pgBadger-
Global information
- Generated on Thu Feb 5 08:00:19 2026
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-02-05_090000.log, ..., /home/postgres/pg_data/data/pg_log/postgresql-2026-02-05_094505.log
- Parsed 3,511,226 log entries in 1m18s
- Log start from 2026-02-05 09:00:00 to 2026-02-05 10:00:00
-
Overview
Global Stats
- 276 Number of unique normalized queries
- 346,046 Number of queries
- 2h56m25s Total query duration
- 2026-02-05 09:00:00 First query
- 2026-02-05 10:00:00 Last query
- 5,209 queries/s at 2026-02-05 09:00:04 Query peak
- 2h56m25s Total query duration
- 12s446ms Prepare/parse total duration
- 1m24s Bind total duration
- 2h54m48s Execute total duration
- 0 Number of events
- 0 Number of unique normalized events
- 0 Max number of times the same event was reported
- 0 Number of cancellation
- 45 Total number of automatic vacuums
- 59 Total number of automatic analyzes
- 730 Number temporary file
- 601.79 MiB Max size of temporary file
- 8.70 MiB Average size of temporary file
- 4,083 Total number of sessions
- 12 sessions at 2026-02-05 09:40:54 Session peak
- 18d21h23m20s Total duration of sessions
- 6m39s Average duration of sessions
- 84 Average queries per session
- 2s592ms Average queries duration per session
- 6m37s Average idle time per session
- 4,067 Total number of connections
- 57 connections/s at 2026-02-05 09:45:49 Connection peak
- 3 Total number of databases
SQL Traffic
Key values
- 5,209 queries/s Query Peak
- 2026-02-05 09:00:04 Date
SELECT Traffic
Key values
- 2,580 queries/s Query Peak
- 2026-02-05 09:00:04 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 177 queries/s Query Peak
- 2026-02-05 09:01:52 Date
Queries duration
Key values
- 2h56m25s 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 05 09 346,042 0ms 49s915ms 30ms 6m48s 7m8s 7m20s 10 4 0ms 0ms 0ms 0ms 0ms 0ms Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Feb 05 09 116,638 26 0ms 0ms 0ms 0ms 10 2 0 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Feb 05 09 32,567 2,403 16 96 0ms 0ms 0ms 0ms 10 0 0 0 0 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Feb 05 09 30,674 139,356 4.54 18.45% 10 0 2 2.00 0.00% Day Hour Count Average / Second Feb 05 09 4,067 1.13/s 10 0 0.00/s Day Hour Count Average Duration Average idle time Feb 05 09 4,083 6m39s 6m37s 10 0 0ms 0ms -
Connections
Established Connections
Key values
- 57 connections Connection Peak
- 2026-02-05 09:45:49 Date
Connections per database
Key values
- acaweb_fx Main Database
- 4,067 connections Total
Connections per user
Key values
- postgres Main User
- 4,067 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 1275 connections
- 4,067 Total connections
Host Count 127.0.0.1 114 182.165.1.54 2 192.168.0.114 5 192.168.0.216 101 192.168.0.74 584 192.168.0.84 2 192.168.1.127 14 192.168.1.131 2 192.168.1.145 216 192.168.1.15 635 192.168.1.20 240 192.168.1.238 2 192.168.1.239 8 192.168.1.90 65 192.168.2.126 48 192.168.2.182 12 192.168.3.199 36 192.168.4.136 4 192.168.4.142 1,275 192.168.4.150 10 192.168.4.158 4 192.168.4.222 1 192.168.4.238 12 192.168.4.33 100 192.168.4.66 1 192.168.4.98 330 [local] 244 -
Sessions
Simultaneous sessions
Key values
- 12 sessions Session Peak
- 2026-02-05 09:40:54 Date
Histogram of session times
Key values
- 3,301 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 4,083 sessions Total
Sessions per user
Key values
- postgres Main User
- 4,083 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 4,083 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 114 8s978ms 78ms 182.165.1.54 2 16h41m40s 8h20m50s 192.168.0.114 4 35m1s 8m45s 192.168.0.171 5 4d12h59m17s 21h47m51s 192.168.0.216 101 1m2s 617ms 192.168.0.74 584 23h10m54s 2m22s 192.168.0.84 2 23h59m22s 11h59m41s 192.168.1.127 14 29s127ms 2s80ms 192.168.1.131 2 23h59m20s 11h59m40s 192.168.1.145 217 2d2h9m6s 13m52s 192.168.1.15 640 1d13h25m1s 3m30s 192.168.1.154 4 3d9h43m34s 20h25m53s 192.168.1.20 241 1d17h8m23s 10m14s 192.168.1.238 2 23h59m28s 11h59m44s 192.168.1.239 8 52ms 6ms 192.168.1.90 65 36s377ms 559ms 192.168.2.126 48 17s631ms 367ms 192.168.2.182 12 962ms 80ms 192.168.3.199 36 1s402ms 38ms 192.168.4.136 4 40ms 10ms 192.168.4.142 1,275 8m30s 400ms 192.168.4.150 11 21h2m39s 1h54m47s 192.168.4.158 4 26s503ms 6s625ms 192.168.4.222 1 45s558ms 45s558ms 192.168.4.238 12 15s371ms 1s280ms 192.168.4.33 100 11m33s 6s934ms 192.168.4.66 1 169ms 169ms 192.168.4.98 330 18s184ms 55ms [local] 244 5m1s 1s236ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 9,071 buffers Checkpoint Peak
- 2026-02-05 09:04:26 Date
- 210.001 seconds Highest write time
- 0.017 seconds Sync time
Checkpoints Wal files
Key values
- 5 files Wal files usage Peak
- 2026-02-05 09:09:26 Date
Checkpoints distance
Key values
- 164.96 Mo Distance Peak
- 2026-02-05 09:09:26 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Feb 05 09 51,566 2,065.662s 0.059s 2,066.062s 10 0 0s 0s 0s Day Hour Added Removed Recycled Synced files Longest sync Average sync Feb 05 09 0 0 26 2,052 0.006s 0s 10 0 0 0 0 0s 0s Day Hour Count Avg time (sec) Feb 05 09 0 0s 10 0 0s Day Hour Mean distance Mean estimate Feb 05 09 34,729.83 kB 68,385.00 kB 10 0.00 kB 0.00 kB -
Temporary Files
Size of temporary files
Key values
- 601.79 MiB Temp Files size Peak
- 2026-02-05 09:14:04 Date
Number of temporary files
Key values
- 30 per second Temp Files Peak
- 2026-02-05 09:02:12 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Feb 05 09 730 6.20 GiB 8.70 MiB 10 0 0 0 Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 81 397.68 MiB 4.85 MiB 4.96 MiB 4.91 MiB select resultuid from relevance_fibonacci_results order by resultuid desc limit ?), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp)))), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;-
SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4)) AND ($5 = 0 OR s.exchange in ($6)) AND ($7 = 0 OR coalesce(bim.code, s.symbol) in ($8)) AND ($9 = 0 OR fr.pattern in ($10)) AND ($11 = 0 OR fr.patternlengthbars <= $12) AND ($13 = 0 OR ($14 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($15 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $16 OR relevant = 1) AND ($17 = 0 OR age <= $18) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2026-02-05 09:45:52 Duration: 0ms
2 29 1.65 GiB 8.77 MiB 157.52 MiB 58.34 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), 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: 2026-02-05 09:50:05 Duration: 0ms
3 28 94.43 MiB 3.25 MiB 3.46 MiB 3.37 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: 2026-02-05 09:46:29 Duration: 0ms
4 19 162.72 MiB 8.56 MiB 8.57 MiB 8.56 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: 2026-02-05 09:46:47 Duration: 0ms
5 16 619.88 MiB 38.74 MiB 38.74 MiB 38.74 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: 2026-02-05 09:46:13 Duration: 0ms
6 16 1.11 GiB 71.12 MiB 71.12 MiB 71.12 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: 2026-02-05 09:46:18 Duration: 0ms
7 8 1.05 GiB 133.99 MiB 134.04 MiB 134.02 MiB select updateresultsmaterializedview ();-
select updateresultsmaterializedview ();
Date: 2026-02-05 09:47:16 Duration: 0ms
8 4 342.46 MiB 85.55 MiB 85.69 MiB 85.62 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2026-02-05 09:47:06 Duration: 0ms
Queries generating the largest temporary files
Rank Size Query 1 157.52 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 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: 2026-02-05 09:20:08 ]
2 146.32 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: 2026-02-05 09:50:05 ]
3 134.04 MiB select updateresultsmaterializedview ();[ Date: 2026-02-05 09:32:13 ]
4 134.03 MiB select updateresultsmaterializedview ();[ Date: 2026-02-05 09:02:17 ]
5 134.03 MiB select updateresultsmaterializedview ();[ Date: 2026-02-05 09:47:16 ]
6 134.02 MiB select updateresultsmaterializedview ();[ Date: 2026-02-05 09:35:33 ]
7 134.02 MiB select updateresultsmaterializedview ();[ Date: 2026-02-05 09:50:32 ]
8 134.01 MiB select updateresultsmaterializedview ();[ Date: 2026-02-05 09:17:12 ]
9 134.00 MiB select updateresultsmaterializedview ();[ Date: 2026-02-05 09:05:32 ]
10 133.99 MiB select updateresultsmaterializedview ();[ Date: 2026-02-05 09:20:32 ]
11 109.66 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: 2026-02-05 09:40:04 ]
12 101.65 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: 2026-02-05 09:00:06 ]
13 100.58 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: 2026-02-05 09:00:05 ]
14 100.12 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: 2026-02-05 09:40:06 ]
15 91.13 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: 2026-02-05 09:30:04 ]
16 85.71 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: 2026-02-05 09:30:05 ]
17 85.69 MiB select updateageforrelevantresults ();[ Date: 2026-02-05 09:02:06 ]
18 85.63 MiB select updateageforrelevantresults ();[ Date: 2026-02-05 09:32:05 ]
19 85.59 MiB select updateageforrelevantresults ();[ Date: 2026-02-05 09:47:06 ]
20 85.55 MiB select updateageforrelevantresults ();[ Date: 2026-02-05 09:17:04 ]
-
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 (21) Main table analyzed (database acaweb_fx)
