-
Global information
- Generated on Wed Mar 11 04:59:40 2026
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-03-11_060000.log
- Parsed 1,290,600 log entries in 38s
- Log start from 2026-03-11 06:00:00 to 2026-03-11 06:59:38
-
Overview
Global Stats
- 1,038 Number of unique normalized queries
- 170,810 Number of queries
- 3h13m20s Total query duration
- 2026-03-11 06:00:00 First query
- 2026-03-11 06:59:38 Last query
- 6,080 queries/s at 2026-03-11 06:05:02 Query peak
- 3h13m20s Total query duration
- 2m20s Prepare/parse total duration
- 45s293ms Bind total duration
- 3h10m14s Execute total duration
- 357 Number of events
- 3 Number of unique normalized events
- 292 Max number of times the same event was reported
- 0 Number of cancellation
- 50 Total number of automatic vacuums
- 50 Total number of automatic analyzes
- 1,820 Number temporary file
- 617.18 MiB Max size of temporary file
- 81.01 MiB Average size of temporary file
- 2,775 Total number of sessions
- 13 sessions at 2026-03-11 06:53:48 Session peak
- 4d14h24m20s Total duration of sessions
- 2m23s Average duration of sessions
- 61 Average queries per session
- 4s180ms Average queries duration per session
- 2m19s Average idle time per session
- 2,776 Total number of connections
- 27 connections/s at 2026-03-11 06:33:48 Connection peak
- 6 Total number of databases
SQL Traffic
Key values
- 6,080 queries/s Query Peak
- 2026-03-11 06:05:02 Date
SELECT Traffic
Key values
- 3,039 queries/s Query Peak
- 2026-03-11 06:05:02 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 142 queries/s Query Peak
- 2026-03-11 06:00:54 Date
Queries duration
Key values
- 3h13m20s 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) Mar 11 06 170,810 0ms 14m36s 66ms 4m54s 6m32s 25m44s Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Mar 11 06 50,562 602 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Mar 11 06 23,899 1,472 13 78 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Mar 11 06 18,266 50,337 2.76 22.64% Day Hour Count Average / Second Mar 11 06 2,776 0.77/s Day Hour Count Average Duration Average idle time Mar 11 06 2,775 2m23s 2m19s -
Connections
Established Connections
Key values
- 27 connections Connection Peak
- 2026-03-11 06:33:48 Date
Connections per database
Key values
- acaweb_fx Main Database
- 2,776 connections Total
Connections per user
Key values
- postgres Main User
- 2,776 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 1227 connections
- 2,776 Total connections
Host Count 127.0.0.1 115 192.168.0.216 102 192.168.0.74 253 192.168.1.145 27 192.168.1.15 161 192.168.1.20 51 192.168.1.231 20 192.168.1.239 12 192.168.1.90 48 192.168.2.126 38 192.168.2.182 12 192.168.3.199 36 192.168.4.142 1,227 192.168.4.150 10 192.168.4.238 48 192.168.4.33 70 192.168.4.86 1 192.168.4.90 7 192.168.4.98 330 [local] 208 -
Sessions
Simultaneous sessions
Key values
- 13 sessions Session Peak
- 2026-03-11 06:53:48 Date
Histogram of session times
Key values
- 2,245 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 2,775 sessions Total
Sessions per user
Key values
- postgres Main User
- 2,775 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 2,775 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 115 37m55s 19s788ms 192.168.0.216 102 1m4s 629ms 192.168.0.74 254 2d4h29m56s 12m24s 192.168.1.145 26 4h25m44s 10m13s 192.168.1.15 161 7h7m2s 2m39s 192.168.1.20 50 14h47m37s 17m45s 192.168.1.231 20 9h52m25s 29m37s 192.168.1.239 12 137ms 11ms 192.168.1.90 48 3m12s 4s20ms 192.168.2.126 38 6s736ms 177ms 192.168.2.182 12 1s628ms 135ms 192.168.3.199 36 1s618ms 44ms 192.168.4.142 1,227 7m28s 365ms 192.168.4.150 10 20h18m18s 2h1m49s 192.168.4.238 48 7m48s 9s750ms 192.168.4.33 70 1m13s 1s52ms 192.168.4.86 1 219ms 219ms 192.168.4.90 7 1m4s 9s232ms 192.168.4.98 330 22s575ms 68ms [local] 208 22m55s 6s613ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 9,795 buffers Checkpoint Peak
- 2026-03-11 06:06:23 Date
- 209.721 seconds Highest write time
- 0.698 seconds Sync time
Checkpoints Wal files
Key values
- 4 files Wal files usage Peak
- 2026-03-11 06:36:24 Date
Checkpoints distance
Key values
- 157.78 Mo Distance Peak
- 2026-03-11 06:06:23 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Mar 11 06 29,554 1,708.97s 2.137s 1,716.634s Day Hour Added Removed Recycled Synced files Longest sync Average sync Mar 11 06 0 0 18 1,909 0.693s 0.018s Day Hour Count Avg time (sec) Mar 11 06 0 0s Day Hour Mean distance Mean estimate Mar 11 06 25,826.33 kB 57,394.75 kB -
Temporary Files
Size of temporary files
