results 2 2 1659 0 acaweb_fx.public.solr_relevance_old 16 16 53824 0 acaweb_fx.public.relevance_autochartist_results 2 2 650 0 acaweb_fx.pg_catalog.pg_class 2 2 318 0 acaweb_fx.public.relevance_fibonacci_results 2 2 262 0 Total 38 34 69,623 27 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Feb 16 11 38 56 - 0 sec Highest CPU-cost vacuum
-
Locks
Locks by types
Key values
- unknown Main Lock Type
- 0 locks Total
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
Queries by type
Key values
- 58,919 Total read queries
- 30,831 Total write queries
Queries by database
Key values
- unknown Main database
- 187,417 Requests
- 1h49m1s (unknown)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 883 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 170 0ms select 73 0ms tcl 361 0ms update 37 0ms socialmedia Total 147 0ms others 69 0ms select 74 0ms tcl 4 0ms unknown Total 187,417 1h49m1s copy from 16 0ms cte 3,503 0ms ddl 1 0ms delete 1 0ms insert 23,720 0ms others 4,234 0ms select 58,772 0ms tcl 413 0ms update 2,533 0ms Queries by user
Key values
- unknown Main user
- 187,417 Requests
User Request type Count Duration postgres Total 1,030 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 239 0ms select 147 0ms tcl 365 0ms update 37 0ms unknown Total 187,417 1h49m1s copy from 16 0ms cte 3,503 0ms ddl 1 0ms delete 1 0ms insert 23,720 0ms others 4,234 0ms select 58,772 0ms tcl 413 0ms update 2,533 0ms Duration by user
Key values
- 1h49m1s (unknown) Main time consuming user
User Request type Count Duration postgres Total 1,030 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 239 0ms select 147 0ms tcl 365 0ms update 37 0ms unknown Total 187,417 1h49m1s copy from 16 0ms cte 3,503 0ms ddl 1 0ms delete 1 0ms insert 23,720 0ms others 4,234 0ms select 58,772 0ms tcl 413 0ms update 2,533 0ms Queries by host
Key values
- unknown Main host
- 188,447 Requests
- 1h49m1s (unknown)
- Main time consuming host
Queries by application
Key values
- unknown Main application
- 188,091 Requests
- 1h49m1s (unknown)
- Main time consuming application
Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2026-02-16 11:35:13 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 66,148 0-1ms duration
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 23 0ms 0ms 0ms select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Feb 16 11 23 0ms 0ms 2 0ms 2 0ms 0ms 0ms select distinct "public"."processes"."live" AS "live" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? order by ? asc;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Feb 16 11 2 0ms 0ms 3 0ms 10 0ms 0ms 0ms select "public"."processparameters"."id" AS "id", "public"."processparameters"."processid" AS "processid", "public"."processparameters"."key" AS "key", "public"."processparameters"."value" AS "value" from "public"."processparameters" where "public"."processparameters"."id" = ? and "public"."processparameters"."id" = ? limit ? offset ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Feb 16 11 10 0ms 0ms 4 0ms 1 0ms 0ms 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 #4
Day Hour Count Duration Avg duration Feb 16 11 1 0ms 0ms 5 0ms 40 0ms 0ms 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 #5
Day Hour Count Duration Avg duration Feb 16 11 40 0ms 0ms 6 0ms 2,058 0ms 0ms 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 #6
Day Hour Count Duration Avg duration Feb 16 11 2,058 0ms 0ms 7 0ms 1 0ms 0ms 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 #7
Day Hour Count Duration Avg duration Feb 16 11 1 0ms 0ms 8 0ms 4 0ms 0ms 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 #8
Day Hour Count Duration Avg duration Feb 16 11 4 0ms 0ms 9 0ms 4 0ms 0ms 0ms select updaterelevantforrelevantresults ();Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Feb 16 11 4 0ms 0ms 10 0ms 1 0ms 0ms 0ms select oid from pg_catalog.pg_foreign_data_wrapper;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Feb 16 11 1 0ms 0ms 11 0ms 1 0ms 0ms 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 Feb 16 11 1 0ms 0ms 12 0ms 1 0ms 0ms 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 Feb 16 11 1 0ms 0ms 13 0ms 69 0ms 0ms 0ms set datestyle = iso;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Feb 16 11 69 0ms 0ms 14 0ms 2 0ms 0ms 0ms update "public"."processes" set "locale" = ?, "region" = ?, "schedule" = ? where "id" = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Feb 16 11 2 0ms 0ms 15 0ms 69 0ms 0ms 0ms set client_encoding to ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Feb 16 11 69 0ms 0ms 16 0ms 18 0ms 0ms 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 #16
Day Hour Count Duration Avg duration Feb 16 11 18 0ms 0ms 17 0ms 2 0ms 0ms 0ms select distinct "public"."processes"."enabled" AS "enabled" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? order by ? asc;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Feb 16 11 2 0ms 0ms 18 0ms 2 0ms 0ms 0ms select count(*) from ( select max(lastupdated) from sa_hist_bigmove where symbolid in ( select symbolid from t60 group by symbolid order by max(sastdatetimereceived) desc limit ?) group by symbolid having max(lastupdated) > current_timestamp - interval ? order by max(lastupdated) desc limit ?) as k;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Feb 16 11 2 0ms 0ms 19 0ms 374 0ms 0ms 0ms commit;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Feb 16 11 374 0ms 0ms 20 0ms 1 0ms 0ms 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 #20