- 59 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 21 acaweb_fx.pg_catalog.pg_attribute 5 acaweb_fx.public.relevance_keylevels_results 4 acaweb_fx.pg_catalog.pg_class 4 acaweb_fx.public.relevance_fibonacci_results 4 acaweb_fx.pg_catalog.pg_type 4 acaweb_fx.public.relevance_autochartist_results 4 acaweb_fx.public.datafeeds_latestrun 3 acaweb_fx.pg_catalog.pg_depend 2 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.pg_catalog.pg_index 1 acaweb_fx.public.t60 1 acaweb_fx.public.autochartist_symbolupdates 1 socialmedia.public.processes 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.symbollatestupdatetime 1 Total 59 Vacuums per table
Key values
- public.solr_relevance_old (21) Main table vacuumed on database acaweb_fx
- 45 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 21 17 16,094 0 84 0 34 10,566 1,088 5,758,252 acaweb_fx.pg_catalog.pg_attribute 5 5 4,287 0 773 0 335 1,842 724 4,130,198 acaweb_fx.public.datafeeds_latestrun 3 0 360 0 5 0 0 39 5 36,370 acaweb_fx.pg_toast.pg_toast_2619 2 2 265 0 52 0 0 185 53 224,490 acaweb_fx.pg_catalog.pg_type 2 2 324 0 77 0 0 150 66 289,110 acaweb_fx.public.relevance_keylevels_results 2 2 7,305 0 189 2 207 1,744 175 609,221 acaweb_fx.pg_catalog.pg_class 2 2 923 0 124 0 0 308 145 655,327 acaweb_fx.public.relevance_autochartist_results 2 2 7,075 0 144 2 481 1,435 131 448,129 acaweb_fx.public.relevance_fibonacci_results 2 2 2,472 0 40 2 104 351 23 91,354 acaweb_fx.public.autochartist_symbolupdates 1 1 22,880 0 2,272 3 38,287 6,313 4,734 1,706,823 acaweb_fx.pg_catalog.pg_statistic 1 1 995 0 140 0 594 466 120 513,327 acaweb_fx.public.relevance_consecutivecandles_results 1 1 72 0 8 0 0 20 4 25,876 acaweb_fx.public.latest_t15_candle_view 1 1 66 0 1 0 0 6 1 9,037 Total 45 38 63,118 47,354 3,909 9 40,042 23,425 7,269 14,497,514 Tuples removed per table
Key values
- public.solr_relevance_old (88783) Main table with removed tuples on database acaweb_fx
- 105936 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 21 17 88,783 142,547 18,943 0 4,157 acaweb_fx.pg_catalog.pg_attribute 5 5 7,761 54,260 685 0 1,313 acaweb_fx.public.autochartist_symbolupdates 1 1 5,090 47,215 86 0 40,691 acaweb_fx.public.relevance_autochartist_results 2 2 1,113 17,574 0 0 760 acaweb_fx.public.relevance_keylevels_results 2 2 1,009 24,006 0 0 558 acaweb_fx.pg_catalog.pg_type 2 2 692 2,898 6 4 84 acaweb_fx.pg_catalog.pg_statistic 1 1 660 3,779 0 0 1,194 acaweb_fx.pg_catalog.pg_class 2 2 285 3,308 10 0 300 acaweb_fx.public.relevance_fibonacci_results 2 2 163 2,904 0 0 204 acaweb_fx.public.datafeeds_latestrun 3 0 161 42 0 0 48 acaweb_fx.pg_toast.pg_toast_2619 2 2 122 347 17 0 102 acaweb_fx.public.latest_t15_candle_view 1 1 56 14 0 0 1 acaweb_fx.public.relevance_consecutivecandles_results 1 1 41 288 0 0 7 Total 45 38 105,936 299,182 19,747 4 49,419 Pages removed per table
Key values
- pg_catalog.pg_type (4) Main table with removed pages on database acaweb_fx
- 4 pages Total removed
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_catalog.pg_type 2 2 692 4 acaweb_fx.pg_toast.pg_toast_2619 2 2 122 0 acaweb_fx.public.autochartist_symbolupdates 1 1 5090 0 acaweb_fx.public.datafeeds_latestrun 3 0 161 0 acaweb_fx.pg_catalog.pg_statistic 1 1 660 0 acaweb_fx.pg_catalog.pg_attribute 5 5 7761 0 acaweb_fx.public.relevance_consecutivecandles_results 1 1 41 0 acaweb_fx.public.latest_t15_candle_view 1 1 56 0 acaweb_fx.public.relevance_keylevels_results 2 2 1009 0 acaweb_fx.pg_catalog.pg_class 2 2 285 0 acaweb_fx.public.solr_relevance_old 21 17 88783 0 acaweb_fx.public.relevance_autochartist_results 2 2 1113 0 acaweb_fx.public.relevance_fibonacci_results 2 2 163 0 Total 45 38 105,936 4 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Feb 05 09 45 59 10 0 0 - 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
- 116,640 Total read queries
- 49,629 Total write queries
Queries by database
Key values
- unknown Main database
- 345,082 Requests
- 2h54m48s (unknown)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 846 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 161 0ms select 72 0ms tcl 331 0ms update 40 0ms socialmedia Total 118 0ms others 14 0ms select 100 0ms tcl 4 0ms unknown Total 345,082 2h54m48s copy from 16 0ms cte 13,603 0ms insert 32,567 0ms others 6,578 0ms select 116,468 0ms tcl 463 0ms update 2,363 0ms Queries by user
Key values
- unknown Main user
- 345,082 Requests
User Request type Count Duration postgres Total 964 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 175 0ms select 172 0ms tcl 335 0ms update 40 0ms unknown Total 345,082 2h54m48s copy from 16 0ms cte 13,603 0ms insert 32,567 0ms others 6,578 0ms select 116,468 0ms tcl 463 0ms update 2,363 0ms Duration by user
Key values
- 2h54m48s (unknown) Main time consuming user
User Request type Count Duration postgres Total 964 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 175 0ms select 172 0ms tcl 335 0ms update 40 0ms unknown Total 345,082 2h54m48s copy from 16 0ms cte 13,603 0ms insert 32,567 0ms others 6,578 0ms select 116,468 0ms tcl 463 0ms update 2,363 0ms Queries by host
Key values
- unknown Main host
- 346,046 Requests
- 2h54m48s (unknown)
- Main time consuming host
Queries by application
Key values
- unknown Main application
- 345,688 Requests
- 2h54m48s (unknown)
- Main time consuming application
Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2026-02-05 09:34:39 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 122,285 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 57 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 05 09 57 0ms 0ms 2 0ms 264 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 #2
Day Hour Count Duration Avg duration Feb 05 09 264 0ms 0ms 3 0ms 2,209 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 #3
Day Hour Count Duration Avg duration Feb 05 09 2,209 0ms 0ms 4 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 #4
Day Hour Count Duration Avg duration Feb 05 09 4 0ms 0ms 5 0ms 4 0ms 0ms 0ms select updaterelevantforrelevantresults ();Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Feb 05 09 4 0ms 0ms 6 0ms 14 0ms 0ms 0ms set datestyle = iso;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Feb 05 09 14 0ms 0ms 7 0ms 14 0ms 0ms 0ms set client_encoding to ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Feb 05 09 14 0ms 0ms 8 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 #8
Day Hour Count Duration Avg duration Feb 05 09 18 0ms 0ms 9 0ms 399 0ms 0ms 0ms commit;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Feb 05 09 399 0ms 0ms 10 0ms 391 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Feb 05 09 391 0ms 0ms 11 0ms 240 0ms 0ms 0ms select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Feb 05 09 240 0ms 0ms 12 0ms 240 0ms 0ms 0ms select system_identifier from pg_control_system ();Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Feb 05 09 240 0ms 0ms 13 0ms 14 0ms 0ms 0ms select groupid, exchange, groupname, symbol, longname from prfsymboltree where brokerid = ? order by groupname, symbol;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Feb 05 09 14 0ms 0ms 14 0ms 1 0ms 0ms 0ms insert into executionlogs (executionid, status, message, details, detailtype) values (?, ?, ?, ? 's EarlyBird Check - In, upgraded boarding, and transportation of pets and unaccompanied minors. Southwest Airlines Co. was incorporated in ? and is headquartered in Dallas, Texas. ", " Address ": " P.O. Box ?, Dallas, TX, United States, ? - 1611 ", " Phone ": " ? ? ? ", " WebURL ": " https: // www.southwest.com ", " LogoURL ": " https: // eodhistoricaldata.com / img / logos / US / luv.png ", " FullTimeEmployees ": ?, " UpdatedAt ": " ? - 02 - 04 ", " ticker ": " LUV.US ", " code ": " LUV ", " exchange ": " US ", " open ": ?.?, " close ": ?.?, " change ": ?.?, " change_percent ": ?.?, " change_str ": " + ?.? % ", " nocolor_change_str ": " + ?.? % ", " CloseHeading ": " u0627 u0644 u0627 u063a u0644 u0627 u0642 ", " OpenHeading ": " u0627 u0644 u0627 u0641 u062a u062a u0627 u062d ", " ChangeHeading ": " u0627 u0644 u062a u063a u064a u064a u0631 ", " change_str.fill_color ": " # ? " }, " ? ": { " Code ": " ODFL ", " Type ": " Common Stock ", " Name ": " Old Dominion Freight Line Inc ", " Exchange ": " NASDAQ ", " CurrencyCode ": " USD ", " CurrencyName ": " US Dollar ", " CurrencySymbol ": " $ ", " CountryName ": " USA ", " CountryISO ": " US ", " OpenFigi ": " BBG ? CHSS ? ", " ISIN ": " US ? ", " LEI ": " ? TWK ? WE ? T ? ", " PrimaryTicker ": " ODFL.US ", " CUSIP ": " ? ", " CIK ": " ? ", " EmployerIdNumber ": " ? - 0751714 ", " FiscalYearEnd ": " December ", " IPODate ": " ? - 10 - 24 ", " InternationalDomestic ": " Domestic ", " Sector ": " Industrials ", " Industry ": " Trucking ", " GicSector ": " Industrials ", " GicGroup ": " Transportation ", " GicIndustry ": " Ground Transportation ", " GicSubIndustry ": " Cargo Ground Transportation ", " HomeCategory ": " Domestic ", " IsDelisted ": false, " Description ": " Old Dominion Freight Line, Inc. operates as a less - than - truckload motor carrier in the United States and North America. The company offers regional, inter - regional, and national less - than - truckload services, as well as expedited transportation. It also