Key values
- 759.83 MiB Temp Files size Peak
- 2026-03-11 06:30:12 Date
Number of temporary files
Key values
- 30 per second Temp Files Peak
- 2026-03-11 06:02:10 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Mar 11 06 1,820 143.98 GiB 81.01 MiB Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 236 138.40 GiB 368.71 MiB 617.18 MiB 600.53 MiB from pg_stat_activity where (state = ?) and query_start < current_timestamp - interval ? and query not like ?;-
from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';
Date: 2026-03-11 06:00:13 Duration: 0ms
2 166 280.88 MiB 137.65 KiB 3.76 MiB 1.69 MiB with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ), ar as ( select a.*, rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end ), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, 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, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.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 sg.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 currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= 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 ;-
WITH rar_max as ( SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1 ), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END ), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, 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, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.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 sg.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 OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4, $5, $6, $7, $8, $9, $10)) AND ($11 = 0 OR s.exchange in ($12)) AND ($13 = 0 OR coalesce(bim.code, s.symbol) in ($14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226)) AND ($227 = 0 OR ar.pattern in ($228)) AND ($229 = 0 OR ($230 = 1 AND ar.breakout >= 0) OR ($231 = 2 AND ar.breakout < 0)) AND ($232 = 0 OR ar.patternlengthbars <= $233) and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $234 OR relevant = 1) AND ($235 = 0 OR age <= $236) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2026-03-11 06:00:21 Duration: 0ms
3 71 128.00 MiB 137.65 KiB 4.68 MiB 1.80 MiB 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 ? ;-
WITH rar_max as ( SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ), 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 = $1 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 11 ELSE 0 END as age, CASE WHEN kr.relevant IS NOT NULL THEN kr.relevant WHEN kr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM kr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = kr.symbolid INNER JOIN symbols s ON bsl.symbolid = s.symbolid AND s.nonliquid = 0 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 = 3 INNER JOIN rar_max rm ON 1 = 1 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 = 'OUTBOUND' WHERE kr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (kr.simulation = 0 OR kr.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 p.patternname in ($10)) AND ($11 = 0 OR kr.patternclassid in ($12)) AND ($13 = 0 OR kr.patternlengthbars <= $14) AND kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $15 OR relevant = 1) AND ($16 = 0 OR age <= $17) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC LIMIT 200;
Date: 2026-03-11 06:00:02 Duration: 0ms
4 45 227.88 MiB 4.91 MiB 5.38 MiB 5.06 MiB select resultuid from relevance_fibonacci_results order by resultuid desc limit ?), fr as ( select a.*, rr.age, rr.relevant from fibonacci_results a left outer join relevance_fibonacci_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) end), all_results as ( select fr.resultuid as resultuid, fr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, fr.pattern as pattern_name, fr.timed as timed, fr.patternendtime as identified, dtt.timezone as timezone, fr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when fr.age is not null then fr.age when fr.resultuid <= rm.resultuid then ? else ? end as age, case when fr.relevant is not null then fr.relevant when fr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from fr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = fr.symbolid inner join symbols s on fr.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on fr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on fr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left join lateral calc_fib_signal_filter (fr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where fr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (fr.simulation = ? or fr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or fr.pattern in (...)) and (? = ? or fr.patternlengthbars <= ?) and (? = ? or (? = ? and fr.timed > cast(? as timestamp)) or (? = ? and fr.timed < cast(? as timestamp)))), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;-