Day Hour Count Duration Avg duration Feb 16 11 1 0ms 0ms Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 21,532 0ms 0ms 0ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Feb 16 11 21,532 0ms 0ms 2 8,254 0ms 0ms 0ms 0ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Feb 16 11 8,254 0ms 0ms 3 6,785 0ms 0ms 0ms 0ms select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Feb 16 11 6,785 0ms 0ms 4 5,471 0ms 0ms 0ms 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 #4
Day Hour Count Duration Avg duration Feb 16 11 5,471 0ms 0ms 5 3,798 0ms 0ms 0ms 0ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Feb 16 11 3,798 0ms 0ms 6 3,641 0ms 0ms 0ms 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 #6
Day Hour Count Duration Avg duration Feb 16 11 3,641 0ms 0ms 7 3,136 0ms 0ms 0ms 0ms insert into t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Feb 16 11 3,136 0ms 0ms 8 2,857 0ms 0ms 0ms 0ms insert into keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errormargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestprice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) values (?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?, ?, ?.?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?.?, ?::timestamp without time zone, ?, ?.?, ?.?, ?, ?, ?.?, ?.?, ?::timestamp without time zone, ?, ?, ?.?, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Feb 16 11 2,857 0ms 0ms 9 2,673 0ms 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Feb 16 11 2,673 0ms 0ms 10 2,101 0ms 0ms 0ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Feb 16 11 2,101 0ms 0ms 11 2,058 0ms 0ms 0ms 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Feb 16 11 2,058 0ms 0ms 12 2,034 0ms 0ms 0ms 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 #12
Day Hour Count Duration Avg duration Feb 16 11 2,034 0ms 0ms 13 1,863 0ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Feb 16 11 1,863 0ms 0ms 14 1,838 0ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Feb 16 11 1,838 0ms 0ms 15 1,554 0ms 0ms 0ms 0ms select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Feb 16 11 1,554 0ms 0ms 16 1,458 0ms 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Feb 16 11 1,458 0ms 0ms 17 1,109 0ms 0ms 0ms 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 Feb 16 11 1,109 0ms 0ms 18 990 0ms 0ms 0ms 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars as length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternstartprice, resy1, supporty1, dtt.timezone, cps.pip, newlevels.profit from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern left join currencypips cps on cps.symbol = s.symbol left join lateral calc_cp_signal (a.resultuid) newlevels on true where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Feb 16 11 990 0ms 0ms 19 627 0ms 0ms 0ms 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, a.patternprice, atbaridentified as patternendtime, breakout, p.patternname, dtt.timezone, a.direction, case when a.patternclassid = ? then a.predictionpricefrom else a.patternprice end as predictionpricefrom, case when a.patternclassid = ? then a.predictionpriceto else a.patternprice end as predictionpriceto, s.timegranularity as interval, patternlengthbars as length, cps.pip from keylevels_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join hrspatterns p on a.patternid = p.patternid left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Feb 16 11 627 0ms 0ms 20 551 0ms 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ) select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as ruid, s.symbolid as sid, s.symbol as sym, longname, shortname, exchange as e, timegranularity as tg, a.patternid as pid, a.direction as d, a.patternprice as pp, atbaridentified as pet, case when (x9 != ?) then x9 when (x8 != ?) then x8 when (x7 != ?) then x7 when (x6 != ?) then x6 when (x5 != ?) then x5 when (x4 != ?) then x4 when (x3 != ?) then x3 when (x2 != ?) then x2 end as pst, patternprice as patp, x0, x1, x2, case when (x3 != ?) then x3 else ? end as x3, case when (x4 != ?) then x4 else ? end as x4, case when (x5 != ?) then x5 else ? end as x5, case when (x6 != ?) then x6 else ? end as x6, case when (x7 != ?) then x7 else ? end as x7, case when (x8 != ?) then x8 else ? end as x8, errormargin as erm, breakoutprice as pe, breakoutbars as be, breakout, atbaridentified as atbar, atpriceidentified as atprice, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzos, dtt.timezone as timezone, approachingtimestamp as apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, furthestprice as fp, newlevels.filtered, a.uniquepointsvalue as upv, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from keylevels_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join hrspatterns p on a.patternid = p.patternid inner join rar_max rm on ? = ? left outer join relevance_keylevels_results rar on a.resultuid = rar.resultuid left join lateral calc_kl_signal_filter (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Feb 16 11 551 0ms 0ms Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 0ms 0ms 0ms 23 0ms select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Feb 16 11 23 0ms 0ms 2 0ms 0ms 0ms 2 0ms select distinct "public"."processes"."live" AS "live" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? order by ? asc;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Feb 16 11 2 0ms 0ms 3 0ms 0ms 0ms 10 0ms select "public"."processparameters"."id" AS "id", "public"."processparameters"."processid" AS "processid", "public"."processparameters"."key" AS "key", "public"."processparameters"."value" AS "value" from "public"."processparameters" where "public"."processparameters"."id" = ? and "public"."processparameters"."id" = ? limit ? offset ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Feb 16 11 10 0ms 0ms 4 0ms 0ms 0ms 1 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 #4
Day Hour Count Duration Avg duration Feb 16 11 1 0ms 0ms 5 0ms 0ms 0ms 40 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 #5
Day Hour Count Duration Avg duration Feb 16 11 40 0ms 0ms 6 0ms 0ms 0ms 2,058 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 #6
Day Hour Count Duration Avg duration Feb 16 11 2,058 0ms 0ms 7 0ms 0ms 0ms 1 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 #7
Day Hour Count Duration Avg duration Feb 16 11 1 0ms 0ms 8 0ms 0ms 0ms 4 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 #8
Day Hour Count Duration Avg duration Feb 16 11 4 0ms 0ms 9 0ms 0ms 0ms 4 0ms select updaterelevantforrelevantresults ();Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Feb 16 11 4 0ms 0ms 10 0ms 0ms 0ms 1 0ms select oid from pg_catalog.pg_foreign_data_wrapper;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Feb 16 11 1 0ms 0ms 11 0ms 0ms 0ms 1 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 Feb 16 11 1 0ms 0ms 12 0ms 0ms 0ms 1 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 Feb 16 11 1 0ms 0ms 13 0ms 0ms 0ms 69 0ms set datestyle = iso;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Feb 16 11 69 0ms 0ms 14 0ms 0ms 0ms 2 0ms update "public"."processes" set "locale" = ?, "region" = ?, "schedule" = ? where "id" = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Feb 16 11 2 0ms 0ms 15 0ms 0ms 0ms 69 0ms set client_encoding to ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Feb 16 11 69 0ms 0ms 16 0ms 0ms 0ms 18 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 #16
Day Hour Count Duration Avg duration Feb 16 11 18 0ms 0ms 17 0ms 0ms 0ms 2 0ms select distinct "public"."processes"."enabled" AS "enabled" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? order by ? asc;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Feb 16 11 2 0ms 0ms 18 0ms 0ms 0ms 2 0ms select count(*) from ( select max(lastupdated) from sa_hist_bigmove where symbolid in ( select symbolid from t60 group by symbolid order by max(sastdatetimereceived) desc limit ?) group by symbolid having max(lastupdated) > current_timestamp - interval ? order by max(lastupdated) desc limit ?) as k;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Feb 16 11 2 0ms 0ms 19 0ms 0ms 0ms 374 0ms commit;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Feb 16 11 374 0ms 0ms 20 0ms 0ms 0ms 1 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 #20
Day Hour Count Duration Avg duration Feb 16 11 1 0ms 0ms Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 2s295ms 2,123 0ms 17ms 1ms WITH rar_max as ( ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Feb 16 11 2,123 2s295ms 1ms -
WITH rar_max as ( ;
Date: 2026-02-16 11:15:45 Duration: 17ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-02-16 11:20:56 Duration: 15ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-02-16 11:46:01 Duration: 12ms Database: postgres
2 1s865ms 1,228 0ms 9ms 1ms SELECT symbolid, ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 11 1,228 1s865ms 1ms -
SELECT symbolid, ;
Date: 2026-02-16 11:30:57 Duration: 9ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-02-16 11:15:51 Duration: 4ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-02-16 11:46:37 Duration: 3ms Database: postgres
3 816ms 2,916 0ms 17ms 0ms SELECT ;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 11 2,916 816ms 0ms -
SELECT ;
Date: 2026-02-16 11:45:52 Duration: 17ms Database: postgres
-
SELECT ;
Date: 2026-02-16 11:25:50 Duration: 12ms Database: postgres
-
SELECT ;
Date: 2026-02-16 11:15:45 Duration: 9ms Database: postgres
4 411ms 371 0ms 3ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 11 371 411ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-16 11:00:53 Duration: 3ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-16 11:00:51 Duration: 2ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-16 11:30:56 Duration: 2ms Database: postgres
5 277ms 1,863 0ms 2ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 11 1,863 277ms 0ms -
SET extra_float_digits = 3;
Date: 2026-02-16 11:27:50 Duration: 2ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-02-16 11:04:15 Duration: 2ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-02-16 11:00:43 Duration: 1ms Database: postgres
6 273ms 2,971 0ms 0ms 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 prepare #6