provides various value - added services, including container drayage, truckload brokerage, and supply chain consulting. In addition, the company operates service and fleet maintenance centers. As of December ?, ?, it owned and operated ?, ? tractors, ?, ? linehaul trailers, and ?, ? pickup and delivery trailers. Old Dominion Freight Line, Inc. was founded in ? and is headquartered in Thomasville, North Carolina. ", " Address ": " ? Old Dominion Way, Thomasville, NC, United States, ? ", " Phone ": " ? ? ? ", " WebURL ": " https: // www.odfl.com ", " LogoURL ": " https: // eodhistoricaldata.com / img / logos / US / ODFL.png ", " FullTimeEmployees ": ?, " UpdatedAt ": " ? - 02 - 04 ", " ticker ": " ODFL.US ", " code ": " ODFL ", " exchange ": " US ", " open ": ?.?, " close ": ?.?, " change ": ?.?, " change_percent ": ?.?, " change_str ": " + ?.? % ", " nocolor_change_str ": " + ?.? % ", " CloseHeading ": " u0627 u0644 u0627 u063a u0644 u0627 u0642 ", " OpenHeading ": " u0627 u0644 u0627 u0641 u062a u062a u0627 u062d ", " ChangeHeading ": " u0627 u0644 u062a u063a u064a u064a u0631 ", " change_str.fill_color ": " # ? " }, " ? ": { " Code ": " VZ ", " Type ": " Common Stock ", " Name ": " Verizon Communications Inc ", " Exchange ": " NYSE ", " CurrencyCode ": " USD ", " CurrencyName ": " US Dollar ", " CurrencySymbol ": " $ ", " CountryName ": " USA ", " CountryISO ": " US ", " OpenFigi ": " BBG ? HS ? T ? ", " ISIN ": " US ? V ? ", " LEI ": " ? S ? QS ? UO ? OESLG ? Y ? ", " PrimaryTicker ": " VZ.US ", " CUSIP ": " ? ", " CIK ": " ? ", " EmployerIdNumber ": " ? - 2259884 ", " FiscalYearEnd ": " December ", " IPODate ": " ? - 07 - 23 ", " InternationalDomestic ": " International / Domestic ", " Sector ": " Communication Services ", " Industry ": " Telecom Services ", " GicSector ": " Communication Services ", " GicGroup ": " Telecommunication Services ", " GicIndustry ": " Diversified Telecommunication Services ", " GicSubIndustry ": " Integrated Telecommunication Services ", " HomeCategory ": " Domestic Primary ", " IsDelisted ": false, " Description ": " Verizon Communications Inc., through its subsidiaries, engages in the provision of communications, technology, information, and entertainment products and services to consumers, businesses, and governmental entities worldwide. It operates in two segments, Verizon Consumer Group (Consumer) and Verizon Business Group (Business).The Consumer segment provides wireless services across the wireless networks in the United States under the Verizon and TracFone brands and through wholesale and other arrangements; and fixed wireless access (FWA) broadband through its wireless networks, as well as related equipment and devices, such as smartphones, tablets, smart watches, and other wireless - enabled connected devices. The segment also offers wireline services in the Mid - Atlantic and Northeastern United States, as well as Washington D.C. through its fiber - optic network, Verizon Fios product portfolio, and a copper - based network. The Business segment provides wireless and wireline communications services and products, including FWA broadband, data, video and conferencing, corporate networking, security and managed network, local and long - distance voice, and network access services to deliver various IoT services and products to businesses, government customers, and wireless and wireline carriers in the United States and internationally. The company was formerly known as Bell Atlantic Corporation and changed its name to Verizon Communications Inc. in June ?.Verizon Communications Inc. was incorporated in ? and is headquartered in New York, New York. ", " Address ": " ? Avenue of the Americas, New York, NY, United States, ? ", " Phone ": " ? ? ? ", " WebURL ": " https: // www.verizon.com ", " LogoURL ": " https: // eodhistoricaldata.com / img / logos / US / vz.png ", " FullTimeEmployees ": ?, " UpdatedAt ": " ? - 02 - 05 ", " ticker ": " VZ.US ", " code ": " VZ ", " exchange ": " US ", " open ": ?.?, " close ": ?.?, " change ": ?.?, " change_percent ": ?.?, " change_str ": " + ?.? % ", " nocolor_change_str ": " + ?.? % ", " CloseHeading ": " u0627 u0644 u0627 u063a u0644 u0627 u0642 ", " OpenHeading ": " u0627 u0644 u0627 u0641 u062a u062a u0627 u062d ", " ChangeHeading ": " u0627 u0644 u062a u063a u064a u064a u0631 ", " change_str.fill_color ": " # ? " }, " ? ": { " Code ": " DECK ", " Type ": " Common Stock ", " Name ": " Deckers Outdoor Corporation ", " Exchange ": " NYSE ", " CurrencyCode ": " USD ", " CurrencyName ": " US Dollar ", " CurrencySymbol ": " $ ", " CountryName ": " USA ", " CountryISO ": " US ", " OpenFigi ": " BBG ? BKXYX ? ", " ISIN ": " US ? ", " LEI ": " ? LG ? W ? I ? K ? J ? ", " PrimaryTicker ": " DECK.US ", " CUSIP ": " ? ", " CIK ": " ? ", " EmployerIdNumber ": " ? - 3015862 ", " FiscalYearEnd ": " March ", " IPODate ": " ? - 10 - 14 ", " InternationalDomestic ": " Domestic ", " Sector ": " Consumer Cyclical ", " Industry ": " Footwear & Accessories ", " GicSector ": " Consumer Discretionary ", " GicGroup ": " Consumer Durables & Apparel ", " GicIndustry ": " Textiles, Apparel & Luxury Goods ", " GicSubIndustry ": " Footwear ", " HomeCategory ": " Domestic ", " IsDelisted ": false, " Description ": " Deckers Outdoor Corporation, together with its subsidiaries, designs, markets, and distributes footwear, apparel, and accessories for casual lifestyle use and high - performance activities in the United States and internationally. The company offers premium footwear, apparel, and accessories under the UGG brand name; footwear, such as running, trail, hiking, fitness, and lifestyle shoes, as well as apparel and accessories under the HOKA brand name; and sandals, shoes, and boots under the Teva brand name. It also provides a casual footwear fashion line under the Koolaburra brand name; and footwear products under the AHNU brand name. The company sells its products through domestic and international retailers, international distributors, and directly to its consumers through its direct - to - consumer business, which includes e - commerce websites and retail stores. Deckers Outdoor Corporation was founded in ? and is headquartered in Goleta, California. ", " Address ": " ? Coromar Drive, Goleta, CA, United States, ? ", " Phone ": " ? ? ? ", " WebURL ": " https: // www.deckers.com ", " LogoURL ": " https: // eodhistoricaldata.com / img / logos / US / DECK.png ", " FullTimeEmployees ": ?, " UpdatedAt ": " ? - 02 - 04 ", " ticker ": " DECK.US ", " code ": " DECK ", " exchange ": " US ", " open ": ?.?, " close ": ?.?, " change ": ?.?, " change_percent ": ?.?, " change_str ": " + ?.? % ", " nocolor_change_str ": " + ?.? % ", " CloseHeading ": " u0627 u0644 u0627 u063a u06[...];Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Feb 05 09 1 0ms 0ms 15 0ms 6 0ms 0ms 0ms select "public"."processes"."id" AS "id", "public"."processes"."locale" AS "locale", "public"."processes"."region" AS "region", "public"."processes"."schedule" AS "schedule", "public"."processes"."enabled" AS "enabled", "public"."processes"."live" AS "live", "public"."processes"."lastmodified" AS "lastmodified", "public"."processes"."lastrun" AS "lastrun", "public"."processes"."contenttypeid" AS "contenttypeid", "public"."processes"."brokerid" AS "brokerid", "public"."processes"."uuid" AS "uuid", "LT?"."name" AS "LA?", "LT?"."name" AS "LA?" 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" = ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Feb 05 09 6 0ms 0ms 16 0ms 344 0ms 0ms 0ms with rar_max as ( 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;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Feb 05 09 344 0ms 0ms 17 0ms 36 0ms 0ms 0ms select distinct classname, to_char(created_datetime, ?), to_char(cleared_datetime, ?), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = ? or cleared_datetime > current_timestamp - interval ?) order by created_datetime desc;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Feb 05 09 36 0ms 0ms 18 0ms 16 0ms 0ms 0ms with max_ra as ( select resultuid from relevance_fibonacci_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 left outer join relevance_fibonacci_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 fibonacci_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null);Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Feb 05 09 16 0ms 0ms 19 0ms 1 0ms 0ms 0ms select port from brokermt4authservers where brokerid = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Feb 05 09 1 0ms 0ms 20 0ms 226 0ms 0ms 0ms set statement_timeout = ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Feb 05 09 226 0ms 0ms Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 53,156 0ms 0ms 0ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Feb 05 09 53,154 0ms 0ms 10 2 0ms 0ms 2 19,060 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 05 09 19,060 0ms 0ms 3 11,389 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 05 09 11,389 0ms 0ms 4 7,870 0ms 0ms 0ms 0ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Feb 05 09 7,870 0ms 0ms 5 7,600 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 #5
Day Hour Count Duration Avg duration Feb 05 09 7,600 0ms 0ms 6 6,451 0ms 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ) select a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, s.exchange, s.symbol, s.longname, s.shortname, breakout, dtt.timezone, patternstartprice, patternendprice, qtytp, newlevels.profit, newlevels.stop, newlevels.filtered, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern inner join rar_max rm on ? = ? left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid left join lateral calc_cp_signal (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Feb 05 09 6,451 0ms 0ms 7 6,040 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 #7
Day Hour Count Duration Avg duration Feb 05 09 6,040 0ms 0ms 8 5,247 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 #8
Day Hour Count Duration Avg duration Feb 05 09 5,247 0ms 0ms 9 3,446 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 #9
Day Hour Count Duration Avg duration Feb 05 09 3,446 0ms 0ms 10 3,333 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 #10
Day Hour Count Duration Avg duration Feb 05 09 3,333 0ms 0ms 11 3,227 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 #11
Day Hour Count Duration Avg duration Feb 05 09 3,227 0ms 0ms 12 3,061 0ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Feb 05 09 3,061 0ms 0ms 13 3,026 0ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Feb 05 09 3,026 0ms 0ms 14 2,862 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 #14
Day Hour Count Duration Avg duration Feb 05 09 2,862 0ms 0ms 15 2,356 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 #15
Day Hour Count Duration Avg duration Feb 05 09 2,356 0ms 0ms 16 2,209 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 #16
Day Hour Count Duration Avg duration Feb 05 09 2,209 0ms 0ms 17 2,154 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 #17
Day Hour Count Duration Avg duration Feb 05 09 2,154 0ms 0ms 18 1,863 0ms 0ms 0ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Feb 05 09 1,863 0ms 0ms 19 1,305 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 05 09 1,305 0ms 0ms 20 1,140 0ms 0ms 0ms 0ms select * from status_perbroker;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Feb 05 09 1,140 0ms 0ms Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 0ms 0ms 0ms 57 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 05 09 57 0ms 0ms 2 0ms 0ms 0ms 264 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 #2
Day Hour Count Duration Avg duration Feb 05 09 264 0ms 0ms 3 0ms 0ms 0ms 2,209 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 #3
Day Hour Count Duration Avg duration Feb 05 09 2,209 0ms 0ms 4 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 #4
Day Hour Count Duration Avg duration Feb 05 09 4 0ms 0ms 5 0ms 0ms 0ms 4 0ms select updaterelevantforrelevantresults ();Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Feb 05 09 4 0ms 0ms 6 0ms 0ms 0ms 14 0ms set datestyle = iso;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Feb 05 09 14 0ms 0ms 7 0ms 0ms 0ms 14 0ms set client_encoding to ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Feb 05 09 14 0ms 0ms 8 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 #8
Day Hour Count Duration Avg duration Feb 05 09 18 0ms 0ms 9 0ms 0ms 0ms 399 0ms commit;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Feb 05 09 399 0ms 0ms 10 0ms 0ms 0ms 391 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Feb 05 09 391 0ms 0ms 11 0ms 0ms 0ms 240 0ms select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Feb 05 09 240 0ms 0ms 12 0ms 0ms 0ms 240 0ms select system_identifier from pg_control_system ();Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Feb 05 09 240 0ms 0ms 13 0ms 0ms 0ms 14 0ms select groupid, exchange, groupname, symbol, longname from prfsymboltree where brokerid = ? order by groupname, symbol;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Feb 05 09 14 0ms 0ms 14 0ms 0ms 0ms 1 0ms insert into executionlogs (executionid, status, message, details, detailtype) values (?, ?, ?, ? 's EarlyBird Check - In, upgraded boarding, and transportation of pets and unaccompanied minors. Southwest Airlines Co. was incorporated in ? and is headquartered in Dallas, Texas. ", " Address ": " P.O. Box ?, Dallas, TX, United States, ? - 1611 ", " Phone ": " ? ? ? ", " WebURL ": " https: // www.southwest.com ", " LogoURL ": " https: // eodhistoricaldata.com / img / logos / US / luv.png ", " FullTimeEmployees ": ?, " UpdatedAt ": " ? - 02 - 04 ", " ticker ": " LUV.US ", " code ": " LUV ", " exchange ": " US ", " open ": ?.?, " close ": ?.?, " change ": ?.?, " change_percent ": ?.?, " change_str ": " + ?.? % ", " nocolor_change_str ": " + ?.? % ", " CloseHeading ": " u0627 u0644 u0627 u063a u0644 u0627 u0642 ", " OpenHeading ": " u0627 u0644 u0627 u0641 u062a u062a u0627 u062d ", " ChangeHeading ": " u0627 u0644 u062a u063a u064a u064a u0631 ", " change_str.fill_color ": " # ? " }, " ? ": { " Code ": " ODFL ", " Type ": " Common Stock ", " Name ": " Old Dominion Freight Line Inc ", " Exchange ": " NASDAQ ", " CurrencyCode ": " USD ", " CurrencyName ": " US Dollar ", " CurrencySymbol ": " $ ", " CountryName ": " USA ", " CountryISO ": " US ", " OpenFigi ": " BBG ? CHSS ? ", " ISIN ": " US ? ", " LEI ": " ? TWK ? WE ? T ? ", " PrimaryTicker ": " ODFL.US ", " CUSIP ": " ? ", " CIK ": " ? ", " EmployerIdNumber ": " ? - 0751714 ", " FiscalYearEnd ": " December ", " IPODate ": " ? - 10 - 24 ", " InternationalDomestic ": " Domestic ", " Sector ": " Industrials ", " Industry ": " Trucking ", " GicSector ": " Industrials ", " GicGroup ": " Transportation ", " GicIndustry ": " Ground Transportation ", " GicSubIndustry ": " Cargo Ground Transportation ", " HomeCategory ": " Domestic ", " IsDelisted ": false, " Description ": " Old Dominion Freight Line, Inc. operates as a less - than - truckload motor carrier in the United States and North America. The company offers regional, inter - regional, and national less - than - truckload services, as well as expedited transportation. It also provides various value - added services, including container drayage, truckload brokerage, and supply chain consulting. In addition, the company operates service and fleet maintenance centers. As of December ?, ?, it owned and operated ?, ? tractors, ?, ? linehaul trailers, and ?, ? pickup and delivery trailers. Old Dominion Freight Line, Inc. was founded in ? and is headquartered in Thomasville, North Carolina. ", " Address ": " ? Old Dominion Way, Thomasville, NC, United States, ? ", " Phone ": " ? ? ? ", " WebURL ": " https: // www.odfl.com ", " LogoURL ": " https: // eodhistoricaldata.com / img / logos / US / ODFL.png ", " FullTimeEmployees ": ?, " UpdatedAt ": " ? - 02 - 04 ", " ticker ": " ODFL.US ", " code ": " ODFL ", " exchange ": " US ", " open ": ?.?, " close ": ?.?, " change ": ?.?, " change_percent ": ?.?, " change_str ": " + ?.? % ", " nocolor_change_str ": " + ?.? % ", " CloseHeading ": " u0627 u0644 u0627 u063a u0644 u0627 u0642 ", " OpenHeading ": " u0627 u0644 u0627 u0641 u062a u062a u0627 u062d ", " ChangeHeading ": " u0627 u0644 u062a u063a u064a u064a u0631 ", " change_str.fill_color ": " # ? " }, " ? ": { " Code ": " VZ ", " Type ": " Common Stock ", " Name ": " Verizon Communications Inc ", " Exchange ": " NYSE ", " CurrencyCode ": " USD ", " CurrencyName ": " US Dollar ", " CurrencySymbol ": " $ ", " CountryName ": " USA ", " CountryISO ": " US ", " OpenFigi ": " BBG ? HS ? T ? ", " ISIN ": " US ? V ? ", " LEI ": " ? S ? QS ? UO ? OESLG ? Y ? ", " PrimaryTicker ": " VZ.US ", " CUSIP ": " ? ", " CIK ": " ? ", " EmployerIdNumber ": " ? - 2259884 ", " FiscalYearEnd ": " December ", " IPODate ": " ? - 07 - 23 ", " InternationalDomestic ": " International / Domestic ", " Sector ": " Communication Services ", " Industry ": " Telecom Services ", " GicSector ": " Communication Services ", " GicGroup ": " Telecommunication Services ", " GicIndustry ": " Diversified Telecommunication Services ", " GicSubIndustry ": " Integrated Telecommunication Services ", " HomeCategory ": " Domestic Primary ", " IsDelisted ": false, " Description ": " Verizon Communications Inc., through its subsidiaries, engages in the provision of communications, technology, information, and entertainment products and services to consumers, businesses, and governmental entities worldwide. It operates in two segments, Verizon Consumer Group (Consumer) and Verizon Business Group (Business).The Consumer segment provides wireless services across the wireless networks in the United States under the Verizon and TracFone brands and through wholesale and other arrangements; and fixed wireless access (FWA) broadband through its wireless networks, as well as related equipment and devices, such as smartphones, tablets, smart watches, and other wireless - enabled connected devices. The segment also offers wireline services in the Mid - Atlantic and Northeastern United States, as well as Washington D.C. through its fiber - optic network, Verizon Fios product portfolio, and a copper - based network. The Business segment provides wireless and wireline communications services and products, including FWA broadband, data, video and