Day Hour Count Duration Avg duration 11 2,971 273ms 0ms -
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:11:48 Duration: 0ms Database: postgres
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:41:47 Duration: 0ms Database: postgres
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:45:55 Duration: 0ms Database: postgres
7 202ms 1,877 0ms 0ms 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 prepare #7
Day Hour Count Duration Avg duration 11 1,877 202ms 0ms -
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:15:48 Duration: 0ms Database: postgres
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:11:48 Duration: 0ms Database: postgres
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:15:52 Duration: 0ms Database: postgres
8 179ms 1,137 0ms 0ms 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 prepare #8
Day Hour Count Duration Avg duration 11 1,137 179ms 0ms -
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:17:42 Duration: 0ms Database: postgres
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:56:48 Duration: 0ms Database: postgres
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:17:03 Duration: 0ms Database: postgres
9 82ms 1,534 0ms 5ms 0ms select 1;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 11 1,534 82ms 0ms -
select 1;
Date: 2026-02-16 11:21:02 Duration: 5ms Database: postgres
-
select 1;
Date: 2026-02-16 11:01:29 Duration: 3ms Database: postgres
-
select 1;
Date: 2026-02-16 11:15:04 Duration: 2ms Database: postgres
10 55ms 8 6ms 7ms 6ms with sym_info as ( ;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 11 8 55ms 6ms -
with sym_info as ( ;
Date: 2026-02-16 11:51:43 Duration: 7ms Database: postgres
-
with sym_info as ( ;
Date: 2026-02-16 11:21:44 Duration: 7ms Database: postgres
-
with sym_info as ( ;
Date: 2026-02-16 11:51:54 Duration: 6ms Database: postgres
11 54ms 39 0ms 3ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 11 39 54ms 1ms -
WITH last_candle AS ( ;
Date: 2026-02-16 11:33:05 Duration: 3ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-02-16 11:52:00 Duration: 3ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-02-16 11:36:00 Duration: 3ms Database: postgres
12 51ms 372 0ms 0ms 0ms select category, ;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 11 372 51ms 0ms -
select category, ;
Date: 2026-02-16 11:32:23 Duration: 0ms Database: postgres
-
select category, ;
Date: 2026-02-16 11:32:24 Duration: 0ms Database: postgres
-
select category, ;
Date: 2026-02-16 11:34:17 Duration: 0ms Database: postgres
13 45ms 18 1ms 3ms 2ms select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 11 18 45ms 2ms -
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-02-16 11:31:18 Duration: 3ms Database: postgres
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-02-16 11:41:13 Duration: 2ms Database: postgres
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-02-16 11:01:37 Duration: 2ms Database: postgres
14 35ms 32 0ms 1ms 1ms select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 11 32 35ms 1ms -
select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2026-02-16 11:40:58 Duration: 1ms Database: postgres
-
select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2026-02-16 11:01:40 Duration: 1ms Database: postgres
-
select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2026-02-16 11:05:51 Duration: 1ms Database: postgres
15 31ms 210 0ms 0ms 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 prepare #15
Day Hour Count Duration Avg duration 11 210 31ms 0ms -
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-02-16 11:13:50 Duration: 0ms Database: postgres
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-02-16 11:13:51 Duration: 0ms Database: postgres
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-02-16 11:13:50 Duration: 0ms Database: postgres
16 29ms 32 0ms 1ms 0ms select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 11 32 29ms 0ms -
select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2026-02-16 11:46:47 Duration: 1ms Database: postgres
-
select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2026-02-16 11:05:51 Duration: 1ms Database: postgres
-
select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2026-02-16 11:40:58 Duration: 1ms Database: postgres
17 28ms 12 1ms 6ms 2ms with wh_patitioned as ( ;Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 11 12 28ms 2ms -
with wh_patitioned as ( ;
Date: 2026-02-16 11:33:04 Duration: 6ms Database: postgres
-
with wh_patitioned as ( ;
Date: 2026-02-16 11:33:05 Duration: 4ms Database: postgres
-
with wh_patitioned as ( ;
Date: 2026-02-16 11:06:27 Duration: 2ms Database: postgres
18 26ms 192 0ms 0ms 0ms INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 11 192 26ms 0ms -
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:01:33 Duration: 0ms Database: postgres
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:01:29 Duration: 0ms Database: postgres
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:01:31 Duration: 0ms Database: postgres
19 24ms 1,832 0ms 2ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 11 1,832 24ms 0ms -