conferencing, corporate networking, security and managed network, local and long - distance voice, and network access services to deliver various IoT services and products to businesses, government customers, and wireless and wireline carriers in the United States and internationally. The company was formerly known as Bell Atlantic Corporation and changed its name to Verizon Communications Inc. in June ?.Verizon Communications Inc. was incorporated in ? and is headquartered in New York, New York. ", " Address ": " ? Avenue of the Americas, New York, NY, United States, ? ", " Phone ": " ? ? ? ", " WebURL ": " https: // www.verizon.com ", " LogoURL ": " https: // eodhistoricaldata.com / img / logos / US / vz.png ", " FullTimeEmployees ": ?, " UpdatedAt ": " ? - 02 - 05 ", " ticker ": " VZ.US ", " code ": " VZ ", " exchange ": " US ", " open ": ?.?, " close ": ?.?, " change ": ?.?, " change_percent ": ?.?, " change_str ": " + ?.? % ", " nocolor_change_str ": " + ?.? % ", " CloseHeading ": " u0627 u0644 u0627 u063a u0644 u0627 u0642 ", " OpenHeading ": " u0627 u0644 u0627 u0641 u062a u062a u0627 u062d ", " ChangeHeading ": " u0627 u0644 u062a u063a u064a u064a u0631 ", " change_str.fill_color ": " # ? " }, " ? ": { " Code ": " DECK ", " Type ": " Common Stock ", " Name ": " Deckers Outdoor Corporation ", " Exchange ": " NYSE ", " CurrencyCode ": " USD ", " CurrencyName ": " US Dollar ", " CurrencySymbol ": " $ ", " CountryName ": " USA ", " CountryISO ": " US ", " OpenFigi ": " BBG ? BKXYX ? ", " ISIN ": " US ? ", " LEI ": " ? LG ? W ? I ? K ? J ? ", " PrimaryTicker ": " DECK.US ", " CUSIP ": " ? ", " CIK ": " ? ", " EmployerIdNumber ": " ? - 3015862 ", " FiscalYearEnd ": " March ", " IPODate ": " ? - 10 - 14 ", " InternationalDomestic ": " Domestic ", " Sector ": " Consumer Cyclical ", " Industry ": " Footwear & Accessories ", " GicSector ": " Consumer Discretionary ", " GicGroup ": " Consumer Durables & Apparel ", " GicIndustry ": " Textiles, Apparel & Luxury Goods ", " GicSubIndustry ": " Footwear ", " HomeCategory ": " Domestic ", " IsDelisted ": false, " Description ": " Deckers Outdoor Corporation, together with its subsidiaries, designs, markets, and distributes footwear, apparel, and accessories for casual lifestyle use and high - performance activities in the United States and internationally. The company offers premium footwear, apparel, and accessories under the UGG brand name; footwear, such as running, trail, hiking, fitness, and lifestyle shoes, as well as apparel and accessories under the HOKA brand name; and sandals, shoes, and boots under the Teva brand name. It also provides a casual footwear fashion line under the Koolaburra brand name; and footwear products under the AHNU brand name. The company sells its products through domestic and international retailers, international distributors, and directly to its consumers through its direct - to - consumer business, which includes e - commerce websites and retail stores. Deckers Outdoor Corporation was founded in ? and is headquartered in Goleta, California. ", " Address ": " ? Coromar Drive, Goleta, CA, United States, ? ", " Phone ": " ? ? ? ", " WebURL ": " https: // www.deckers.com ", " LogoURL ": " https: // eodhistoricaldata.com / img / logos / US / DECK.png ", " FullTimeEmployees ": ?, " UpdatedAt ": " ? - 02 - 04 ", " ticker ": " DECK.US ", " code ": " DECK ", " exchange ": " US ", " open ": ?.?, " close ": ?.?, " change ": ?.?, " change_percent ": ?.?, " change_str ": " + ?.? % ", " nocolor_change_str ": " + ?.? % ", " CloseHeading ": " u0627 u0644 u0627 u063a u06[...];Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Feb 05 09 1 0ms 0ms 15 0ms 0ms 0ms 6 0ms select "public"."processes"."id" AS "id", "public"."processes"."locale" AS "locale", "public"."processes"."region" AS "region", "public"."processes"."schedule" AS "schedule", "public"."processes"."enabled" AS "enabled", "public"."processes"."live" AS "live", "public"."processes"."lastmodified" AS "lastmodified", "public"."processes"."lastrun" AS "lastrun", "public"."processes"."contenttypeid" AS "contenttypeid", "public"."processes"."brokerid" AS "brokerid", "public"."processes"."uuid" AS "uuid", "LT?"."name" AS "LA?", "LT?"."name" AS "LA?" 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" = ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Feb 05 09 6 0ms 0ms 16 0ms 0ms 0ms 344 0ms with rar_max as ( 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;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Feb 05 09 344 0ms 0ms 17 0ms 0ms 0ms 36 0ms select distinct classname, to_char(created_datetime, ?), to_char(cleared_datetime, ?), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = ? or cleared_datetime > current_timestamp - interval ?) order by created_datetime desc;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Feb 05 09 36 0ms 0ms 18 0ms 0ms 0ms 16 0ms with max_ra as ( select resultuid from relevance_fibonacci_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 left outer join relevance_fibonacci_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 fibonacci_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null);Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Feb 05 09 16 0ms 0ms 19 0ms 0ms 0ms 1 0ms select port from brokermt4authservers where brokerid = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Feb 05 09 1 0ms 0ms 20 0ms 0ms 0ms 226 0ms set statement_timeout = ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Feb 05 09 226 0ms 0ms Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 5s13ms 4,551 0ms 20ms 1ms WITH rar_max as ( ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Feb 05 09 4,551 5s13ms 1ms -
WITH rar_max as ( ;
Date: 2026-02-05 09:21:24 Duration: 20ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-02-05 09:21:54 Duration: 18ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-02-05 09:53:01 Duration: 15ms Database: postgres
2 2s743ms 6,289 0ms 14ms 0ms SELECT ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 09 6,289 2s743ms 0ms -
SELECT ;
Date: 2026-02-05 09:46:18 Duration: 14ms Database: postgres
-
SELECT ;
Date: 2026-02-05 09:46:49 Duration: 12ms Database: postgres
-
SELECT ;
Date: 2026-02-05 09:31:00 Duration: 10ms Database: postgres
3 1s817ms 1,217 0ms 13ms 1ms SELECT symbolid, ;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 09 1,217 1s817ms 1ms -
SELECT symbolid, ;
Date: 2026-02-05 09:00:57 Duration: 13ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-02-05 09:00:42 Duration: 11ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-02-05 09:30:39 Duration: 7ms Database: postgres
4 566ms 495 0ms 5ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 09 495 566ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-05 09:00:52 Duration: 5ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-05 09:31:23 Duration: 2ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-05 09:00:22 Duration: 2ms Database: postgres
5 484ms 3,061 0ms 6ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 09 3,061 484ms 0ms -
SET extra_float_digits = 3;
Date: 2026-02-05 09:45:55 Duration: 6ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-02-05 09:08:19 Duration: 4ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-02-05 09:50:13 Duration: 3ms Database: postgres
6 310ms 3,121 0ms 9ms 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 09 3,121 310ms 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: 2026-02-05 09:31:28 Duration: 9ms 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: 2026-02-05 09:01:40 Duration: 1ms 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: 2026-02-05 09:32:16 Duration: 0ms Database: postgres
7 225ms 2,027 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 09 2,027 225ms 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: 2026-02-05 09:00:56 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: 2026-02-05 09:11:52 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: 2026-02-05 09:01:26 Duration: 0ms Database: postgres
8 202ms 3,777 0ms 5ms 0ms select 1;Times Reported Time consuming prepare #8
Day Hour Count Duration Avg duration 09 3,777 202ms 0ms -
select 1;
Date: 2026-02-05 09:10:53 Duration: 5ms Database: postgres
-
select 1;
Date: 2026-02-05 09:01:11 Duration: 4ms Database: postgres
-
select 1;
Date: 2026-02-05 09:45:42 Duration: 2ms Database: postgres
9 189ms 1,146 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 #9
Day Hour Count Duration Avg duration 09 1,146 189ms 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: 2026-02-05 09:47:24 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: 2026-02-05 09:56:55 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: 2026-02-05 09:17:00 Duration: 0ms Database: postgres
10 143ms 748 0ms 3ms 0ms select category, ;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 09 748 143ms 0ms -
select category, ;
Date: 2026-02-05 09:10:53 Duration: 3ms Database: postgres
-
select category, ;
Date: 2026-02-05 09:10:53 Duration: 0ms Database: postgres
-
select category, ;
Date: 2026-02-05 09:45:57 Duration: 0ms Database: postgres
11 95ms 65 0ms 5ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 09 65 95ms 1ms -