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-02-16 11:30:01 Duration: 2ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-02-16 11:21:22 Duration: 0ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-02-16 11:46:22 Duration: 0ms Database: postgres
20 15ms 6 2ms 3ms 2ms select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 11 6 15ms 2ms -
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2026-02-16 11:00:04 Duration: 3ms Database: postgres
-
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2026-02-16 11:20:05 Duration: 2ms Database: postgres
-
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2026-02-16 11:30:04 Duration: 2ms Database: postgres
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 28s721ms 2,612 0ms 51ms 10ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Feb 16 11 2,612 28s721ms 10ms -
WITH rar_max as ( ;
Date: 2026-02-16 11:25:48 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'
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WITH rar_max as ( ;
Date: 2026-02-16 11:25:55 Duration: 41ms 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 = '500', $174 = '500', $175 = 't', $176 = '10', $177 = '10'
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WITH rar_max as ( ;
Date: 2026-02-16 11:46:04 Duration: 39ms Database: postgres parameters: $1 = '607688280037018301', $2 = '607688280037018301', $3 = '607688280037018301'
2 7s371ms 19,174 0ms 9ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 11 19,174 7s371ms 0ms -
SELECT ;
Date: 2026-02-16 11:45:52 Duration: 9ms Database: postgres parameters: $1 = '667', $2 = '667', $3 = '500991628284405200'
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SELECT ;
Date: 2026-02-16 11:33:06 Duration: 9ms Database: postgres parameters: $1 = '515840243265160300'
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SELECT ;
Date: 2026-02-16 11:37:12 Duration: 8ms Database: postgres parameters: $1 = '500991628208235200'
3 3s206ms 1,228 1ms 19ms 2ms SELECT symbolid, ;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 11 1,228 3s206ms 2ms -
SELECT symbolid, ;
Date: 2026-02-16 11:46:23 Duration: 19ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'ADAUSD', $4 = 'AUDJPY'
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SELECT symbolid, ;
Date: 2026-02-16 11:45:40 Duration: 9ms Database: postgres parameters: $1 = 'ICMARKETS', $2 = '15', $3 = 'USDJPY', $4 = 'US500', $5 = 'USDCZK', $6 = 'USDDKK', $7 = 'USDCHF', $8 = 'USDHKD', $9 = 'USDCNH', $10 = 'USDCAD', $11 = 'USDHUF'
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SELECT symbolid, ;
Date: 2026-02-16 11:45:55 Duration: 5ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'GBPJPY', $4 = 'GBPCHF.FX', $5 = 'GBPJPY.FX', $6 = 'GBPCHF.ID'
4 645ms 371 1ms 10ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 11 371 645ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-16 11:30:56 Duration: 10ms Database: postgres parameters: $1 = 'AXIORY'
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-16 11:00:59 Duration: 5ms Database: postgres parameters: $1 = 'Alpari'
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SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-16 11:45:45 Duration: 3ms Database: postgres parameters: $1 = 'ICMARKETS'
5 624ms 110 0ms 21ms 5ms select distinct s.statsid as statsid, sy.exchange as name;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 11 110 624ms 5ms -
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-02-16 11:32:23 Duration: 21ms Database: postgres parameters: $1 = '1436', $2 = '1436'
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select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-02-16 11:32:23 Duration: 21ms Database: postgres parameters: $1 = '1436', $2 = '1436'
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select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-02-16 11:32:28 Duration: 18ms Database: postgres parameters: $1 = '619', $2 = '619'
6 537ms 18 0ms 46ms 29ms with wh_patitioned as ( ;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 11 18 537ms 29ms -
with wh_patitioned as ( ;
Date: 2026-02-16 11:40:03 Duration: 46ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
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with wh_patitioned as ( ;
Date: 2026-02-16 11:46:21 Duration: 46ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
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with wh_patitioned as ( ;
Date: 2026-02-16 11:33:04 Duration: 46ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
7 458ms 21,426 0ms 6ms 0ms select 1;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 11 21,426 458ms 0ms -
select 1;
Date: 2026-02-16 11:20:58 Duration: 6ms Database: postgres
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select 1;
Date: 2026-02-16 11:20:59 Duration: 6ms Database: postgres
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select 1;
Date: 2026-02-16 11:20:55 Duration: 5ms Database: postgres
8 451ms 59 4ms 18ms 7ms WITH last_candle AS ( ;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 11 59 451ms 7ms -
WITH last_candle AS ( ;
Date: 2026-02-16 11:04:00 Duration: 18ms Database: postgres parameters: $1 = '558', $2 = '558'
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WITH last_candle AS ( ;