WITH last_candle AS ( ;
Date: 2026-02-05 09:00:59 Duration: 5ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-02-05 09:52:00 Duration: 4ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-02-05 09:36:00 Duration: 4ms Database: postgres
12 80ms 12 4ms 7ms 6ms with sym_info as ( ;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 09 12 80ms 6ms -
with sym_info as ( ;
Date: 2026-02-05 09:21:45 Duration: 7ms Database: postgres
-
with sym_info as ( ;
Date: 2026-02-05 09:06:46 Duration: 6ms Database: postgres
-
with sym_info as ( ;
Date: 2026-02-05 09:36:51 Duration: 6ms Database: postgres
13 50ms 3,026 0ms 8ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 09 3,026 50ms 0ms -
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-02-05 09:45:42 Duration: 8ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-02-05 09:43:28 Duration: 1ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-02-05 09:30:29 Duration: 1ms Database: postgres
14 50ms 18 1ms 4ms 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 #14
Day Hour Count Duration Avg duration 09 18 50ms 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: 2026-02-05 09:31:09 Duration: 4ms 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: 2026-02-05 09:31:10 Duration: 4ms 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: 2026-02-05 09:11:16 Duration: 3ms Database: postgres
15 44ms 36 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 #15
Day Hour Count Duration Avg duration 09 36 44ms 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: 2026-02-05 09:25:44 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: 2026-02-05 09:46:01 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: 2026-02-05 09:10:42 Duration: 1ms Database: postgres
16 43ms 20 1ms 6ms 2ms with wh_patitioned as ( ;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 09 20 43ms 2ms -
with wh_patitioned as ( ;
Date: 2026-02-05 09:00:56 Duration: 6ms Database: postgres
-
with wh_patitioned as ( ;
Date: 2026-02-05 09:00:58 Duration: 6ms Database: postgres
-
with wh_patitioned as ( ;
Date: 2026-02-05 09:26:41 Duration: 2ms Database: postgres
17 42ms 228 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 #17
Day Hour Count Duration Avg duration 09 228 42ms 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: 2026-02-05 09:13:52 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: 2026-02-05 09:13:51 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: 2026-02-05 09:13:53 Duration: 0ms Database: postgres
18 37ms 36 0ms 1ms 1ms 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 #18
Day Hour Count Duration Avg duration 09 36 37ms 1ms -
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: 2026-02-05 09:20:43 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: 2026-02-05 09:20:43 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: 2026-02-05 09:51:02 Duration: 1ms Database: postgres
19 27ms 40 0ms 2ms 0ms select distinct s.statsid as statsid, sy.exchange as name;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 09 40 27ms 0ms -
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-02-05 09:10:51 Duration: 2ms Database: postgres
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-02-05 09:10:51 Duration: 2ms Database: postgres
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-02-05 09:10:51 Duration: 1ms Database: postgres
20 26ms 41 0ms 2ms 0ms WITH rcr_max as ( ;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 09 41 26ms 0ms -
WITH rcr_max as ( ;
Date: 2026-02-05 09:31:43 Duration: 2ms Database: postgres
-
WITH rcr_max as ( ;
Date: 2026-02-05 09:31:45 Duration: 2ms Database: postgres
-
WITH rcr_max as ( ;
Date: 2026-02-05 09:16:49 Duration: 2ms Database: postgres
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 53s396ms 12,575 0ms 77ms 4ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Feb 05 09 12,575 53s396ms 4ms -
WITH rar_max as ( ;
Date: 2026-02-05 09:05:56 Duration: 77ms Database: postgres parameters: $1 = 't', $2 = '689', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '310', $14 = '#AAPL', $15 = '#ADS', $16 = '#AIG', $17 = '#ALV', $18 = '#AMZN', $19 = '#AXP', $20 = '#BA', $21 = '#BABA', $22 = '#BAC', $23 = '#BAS', $24 = '#BAYN', $25 = '#BEI', $26 = '#BIDU', $27 = '#BMW', $28 = '#C', $29 = '#CAT', $30 = '#CBK', $31 = '#CL', $32 = '#CSCO', $33 = '#CVX', $34 = '#DAI', $35 = '#DB1', $36 = '#DBK', $37 = '#DIS', $38 = '#DPW', $39 = '#DTE', $40 = '#EBAY', $41 = '#EON', $42 = '#F', $43 = '#FB', $44 = '#FDX', $45 = '#FME', $46 = '#GE', $47 = '#GM', $48 = '#GOOG', $49 = '#GS', $50 = '#HPQ', $51 = '#IBM', $52 = '#IFX', $53 = '#INTC', $54 = '#JD', $55 = '#JNJ', $56 = '#JPM', $57 = '#KO', $58 = '#LHA', $59 = '#LMT', $60 = '#MA', $61 = '#MCD', $62 = '#META', $63 = '#MMM', $64 = '#MSFT', $65 = '#MUV2', $66 = '#NFLX', $67 = '#NKE', $68 = '#NTES', $69 = '#ORCL', $70 = '#PFE', $71 = '#PG', $72 = '#QCOM', $73 = '#RACE', $74 = '#RWE', $75 = '#SAP', $76 = '#SIE', $77 = '#T', $78 = '#UBER', $79 = '#V', $80 = '#VOW', $81 = '#WB', $82 = '#XOM', $83 = 'AUDCAD', $84 = 'AUDCHF', $85 = 'AUDJPY', $86 = 'AUDNZD', $87 = 'AUDUSD', $88 = 'AUS200', $89 = 'BRENT', $90 = 'BTCUSD', $91 = 'CADCHF', $92 = 'CADJPY', $93 = 'CHFJPY', $94 = 'CHI50', $95 = 'ESP35', $96 = 'ETHUSD', $97 = 'EU50', $98 = 'EURAUD', $99 = 'EURCAD', $100 = 'EURCHF', $101 = 'EURGBP', $102 = 'EURHUF', $103 = 'EURJPY', $104 = 'EURNZD', $105 = 'EURPLN', $106 = 'EURUSD', $107 = 'FRA40', $108 = 'GBPAUD', $109 = 'GBPCAD', $110 = 'GBPCHF', $111 = 'GBPJPY', $112 = 'GBPNZD', $113 = 'GBPUSD', $114 = 'GER30', $115 = 'HK50', $116 = 'HKCH50', $117 = 'IT40', $118 = 'JP225', $119 = 'LTCUSD', $120 = 'NAS100', $121 = 'NZDCAD', $122 = 'NZDCHF', $123 = 'NZDJPY', $124 = 'NZDUSD', $125 = 'SPX500', $126 = 'UK100', $127 = 'US30', $128 = 'USDCAD', $129 = 'USDCHF', $130 = 'USDCNH', $131 = 'USDCZK', $132 = 'USDDKK', $133 = 'USDHKD', $134 = 'USDHUF', $135 = 'USDJPY', $136 = 'USDMXN', $137 = 'USDNOK', $138 = 'USDPLN', $139 = 'USDSEK', $140 = 'USDSGD', $141 = 'USDTRY', $142 = 'USDX', $143 = 'USDZAR', $144 = 'WTI', $145 = 'XAGUSD', $146 = 'XAUUSD', $147 = '#ADS', $148 = '#ALV', $149 = '#BAS', $150 = '#BAYN', $151 = '#BEI', $152 = '#BMW', $153 = '#CBK', $154 = '#DAI', $155 = '#DB1', $156 = '#DBK', $157 = '#DPW', $158 = '#DTE', $159 = '#EON', $160 = '#FME', $161 = '#IFX', $162 = '#LHA', $163 = '#MUV2', $164 = '#RWE', $165 = '#SAP', $166 = '#SIE', $167 = '#VOW', $168 = 'AUDCAD', $169 = 'AUDCHF', $170 = 'AUDJPY', $171 = 'AUDNZD', $172 = 'AUDUSD', $173 = 'CADCHF', $174 = 'CADJPY', $175 = 'CHFJPY', $176 = 'EURAUD', $177 = 'EURCAD', $178 = 'EURCHF', $179 = 'EURGBP', $180 = 'EURHUF', $181 = 'EURJPY', $182 = 'EURNZD', $183 = 'EURPLN', $184 = 'EURUSD', $185 = 'GBPAUD', $186 = 'GBPCAD', $187 = 'GBPCHF', $188 = 'GBPJPY', $189 = 'GBPNZD', $190 = 'GBPUSD', $191 = 'NZDCAD', $192 = 'NZDCHF', $193 = 'NZDJPY', $194 = 'NZDUSD', $195 = 'USDCAD', $196 = 'USDCHF', $197 = 'USDCNH', $198 = 'USDCZK', $199 = 'USDDKK', $200 = 'USDHKD', $201 = 'USDHUF', $202 = 'USDJPY', $203 = 'USDMXN', $204 = 'USDNOK', $205 = 'USDPLN', $206 = 'USDSEK', $207 = 'USDSGD', $208 = 'USDTRY', $209 = 'USDX', $210 = 'USDZAR', $211 = 'XAGUSD', $212 = 'XAUUSD', $213 = 'BTCUSD', $214 = 'ETHUSD', $215 = 'LTCUSD', $216 = 'AUDCAD', $217 = 'AUDCHF', $218 = 'AUDJPY', $219 = 'AUDNZD', $220 = 'CADCHF', $221 = 'CADJPY', $222 = 'CHFJPY', $223 = 'EURAUD', $224 = 'EURCAD', $225 = 'EURCHF', $226 = 'EURGBP', $227 = 'EURHUF', $228 = 'EURJPY', $229 = 'EURNZD', $230 = 'EURPLN', $231 = 'GBPAUD', $232 = 'GBPCAD', $233 = 'GBPCHF', $234 = 'GBPJPY', $235 = 'GBPNZD', $236 = 'NZDCAD', $237 = 'NZDCHF', $238 = 'NZDJPY', $239 = 'USDCNH', $240 = 'USDCZK', $241 = 'USDDKK', $242 = 'USDHKD', $243 = 'USDHUF', $244 = 'USDMXN', $245 = 'USDNOK', $246 = 'USDPLN', $247 = 'USDSEK', $248 = 'USDSGD', $249 = 'USDTRY', $250 = 'USDX', $251 = 'USDZAR', $252 = 'XAGUSD', $253 = 'XAUUSD', $254 = 'BRENT', $255 = 'WTI', $256 = 'AUS200', $257 = 'CHI50', $258 = 'ESP35', $259 = 'EU50', $260 = 'FRA40', $261 = 'GER30', $262 = 'HK50', $263 = 'HKCH50', $264 = 'IT40', $265 = 'JP225', $266 = 'NAS100', $267 = 'SPX500', $268 = 'UK100', $269 = 'US30', $270 = 'AUDUSD', $271 = 'EURUSD', $272 = 'GBPUSD', $273 = 'NZDUSD', $274 = 'USDCAD', $275 = 'USDCHF', $276 = 'USDJPY', $277 = '#AAPL', $278 = '#AIG', $279 = '#AMZN', $280 = '#AXP', $281 = '#BA', $282 = '#BABA', $283 = '#BAC', $284 = '#BIDU', $285 = '#C', $286 = '#CAT', $287 = '#CL', $288 = '#CSCO', $289 = '#CVX', $290 = '#DIS', $291 = '#EBAY', $292 = '#F', $293 = '#FB', $294 = '#FDX', $295 = '#GE', $296 = '#GM', $297 = '#GOOG', $298 = '#GS', $299 = '#HPQ', $300 = '#IBM', $301 = '#INTC', $302 = '#JD', $303 = '#JNJ', $304 = '#JPM', $305 = '#KO', $306 = '#LMT', $307 = '#MA', $308 = '#MCD', $309 = '#MMM', $310 = '#MSFT', $311 = '#NFLX', $312 = '#NKE', $313 = '#NTES', $314 = '#ORCL', $315 = '#PFE', $316 = '#PG', $317 = '#QCOM', $318 = '#RACE', $319 = '#T', $320 = '#UBER', $321 = '#V', $322 = '#WB', $323 = '#XOM', $324 = '0', $325 = '', $326 = '0', $327 = '0', $328 = '0', $329 = '700', $330 = '700', $331 = 't', $332 = '10', $333 = '10'
-
WITH rar_max as ( ;