Date: 2026-02-16 11:56:02 Duration: 17ms Database: postgres parameters: $1 = '667', $2 = '667'
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WITH last_candle AS ( ;
Date: 2026-02-16 11:52:02 Duration: 16ms Database: postgres parameters: $1 = '538', $2 = '538'
9 350ms 8 38ms 45ms 43ms with sym_info as ( ;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 11 8 350ms 43ms -
with sym_info as ( ;
Date: 2026-02-16 11:51:43 Duration: 45ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
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with sym_info as ( ;
Date: 2026-02-16 11:51:46 Duration: 44ms Database: postgres parameters: $1 = '617', $2 = 'Forex', $3 = 'Forex', $4 = '617', $5 = 'Forex', $6 = '617', $7 = '617', $8 = 'Forex', $9 = '617'
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with sym_info as ( ;
Date: 2026-02-16 11:21:55 Duration: 44ms Database: postgres parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'
10 295ms 4,617 0ms 1ms 0ms select category, ;Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 11 4,617 295ms 0ms -
select category, ;
Date: 2026-02-16 11:32:28 Duration: 1ms Database: postgres parameters: $1 = '515852059324736307', $2 = 'symbol', $3 = 'USDMXN', $4 = 'CHFZAR', $5 = 'AUDJPY', $6 = 'CHFJPY', $7 = 'USDZAR', $8 = 'USDJPY', $9 = 'CADJPY', $10 = 'ZARJPY', $11 = 'EURCNH', $12 = 'GBPZAR', $13 = 'NZDJPY', $14 = 'TRYJPY', $15 = 'USDHUF', $16 = 'AUDZAR', $17 = 'EURMXN', $18 = 'GBPJPY', $19 = 'EURZAR', $20 = 'EURNOK', $21 = 'USDNOK', $22 = 'SGDJPY', $23 = 'USDCZK', $24 = 'EURHKD', $25 = 'EURSEK', $26 = 'CHFHUF', $27 = 'USDDKK', $28 = 'USDSEK', $29 = 'NZDSEK', $30 = 'EURTRY', $31 = 'EURJPY', $32 = 'EURHUF', $33 = 'USDPLN', $34 = 'GBPNZD', $35 = 'USDCNH', $36 = 'EURCZK', $37 = 'USDILS', $38 = 'EURPLN', $39 = 'GBPAUD', $40 = 'EURGBP', $41 = 'TRYJPY', $42 = 'EURNZD', $43 = 'EURCZK', $44 = 'EURAUD', $45 = 'ZARJPY', $46 = 'CHFHUF', $47 = 'EURHUF', $48 = 'USDCAD', $49 = 'GBPCAD', $50 = 'EURDKK', $51 = 'USDZAR', $52 = 'EURCHF', $53 = '515852059324736307', $54 = 'symbol', $55 = 'USDMXN', $56 = 'CHFZAR', $57 = 'AUDJPY', $58 = 'CHFJPY', $59 = 'USDZAR', $60 = 'USDJPY', $61 = 'CADJPY', $62 = 'ZARJPY', $63 = 'EURCNH', $64 = 'GBPZAR', $65 = 'NZDJPY', $66 = 'TRYJPY', $67 = 'USDHUF', $68 = 'AUDZAR', $69 = 'EURMXN', $70 = 'GBPJPY', $71 = 'EURZAR', $72 = 'EURNOK', $73 = 'USDNOK', $74 = 'SGDJPY', $75 = 'USDCZK', $76 = 'EURHKD', $77 = 'EURSEK', $78 = 'CHFHUF', $79 = 'USDDKK', $80 = 'USDSEK', $81 = 'NZDSEK', $82 = 'EURTRY', $83 = 'EURJPY', $84 = 'EURHUF', $85 = 'USDPLN', $86 = 'GBPNZD', $87 = 'USDCNH', $88 = 'EURCZK', $89 = 'USDILS', $90 = 'EURPLN', $91 = 'GBPAUD', $92 = 'EURGBP', $93 = 'TRYJPY', $94 = 'EURNZD', $95 = 'EURCZK', $96 = 'EURAUD', $97 = 'ZARJPY', $98 = 'CHFHUF', $99 = 'EURHUF', $100 = 'USDCAD', $101 = 'GBPCAD', $102 = 'EURDKK', $103 = 'USDZAR', $104 = 'EURCHF'
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select category, ;
Date: 2026-02-16 11:32:28 Duration: 1ms Database: postgres parameters: $1 = '515852059324253307', $2 = 'symbol', $3 = 'USDMXN', $4 = 'CHFZAR', $5 = 'AUDJPY', $6 = 'CHFJPY', $7 = 'USDZAR', $8 = 'USDJPY', $9 = 'CADJPY', $10 = 'ZARJPY', $11 = 'EURCNH', $12 = 'GBPZAR', $13 = 'NZDJPY', $14 = 'TRYJPY', $15 = 'USDHUF', $16 = 'AUDZAR', $17 = 'EURMXN', $18 = 'GBPJPY', $19 = 'EURZAR', $20 = 'EURNOK', $21 = 'USDNOK', $22 = 'SGDJPY', $23 = 'USDCZK', $24 = 'EURHKD', $25 = 'EURSEK', $26 = 'CHFHUF', $27 = 'USDDKK', $28 = 'USDSEK', $29 = 'NZDSEK', $30 = 'EURTRY', $31 = 'EURJPY', $32 = 'EURHUF', $33 = 'USDPLN', $34 = 'GBPNZD', $35 = 'USDCNH', $36 = 'EURCZK', $37 = 'USDILS', $38 = 'EURPLN', $39 = 'GBPAUD', $40 = 'EURGBP', $41 = 'TRYJPY', $42 = 'EURNZD', $43 = 'EURCZK', $44 = 'EURAUD', $45 = 'ZARJPY', $46 = 'CHFHUF', $47 = 'EURHUF', $48 = 'USDCAD', $49 = 'GBPCAD', $50 = 'EURDKK', $51 = 'USDZAR', $52 = 'EURCHF', $53 = '515852059324253307', $54 = 'symbol', $55 = 'USDMXN', $56 = 'CHFZAR', $57 = 'AUDJPY', $58 = 'CHFJPY', $59 = 'USDZAR', $60 = 'USDJPY', $61 = 'CADJPY', $62 = 'ZARJPY', $63 = 'EURCNH', $64 = 'GBPZAR', $65 = 'NZDJPY', $66 = 'TRYJPY', $67 = 'USDHUF', $68 = 'AUDZAR', $69 = 'EURMXN', $70 = 'GBPJPY', $71 = 'EURZAR', $72 = 'EURNOK', $73 = 'USDNOK', $74 = 'SGDJPY', $75 = 'USDCZK', $76 = 'EURHKD', $77 = 'EURSEK', $78 = 'CHFHUF', $79 = 'USDDKK', $80 = 'USDSEK', $81 = 'NZDSEK', $82 = 'EURTRY', $83 = 'EURJPY', $84 = 'EURHUF', $85 = 'USDPLN', $86 = 'GBPNZD', $87 = 'USDCNH', $88 = 'EURCZK', $89 = 'USDILS', $90 = 'EURPLN', $91 = 'GBPAUD', $92 = 'EURGBP', $93 = 'TRYJPY', $94 = 'EURNZD', $95 = 'EURCZK', $96 = 'EURAUD', $97 = 'ZARJPY', $98 = 'CHFHUF', $99 = 'EURHUF', $100 = 'USDCAD', $101 = 'GBPCAD', $102 = 'EURDKK', $103 = 'USDZAR', $104 = 'EURCHF'
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select category, ;
Date: 2026-02-16 11:32:24 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307', $2 = 'symbol', $3 = 'XAUUSD', $4 = 'DOW30', $5 = 'AUDJPY', $6 = 'GBPJPY', $7 = 'XAGUSD', $8 = 'USDJPY', $9 = 'SP500', $10 = 'NASDAQ100', $11 = 'OIL', $12 = 'NZDJPY', $13 = 'CHFJPY', $14 = 'EURJPY', $15 = 'GBPAUD', $16 = 'EURAUD', $17 = 'GBPCHF', $18 = 'EURCHF', $19 = 'USDCAD', $20 = 'EURCAD', $21 = 'EURGBP', $22 = 'OIL', $23 = 'GBPUSD', $24 = 'DOW30', $25 = 'EURCAD', $26 = 'XAGUSD', $27 = 'EURJPY', $28 = 'EURUSD', $29 = 'NZDUSD', $30 = 'AUDJPY', $31 = 'RK_SSI', $32 = 'GBPJPY', $33 = 'R_SSI', $34 = 'CHFJPY', $35 = 'SP500', $36 = 'GBPAUD', $37 = 'GBPUSD', $38 = 'EURUSD', $39 = 'USDCHF', $40 = 'EURAUD', $41 = 'XAUUSD', $42 = 'NZDJPY', $43 = 'AUDUSD', $44 = 'AUDNZD', $45 = 'USDJPY', $46 = 'USDCAD', $47 = 'NASDAQ100', $48 = 'AUDUSD', $49 = 'GBPCHF', $50 = 'NZDUSD', $51 = 'USDCHF', $52 = 'EURCHF', $53 = '515852059317765307', $54 = 'symbol', $55 = 'XAUUSD', $56 = 'DOW30', $57 = 'AUDJPY', $58 = 'GBPJPY', $59 = 'XAGUSD', $60 = 'USDJPY', $61 = 'SP500', $62 = 'NASDAQ100', $63 = 'OIL', $64 = 'NZDJPY', $65 = 'CHFJPY', $66 = 'EURJPY', $67 = 'GBPAUD', $68 = 'EURAUD', $69 = 'GBPCHF', $70 = 'EURCHF', $71 = 'USDCAD', $72 = 'EURCAD', $73 = 'EURGBP', $74 = 'OIL', $75 = 'GBPUSD', $76 = 'DOW30', $77 = 'EURCAD', $78 = 'XAGUSD', $79 = 'EURJPY', $80 = 'EURUSD', $81 = 'NZDUSD', $82 = 'AUDJPY', $83 = 'RK_SSI', $84 = 'GBPJPY', $85 = 'R_SSI', $86 = 'CHFJPY', $87 = 'SP500', $88 = 'GBPAUD', $89 = 'GBPUSD', $90 = 'EURUSD', $91 = 'USDCHF', $92 = 'EURAUD', $93 = 'XAUUSD', $94 = 'NZDJPY', $95 = 'AUDUSD', $96 = 'AUDNZD', $97 = 'USDJPY', $98 = 'USDCAD', $99 = 'NASDAQ100', $100 = 'AUDUSD', $101 = 'GBPCHF', $102 = 'NZDUSD', $103 = 'USDCHF', $104 = 'EURCHF'
11 293ms 22 9ms 20ms 13ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #11
Day Hour Count Duration Avg duration 11 22 293ms 13ms -
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-02-16 11:12:24 Duration: 20ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
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WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-02-16 11:02:34 Duration: 20ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
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WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-02-16 11:51:38 Duration: 19ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
12 273ms 5,471 0ms 1ms 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 #12
Day Hour Count Duration Avg duration 11 5,471 273ms 0ms -
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:30:59 Duration: 1ms Database: postgres parameters: $1 = '2026-02-16 11:00:00', $2 = '92.7045', $3 = '92.737', $4 = '92.682', $5 = '92.705', $6 = '1070', $7 = '515840230538789300', $8 = '0', $9 = '2026-02-16 11:30:59.781', $10 = '2026-02-16 11:30:59.664', $11 = '92.7045', $12 = '92.737', $13 = '92.682', $14 = '92.705', $15 = '1070', $16 = '0', $17 = '2026-02-16 11:30:59.781', $18 = '2026-02-16 11:30:59.664'
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:15:48 Duration: 0ms Database: postgres parameters: $1 = '2026-02-16 10:45:00', $2 = '0.86884', $3 = '0.869135', $4 = '0.868805', $5 = '0.869115', $6 = '579', $7 = '515840230408357300', $8 = '0', $9 = '2026-02-16 11:15:48.308', $10 = '2026-02-16 11:15:48.154', $11 = '0.86884', $12 = '0.869135', $13 = '0.868805', $14 = '0.869115', $15 = '579', $16 = '0', $17 = '2026-02-16 11:15:48.308', $18 = '2026-02-16 11:15:48.154'
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:30:57 Duration: 0ms Database: postgres parameters: $1 = '2026-02-16 11:15:00', $2 = '1.36594', $3 = '1.36609', $4 = '1.36574', $5 = '1.36585', $6 = '518', $7 = '515840230504056300', $8 = '0', $9 = '2026-02-16 11:30:57.828', $10 = '2026-02-16 11:30:57.661', $11 = '1.36594', $12 = '1.36609', $13 = '1.36574', $14 = '1.36585', $15 = '518', $16 = '0', $17 = '2026-02-16 11:30:57.828', $18 = '2026-02-16 11:30:57.661'
13 252ms 3,136 0ms 0ms 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 #13
Day Hour Count Duration Avg duration 11 3,136 252ms 0ms -
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:45:55 Duration: 0ms Database: postgres parameters: $1 = '2026-02-13 22:30:00', $2 = '255.93', $3 = '256.655', $4 = '255.46', $5 = '256.465', $6 = '2022', $7 = '515840249419597300', $8 = '0', $9 = '2026-02-16 11:45:55.211', $10 = '2026-02-16 11:45:55.003', $11 = '255.93', $12 = '256.655', $13 = '255.46', $14 = '256.465', $15 = '2022', $16 = '0', $17 = '2026-02-16 11:45:55.211', $18 = '2026-02-16 11:45:55.003'
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:31:46 Duration: 0ms Database: postgres parameters: $1 = '2026-02-16 11:00:00', $2 = '1.61468', $3 = '1.6153', $4 = '1.61438', $5 = '1.615', $6 = '2138', $7 = '515840230463448300', $8 = '0', $9 = '2026-02-16 11:31:46.191', $10 = '2026-02-16 11:31:46.191', $11 = '1.61468', $12 = '1.6153', $13 = '1.61438', $14 = '1.615', $15 = '2138', $16 = '0', $17 = '2026-02-16 11:31:46.191', $18 = '2026-02-16 11:31:46.191'
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:45:53 Duration: 0ms Database: postgres parameters: $1 = '2026-02-16 12:00:00', $2 = '6.635e-06', $3 = '6.67e-06', $4 = '6.63e-06', $5 = '6.66e-06', $6 = '252', $7 = '515840249472255300', $8 = '0', $9 = '2026-02-16 11:45:53.251', $10 = '2026-02-16 11:45:53.25', $11 = '6.635e-06', $12 = '6.67e-06', $13 = '6.63e-06', $14 = '6.66e-06', $15 = '252', $16 = '0', $17 = '2026-02-16 11:45:53.251', $18 = '2026-02-16 11:45:53.25'
14 187ms 1 187ms 187ms 187ms SELECT t.*;Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 11 1 187ms 187ms -
SELECT t.*;
Date: 2026-02-16 11:39:11 Duration: 187ms Database: postgres
15 176ms 2,058 0ms 0ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 11 2,058 176ms 0ms -