Date: 2026-02-05 09:25:43 Duration: 68ms Database: postgres parameters: $1 = 't', $2 = '538', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '125', $14 = 'ANGLO', $15 = 'BARC', $16 = 'BAY', $17 = 'BPLON', $18 = 'HSBCL', $19 = 'LLOY', $20 = 'RIO', $21 = 'RollsRoyce', $22 = 'TESCO', $23 = 'VOD', $24 = 'AUDCAD', $25 = 'AUDCHF', $26 = 'AUDJPY', $27 = 'AUDNZD', $28 = 'AUDUSD', $29 = 'CADCHF', $30 = 'CADJPY', $31 = 'CHFJPY', $32 = 'EURAUD', $33 = 'EURCAD', $34 = 'EURCHF', $35 = 'EURDKK', $36 = 'EURGBP', $37 = 'EURHUF', $38 = 'EURJPY', $39 = 'EURNOK', $40 = 'EURNZD', $41 = 'EURPLN', $42 = 'EURUSD', $43 = 'GBPAUD', $44 = 'GBPCAD', $45 = 'GBPCHF', $46 = 'GBPJPY', $47 = 'GBPNZD', $48 = 'GBPUSD', $49 = 'GBPZAR', $50 = 'NZDCAD', $51 = 'NZDCHF', $52 = 'NZDJPY', $53 = 'NZDUSD', $54 = 'USDCAD', $55 = 'USDCHF', $56 = 'USDCNH', $57 = 'USDCZK', $58 = 'USDDKK', $59 = 'USDHKD', $60 = 'USDHUF', $61 = 'USDJPY', $62 = 'USDMXN', $63 = 'USDNOK', $64 = 'USDPLN', $65 = 'USDSEK', $66 = 'USDSGD', $67 = 'USDTRY', $68 = 'USDZAR', $69 = 'XAGEUR', $70 = 'XAGUSD', $71 = 'XAUEUR', $72 = 'XAUUSD', $73 = 'ZARJPY', $74 = 'Cocoa', $75 = 'Coffee', $76 = 'Copper', $77 = 'Palladium', $78 = 'Platinum', $79 = 'Sugar', $80 = 'UKOIL', $81 = 'USOIL', $82 = 'AUS200', $83 = 'FRA40', $84 = 'JPN225', $85 = 'NETH25', $86 = 'SPA35', $87 = 'SUI20', $88 = 'UK100', $89 = 'USA100', $90 = 'USA30', $91 = 'USDIndex', $92 = 'ALCOA', $93 = 'ALIBABA', $94 = 'AMAZON', $95 = 'AMEX', $96 = 'APPLE', $97 = 'BBVA', $98 = 'BOA', $99 = 'BOEING', $100 = 'CHEVRON', $101 = 'CISCO', $102 = 'COKE', $103 = 'EBAY', $104 = 'GE', $105 = 'GOOGLE', $106 = 'GS', $107 = 'HLT', $108 = 'IBM', $109 = 'ILMN', $110 = 'INTEL', $111 = 'Iberdrola', $112 = 'MCARD', $113 = 'MCDON', $114 = 'META', $115 = 'MSFT', $116 = 'Mapfre', $117 = 'Netflix', $118 = 'PFIZER', $119 = 'QCOM', $120 = 'Santander', $121 = 'TEVA', $122 = 'Telefonica', $123 = 'Tesla', $124 = 'AUDUSD', $125 = 'EURGBP', $126 = 'EURUSD', $127 = 'GBPUSD', $128 = 'NZDUSD', $129 = 'USDCAD', $130 = 'USDCHF', $131 = 'USDJPY', $132 = 'Adidas', $133 = 'Bayer', $134 = 'Daimler', $135 = 'Danone', $136 = 'LVMH', $137 = 'Lufthansa', $138 = 'Volksw', $139 = '0', $140 = '', $141 = '0', $142 = '0', $143 = '0', $144 = '700', $145 = '700', $146 = 't', $147 = '10', $148 = '10'
-
WITH rar_max as ( ;
Date: 2026-02-05 09:20:50 Duration: 64ms Database: postgres parameters: $1 = 't', $2 = '667', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '84', $14 = 'AUDCAD', $15 = 'AUDCHF', $16 = 'AUDJPY', $17 = 'AUDNZD', $18 = 'AUDSGD', $19 = 'CADCHF', $20 = 'CADJPY', $21 = 'CHFJPY', $22 = 'EURAUD', $23 = 'EURCAD', $24 = 'EURCHF', $25 = 'EURCZK', $26 = 'EURGBP', $27 = 'EURHUF', $28 = 'EURJPY', $29 = 'EURNOK', $30 = 'EURNZD', $31 = 'EURPLN', $32 = 'EURSEK', $33 = 'EURSGD', $34 = 'EURTRY', $35 = 'EURZAR', $36 = 'GBPAUD', $37 = 'GBPCAD', $38 = 'GBPCHF', $39 = 'GBPJPY', $40 = 'GBPNZD', $41 = 'GBPPLN', $42 = 'GBPSEK', $43 = 'GBPSGD', $44 = 'NZDCAD', $45 = 'NZDCHF', $46 = 'NZDJPY', $47 = 'NZDSGD', $48 = 'USDCNH', $49 = 'USDCZK', $50 = 'USDHUF', $51 = 'USDNOK', $52 = 'USDPLN', $53 = 'USDSEK', $54 = 'USDSGD', $55 = 'USDTRY', $56 = 'USDZAR', $57 = 'WTI', $58 = 'XBRUSD', $59 = 'XTIUSD', $60 = 'BTCUSD', $61 = 'XAGAUD', $62 = 'XAGUSD', $63 = 'XAUAUD', $64 = 'XAUUSD', $65 = 'XPTUSD', $66 = 'XPDUSD', $67 = 'AUDUSD', $68 = 'EURUSD', $69 = 'GBPUSD', $70 = 'NZDUSD', $71 = 'USDCAD', $72 = 'USDCHF', $73 = 'USDHKD', $74 = 'USDJPY', $75 = 'AUS200', $76 = 'CHINA300', $77 = 'CHINA50', $78 = 'DJ30', $79 = 'ESP35t', $80 = 'EUR50', $81 = 'EURO50', $82 = 'FRA40', $83 = 'GDAXI', $84 = 'GDAXIm', $85 = 'HK50', $86 = 'ITA40', $87 = 'J225', $88 = 'JP225', $89 = 'NAS100', $90 = 'SING30', $91 = 'SPA35', $92 = 'STOXX50', $93 = 'SUI20', $94 = 'UK100', $95 = 'US100', $96 = 'US30', $97 = 'US500', $98 = '0', $99 = '', $100 = '0', $101 = '0', $102 = '0', $103 = '700', $104 = '700', $105 = 't', $106 = '10', $107 = '10'
2 17s739ms 39,732 0ms 28ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 09 39,732 17s739ms 0ms -
SELECT ;
Date: 2026-02-05 09:46:18 Duration: 28ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840243153282300'
-
SELECT ;
Date: 2026-02-05 09:30:40 Duration: 28ms Database: postgres parameters: $1 = '500991628207219200'
-
SELECT ;
Date: 2026-02-05 09:21:24 Duration: 20ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840232437573300'
3 3s226ms 1,217 1ms 24ms 2ms SELECT symbolid, ;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 09 1,217 3s226ms 2ms -
SELECT symbolid, ;
Date: 2026-02-05 09:31:23 Duration: 24ms Database: postgres parameters: $1 = 'PEPPERSTONEMT5', $2 = '15', $3 = 'MRNA.US', $4 = 'MA.US', $5 = 'PFE.US', $6 = 'NVDA.US', $7 = 'INTC.US', $8 = 'MCD.US', $9 = 'LMT.US', $10 = 'ORCL.US', $11 = 'PTON.US', $12 = 'JPM.US', $13 = 'NFLX.US', $14 = 'PLTR.US', $15 = 'META.US', $16 = 'MSFT.US', $17 = 'PYPL.US', $18 = 'PG.US', $19 = 'NKE.US'
-
SELECT symbolid, ;
Date: 2026-02-05 09:46:17 Duration: 16ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'BTCUSO'
-
SELECT symbolid, ;
Date: 2026-02-05 09:01:08 Duration: 12ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'BCHJPY', $4 = 'BCHUSD'
4 1s474ms 198 0ms 39ms 7ms select distinct s.statsid as statsid, sy.exchange as name;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 09 198 1s474ms 7ms -
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-02-05 09:10:53 Duration: 39ms Database: postgres parameters: $1 = '558', $2 = '558'
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-02-05 09:10:53 Duration: 34ms Database: postgres parameters: $1 = '549', $2 = '549'
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-02-05 09:10:53 Duration: 33ms Database: postgres parameters: $1 = '538', $2 = '538'
5 1s263ms 53,041 0ms 15ms 0ms select 1;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 09 53,039 1s263ms 0ms 10 2 0ms 0ms -
select 1;
Date: 2026-02-05 09:20:38 Duration: 15ms Database: postgres
-
select 1;
Date: 2026-02-05 09:05:56 Duration: 14ms Database: postgres
-
select 1;
Date: 2026-02-05 09:05:53 Duration: 13ms Database: postgres
6 1s43ms 130 4ms 37ms 8ms WITH last_candle AS ( ;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 09 130 1s43ms 8ms -
WITH last_candle AS ( ;
Date: 2026-02-05 09:16:01 Duration: 37ms Database: postgres parameters: $1 = '538', $2 = '538'
-
WITH last_candle AS ( ;
Date: 2026-02-05 09:00:59 Duration: 31ms Database: postgres parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2026-02-05 09:01:09 Duration: 28ms Database: postgres parameters: $1 = '958', $2 = '958'
7 888ms 495 1ms 3ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 09 495 888ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-05 09:30:43 Duration: 3ms Database: postgres parameters: $1 = 'BDSWISS'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-05 09:30:39 Duration: 2ms Database: postgres parameters: $1 = 'ATFX'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-02-05 09:16:03 Duration: 2ms Database: postgres parameters: $1 = 'HOTFOREX'
8 859ms 27 0ms 103ms 31ms with wh_patitioned as ( ;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 09 27 859ms 31ms -
with wh_patitioned as ( ;
Date: 2026-02-05 09:00:58 Duration: 103ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
-
with wh_patitioned as ( ;
Date: 2026-02-05 09:00:56 Duration: 54ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
-
with wh_patitioned as ( ;
Date: 2026-02-05 09:46:57 Duration: 45ms Database: postgres parameters: $1 = '621', $2 = '621', $3 = '621', $4 = '621', $5 = '621', $6 = '621', $7 = '621', $8 = '621', $9 = '621'
9 851ms 9,063 0ms 9ms 0ms select category, ;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 09 9,063 851ms 0ms -
select category, ;
Date: 2026-02-05 09:10:53 Duration: 9ms Database: postgres parameters: $1 = '515852059305993307', $2 = 'direction', $3 = '515852059305993307', $4 = 'direction'
-
select category, ;
Date: 2026-02-05 09:01:18 Duration: 4ms Database: postgres parameters: $1 = '605633814905634307', $2 = 'symbol', $3 = 'JPN225', $4 = 'US500', $5 = 'UK100', $6 = 'US30', $7 = 'AUS200', $8 = 'EUSTX50', $9 = 'NAS100', $10 = 'GER40', $11 = 'FRA40', $12 = 'HK50', $13 = 'US30', $14 = 'US500', $15 = 'JPN225', $16 = 'EUSTX50', $17 = 'NAS100', $18 = 'AUS200', $19 = 'UK100', $20 = 'HK50', $21 = 'GER40', $22 = 'FRA40', $23 = '605633814905634307', $24 = 'symbol', $25 = 'JPN225', $26 = 'US500', $27 = 'UK100', $28 = 'US30', $29 = 'AUS200', $30 = 'EUSTX50', $31 = 'NAS100', $32 = 'GER40', $33 = 'FRA40', $34 = 'HK50', $35 = 'US30', $36 = 'US500', $37 = 'JPN225', $38 = 'EUSTX50', $39 = 'NAS100', $40 = 'AUS200', $41 = 'UK100', $42 = 'HK50', $43 = 'GER40', $44 = 'FRA40'
-
select category, ;
Date: 2026-02-05 09:00:50 Duration: 4ms Database: postgres parameters: $1 = '601729875359289307', $2 = 'symbol', $3 = 'USOIL', $4 = 'Copper', $5 = 'UKOIL', $6 = 'Platinum', $7 = 'Palladium', $8 = 'Palladium', $9 = 'USOIL', $10 = 'Copper', $11 = 'Platinum', $12 = 'UKOIL', $13 = 'Sugar', $14 = 'Coffee', $15 = 'Cocoa', $16 = 'Sugar', $17 = 'Cocoa', $18 = 'Coffee', $19 = '601729875359289307', $20 = 'symbol', $21 = 'USOIL', $22 = 'Copper', $23 = 'UKOIL', $24 = 'Platinum', $25 = 'Palladium', $26 = 'Palladium', $27 = 'USOIL', $28 = 'Copper', $29 = 'Platinum', $30 = 'UKOIL', $31 = 'Sugar', $32 = 'Coffee', $33 = 'Cocoa', $34 = 'Sugar', $35 = 'Cocoa', $36 = 'Coffee'