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:30:43 Duration: 0ms Database: postgres parameters: $1 = '2026-02-16 10:00:00', $2 = '77.178', $3 = '77.209', $4 = '76.545', $5 = '77.209', $6 = '8091', $7 = '500991628262991200', $8 = '0', $9 = '2026-02-16 11:30:43.276', $10 = '2026-02-16 11:30:43.276', $11 = '77.178', $12 = '77.209', $13 = '76.545', $14 = '77.209', $15 = '8091', $16 = '0', $17 = '2026-02-16 11:30:43.276', $18 = '2026-02-16 11:30:43.276'
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:15:48 Duration: 0ms Database: postgres parameters: $1 = '2026-02-16 10:00:00', $2 = '0.869445', $3 = '0.869615', $4 = '0.868805', $5 = '0.869115', $6 = '3323', $7 = '515840230408963300', $8 = '0', $9 = '2026-02-16 11:15:48.36', $10 = '2026-02-16 11:15:48.359', $11 = '0.869445', $12 = '0.869615', $13 = '0.868805', $14 = '0.869115', $15 = '3323', $16 = '0', $17 = '2026-02-16 11:15:48.36', $18 = '2026-02-16 11:15:48.359'
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-02-16 11:11:48 Duration: 0ms Database: postgres parameters: $1 = '2026-02-16 10:00:00', $2 = '8955.4', $3 = '8967.4', $4 = '8950.4', $5 = '8966.55', $6 = '5339', $7 = '515840248015562300', $8 = '0', $9 = '2026-02-16 11:11:48.85', $10 = '2026-02-16 11:11:48.76', $11 = '8955.4', $12 = '8967.4', $13 = '8950.4', $14 = '8966.55', $15 = '5339', $16 = '0', $17 = '2026-02-16 11:11:48.85', $18 = '2026-02-16 11:11:48.76'
16 146ms 243 0ms 1ms 0ms SELECT absolutetimezoneoffset;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 11 243 146ms 0ms -
SELECT absolutetimezoneoffset;
Date: 2026-02-16 11:32:25 Duration: 1ms Database: postgres parameters: $1 = '538', $2 = 'Shares EU'
-
SELECT absolutetimezoneoffset;
Date: 2026-02-16 11:32:23 Duration: 1ms Database: postgres parameters: $1 = '489', $2 = 'BROKER'
-
SELECT absolutetimezoneoffset;
Date: 2026-02-16 11:18:08 Duration: 1ms Database: postgres parameters: $1 = '914', $2 = 'Crypto'
17 80ms 210 0ms 1ms 0ms SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 11 210 80ms 0ms -
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-02-16 11:13:50 Duration: 1ms Database: postgres
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-02-16 11:13:51 Duration: 0ms Database: postgres
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-02-16 11:13:50 Duration: 0ms Database: postgres
18 61ms 14 3ms 7ms 4ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 11 14 61ms 4ms -
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-02-16 11:06:04 Duration: 7ms Database: postgres parameters: $1 = '627', $2 = '627'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-02-16 11:06:12 Duration: 7ms Database: postgres parameters: $1 = '627', $2 = '627'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-02-16 11:32:31 Duration: 6ms Database: postgres parameters: $1 = '538', $2 = '538'
19 55ms 61 0ms 1ms 0ms SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 11 61 55ms 0ms -
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2026-02-16 11:05:12 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'EURUSD', $3 = '558'
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SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2026-02-16 11:32:17 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'CHFJPY', $3 = '558'
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SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2026-02-16 11:50:11 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'EURUSD', $3 = '558'
20 48ms 265 0ms 1ms 0ms SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T15 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 11 265 48ms 0ms -
SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T15 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2026-02-16 11:33:19 Duration: 1ms Database: postgres parameters: $1 = '515840243238020300'
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T15 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2026-02-16 11:20:50 Duration: 0ms Database: postgres parameters: $1 = '500991628253414200'
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SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T15 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050) a ORDER BY PriceDateTime ASC;
Date: 2026-02-16 11:06:09 Duration: 0ms Database: postgres parameters: $1 = '515840243235939300'
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Events
Log levels
Key values
- 371,282 Log entries
Events distribution
Key values
- 0 PANIC entries
- 2 FATAL entries
- 1 ERROR entries
- 0 WARNING entries
Most Frequent Errors/Events
Key values
- 2 Max number of times the same event was reported
- 3 Total events found
Rank Times reported Error 1 2 FATAL: connection to client lost
Times Reported Most Frequent Error / Event #1
Day Hour Count Feb 16 11 2 - FATAL: connection to client lost
Date: 2026-02-16 11:31:57
2 1 ERROR: relation "..." does not exist
Times Reported Most Frequent Error / Event #2
Day Hour Count Feb 16 11 1 - ERROR: relation "t0" does not exist at character 83
Statement: SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T0 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050 ) a ORDER BY PriceDateTime ASC
Date: 2026-02-16 11:45:30