10 541ms 44 0ms 20ms 12ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 09 44 541ms 12ms -
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-02-05 09:31:52 Duration: 20ms Database: postgres parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-02-05 09:36:45 Duration: 19ms Database: postgres parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-02-05 09:52:40 Duration: 19ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
11 524ms 12 28ms 51ms 43ms with sym_info as ( ;Times Reported Time consuming bind #11
Day Hour Count Duration Avg duration 09 12 524ms 43ms -
with sym_info as ( ;
Date: 2026-02-05 09:21:45 Duration: 51ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
-
with sym_info as ( ;
Date: 2026-02-05 09:36:51 Duration: 44ms Database: postgres parameters: $1 = '627', $2 = 'Forex', $3 = 'Forex', $4 = '627', $5 = 'Forex', $6 = '627', $7 = '627', $8 = 'Forex', $9 = '627'
-
with sym_info as ( ;
Date: 2026-02-05 09:36:55 Duration: 44ms Database: postgres parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'
12 404ms 477 0ms 3ms 0ms SELECT absolutetimezoneoffset;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 09 477 404ms 0ms -
SELECT absolutetimezoneoffset;
Date: 2026-02-05 09:00:51 Duration: 3ms Database: postgres parameters: $1 = '689', $2 = 'BROKER'
-
SELECT absolutetimezoneoffset;
Date: 2026-02-05 09:00:49 Duration: 2ms Database: postgres parameters: $1 = '632', $2 = 'Commodities'
-
SELECT absolutetimezoneoffset;
Date: 2026-02-05 09:10:53 Duration: 2ms Database: postgres parameters: $1 = '538', $2 = 'Forex Majors'
13 310ms 6,040 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 bind #13
Day Hour Count Duration Avg duration 09 6,040 310ms 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: 2026-02-05 09:16:56 Duration: 0ms Database: postgres parameters: $1 = '2026-02-05 00:30:00', $2 = '87.925', $3 = '88.248', $4 = '87.475', $5 = '88.01', $6 = '1466', $7 = '515840249468430300', $8 = '0', $9 = '2026-02-05 09:16:56.133', $10 = '2026-02-05 09:16:55.976', $11 = '87.925', $12 = '88.248', $13 = '87.475', $14 = '88.01', $15 = '1466', $16 = '0', $17 = '2026-02-05 09:16:56.133', $18 = '2026-02-05 09:16:55.976'
-
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: 2026-02-05 09:47:52 Duration: 0ms Database: postgres parameters: $1 = '2026-02-05 00:30:00', $2 = '16.073335', $3 = '16.07407', $4 = '16.06797', $5 = '16.06955', $6 = '187', $7 = '515840249465587300', $8 = '0', $9 = '2026-02-05 09:47:52.466', $10 = '2026-02-05 09:47:52.413', $11 = '16.073335', $12 = '16.07407', $13 = '16.06797', $14 = '16.06955', $15 = '187', $16 = '0', $17 = '2026-02-05 09:47:52.466', $18 = '2026-02-05 09:47:52.413'
-
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: 2026-02-05 09:32:16 Duration: 0ms Database: postgres parameters: $1 = '2026-02-04 21:00:00', $2 = '46587.49', $3 = '46645.01', $4 = '46554.99', $5 = '46620.01', $6 = '1459', $7 = '500991628285199200', $8 = '0', $9 = '2026-02-05 09:32:16.558', $10 = '2026-02-05 09:32:16.474', $11 = '46587.49', $12 = '46645.01', $13 = '46554.99', $14 = '46620.01', $15 = '1459', $16 = '0', $17 = '2026-02-05 09:32:16.558', $18 = '2026-02-05 09:32:16.474'
14 288ms 3,333 0ms 9ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 09 3,333 288ms 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: 2026-02-05 09:46:30 Duration: 9ms Database: postgres parameters: $1 = '2026-02-04 10:00:00', $2 = '26863.5', $3 = '26886.5', $4 = '26839.5', $5 = '26851.5', $6 = '1046', $7 = '515840230551331300', $8 = '0', $9 = '2026-02-05 09:46:30.018', $10 = '2026-02-05 09:46:30.017', $11 = '26863.5', $12 = '26886.5', $13 = '26839.5', $14 = '26851.5', $15 = '1046', $16 = '0', $17 = '2026-02-05 09:46:30.018', $18 = '2026-02-05 09:46:30.017'
-
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: 2026-02-05 09:15:47 Duration: 0ms Database: postgres parameters: $1 = '2026-02-05 09:30:00', $2 = '0.77835', $3 = '0.778545', $4 = '0.778195', $5 = '0.77828', $6 = '1459', $7 = '515840249378121300', $8 = '0', $9 = '2026-02-05 09:15:47.494', $10 = '2026-02-05 09:15:47.477', $11 = '0.77835', $12 = '0.778545', $13 = '0.778195', $14 = '0.77828', $15 = '1459', $16 = '0', $17 = '2026-02-05 09:15:47.494', $18 = '2026-02-05 09:15:47.477'
-
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: 2026-02-05 09:47:10 Duration: 0ms Database: postgres parameters: $1 = '2026-02-04 23:30:00', $2 = '265.1835', $3 = '266.3305', $4 = '264.0715', $5 = '266.0205', $6 = '5725', $7 = '515840249403885300', $8 = '0', $9 = '2026-02-05 09:47:10.796', $10 = '2026-02-05 09:47:10.374', $11 = '265.1835', $12 = '266.3305', $13 = '264.0715', $14 = '266.0205', $15 = '5725', $16 = '0', $17 = '2026-02-05 09:47:10.796', $18 = '2026-02-05 09:47:10.374'
15 195ms 2,209 0ms 1ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 09 2,209 195ms 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: 2026-02-05 09:00:49 Duration: 1ms Database: postgres parameters: $1 = '2026-02-05 08:00:00', $2 = '1.17894', $3 = '1.17909', $4 = '1.17839', $5 = '1.17898', $6 = '2236', $7 = '515840248029668300', $8 = '0', $9 = '2026-02-05 09:00:49.798', $10 = '2026-02-05 09:00:49.665', $11 = '1.17894', $12 = '1.17909', $13 = '1.17839', $14 = '1.17898', $15 = '2236', $16 = '0', $17 = '2026-02-05 09:00:49.798', $18 = '2026-02-05 09:00:49.665'
-
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: 2026-02-05 09:01:42 Duration: 0ms Database: postgres parameters: $1 = '2026-02-05 09:00:00', $2 = '6.53e-06', $3 = '6.54e-06', $4 = '6.43e-06', $5 = '6.44e-06', $6 = '638', $7 = '515840249472436300', $8 = '0', $9 = '2026-02-05 09:01:42.817', $10 = '2026-02-05 09:01:42.816', $11 = '6.53e-06', $12 = '6.54e-06', $13 = '6.43e-06', $14 = '6.44e-06', $15 = '638', $16 = '0', $17 = '2026-02-05 09:01:42.817', $18 = '2026-02-05 09:01:42.816'
-
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: 2026-02-05 09:01:32 Duration: 0ms Database: postgres parameters: $1 = '2026-02-05 08:00:00', $2 = '156.9815', $3 = '157.065', $4 = '156.8545', $5 = '157.003', $6 = '5086', $7 = '515840230604162300', $8 = '0', $9 = '2026-02-05 09:01:32.611', $10 = '2026-02-05 09:01:32.61', $11 = '156.9815', $12 = '157.065', $13 = '156.8545', $14 = '157.003', $15 = '5086', $16 = '0', $17 = '2026-02-05 09:01:32.611', $18 = '2026-02-05 09:01:32.61'
16 139ms 25 3ms 9ms 5ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 09 25 139ms 5ms -
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-02-05 09:10:52 Duration: 9ms Database: postgres parameters: $1 = '627', $2 = '627'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-02-05 09:10:43 Duration: 9ms Database: postgres parameters: $1 = '627', $2 = '627'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-02-05 09:10:43 Duration: 9ms Database: postgres parameters: $1 = '958', $2 = '958'
17 107ms 228 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 bind #17
Day Hour Count Duration Avg duration 09 228 107ms 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: 2026-02-05 09:13:52 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: 2026-02-05 09:13:51 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: 2026-02-05 09:13:53 Duration: 0ms Database: postgres
18 96ms 95 0ms 1ms 1ms SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 09 95 96ms 1ms -
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2026-02-05 09:35:53 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'XAGUSD', $3 = '558'
-
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2026-02-05 09:05:36 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'USDPLN.a', $3 = '558'
-
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2026-02-05 09:20:36 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'USDPLN.a', $3 = '558'
19 93ms 41 1ms 6ms 2ms WITH rcr_max as ( ;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 09 41 93ms 2ms -
WITH rcr_max as ( ;
Date: 2026-02-05 09:31:45 Duration: 6ms Database: postgres parameters: $1 = '607623401340911305', $2 = '607623401340911305', $3 = '607623401340911305'
-
WITH rcr_max as ( ;
Date: 2026-02-05 09:16:49 Duration: 5ms Database: postgres parameters: $1 = '607623456983063305', $2 = '607623456983063305', $3 = '607623456983063305'
-
WITH rcr_max as ( ;
Date: 2026-02-05 09:31:43 Duration: 5ms Database: postgres parameters: $1 = '607623456983063305', $2 = '607623456983063305', $3 = '607623456983063305'
20 65ms 339 0ms 4ms 0ms /*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 09 339 65ms 0ms -
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2026-02-05 09:05:36 Duration: 4ms Database: postgres parameters: $1 = '607625049225067301'
-
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2026-02-05 09:35:46 Duration: 4ms Database: postgres parameters: $1 = '607625051809593301'
-
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2026-02-05 09:51:08 Duration: 4ms Database: postgres parameters: $1 = '607622454873204301'
-
Events
Log levels
Key values
- 689,645 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 0 ERROR entries
- 0 WARNING entries
Errors per 5 minutes
NO DATASET
Most Frequent Errors/Events
Key values
- 0 Max number of times the same event was reported
- 0 Total events found
Rank Times reported Error NO DATASET