SELECT resultuid FROM relevance_fibonacci_results ORDER BY resultuid DESC LIMIT 1), fr AS ( SELECT a.*, rr.age, rr.relevant from fibonacci_results a LEFT OUTER JOIN relevance_fibonacci_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_fibonacci_results) END), all_results AS ( SELECT fr.resultuid AS resultuid, fr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, fr.pattern AS pattern_name, fr.timed AS timed, fr.patternendtime AS identified, dtt.timezone AS timezone, fr.patternlengthbars AS length, g.basegroupname, newLevels.filtered, CASE WHEN fr.age IS NOT NULL THEN fr.age WHEN fr.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN fr.relevant IS NOT NULL THEN fr.relevant WHEN fr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip FROM fr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = fr.symbolid INNER JOIN symbols s ON fr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN symbolgroup sg on fr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON fr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT JOIN LATERAL calc_fib_signal_filter (fr.resultuid) newLevels on true LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE fr.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (fr.simulation = 0 OR fr.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4, $5, $6, $7, $8, $9, $10)) AND ($11 = 0 OR s.exchange in ($12)) AND ($13 = 0 OR coalesce(bim.code, s.symbol) in ($14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226)) AND ($227 = 0 OR fr.pattern in ($228)) AND ($229 = 0 OR fr.patternlengthbars <= $230) AND ($231 = 0 OR ($232 = 1 AND fr.timed > cast('1970-01-01' as timestamp)) OR ($233 = 2 AND fr.timed < cast('1970-01-01' as timestamp)))), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $234 OR relevant = 1) AND ($235 = 0 OR age <= $236) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2026-03-11 06:00:29 Duration: 0ms
5 29 1.66 GiB 2.64 MiB 195.67 MiB 58.62 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: 2026-03-11 06:00:06 Duration: 0ms
6 28 149.90 MiB 3.05 MiB 9.51 MiB 5.35 MiB jr.resultuid as resultuid, jr.direction as direction, jr.patternendtime as identified, jr.patternlengthbars as length, jr.patternstarttime as patternstarttime, case when jr.trendchangeid = ? then ? else ? end as trendchange, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, jp.patternname as pattern_name, dtt.timezone as timezone, ? as age, cps.pip, g.basegroupname from japsticks_results jr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = jr.symbolid inner join relevance_japsticks_results rar on rar.resultuid = jr.resultuid inner join symbols s on jr.symbolid = s.symbolid and s.nonliquid = ? inner join japsticks_patterns jp on jr.patternid = jp.id inner join downloadersymbolsettings dss on jr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where jr.gmttimefound > now() - interval ? and s.deleted = ? and (jr.simulation = ? or jr.simulation is null) and (rar.relevant = ?) --and (semicolon_age = ? or rar.age <= semicolon_age) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or jp.patternname in (...)) and (? = ? or jr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results order by symbolid, resultuid ) select * from results order by identified desc, length desc ;-
jr.resultuid AS resultuid, jr.direction AS direction, jr.patternendtime AS identified, jr.patternlengthbars AS length, jr.patternstarttime AS patternstarttime, case when jr.trendchangeid = 1 then 'Continuation' else 'Reversal' end AS trendchange, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, jp.patternname AS pattern_name, dtt.timezone AS timezone, 0 AS age, cps.pip, g.basegroupname FROM japsticks_results jr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = jr.symbolid INNER JOIN relevance_japsticks_results rar ON rar.resultuid = jr.resultuid INNER JOIN symbols s ON jr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN japsticks_patterns jp ON jr.patternid = jp.id INNER JOIN downloadersymbolsettings dss ON jr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE jr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (jr.simulation = 0 OR jr.simulation IS NULL) AND (rar.relevant = 1) --AND (semicolon_age = 0 OR rar.age <= semicolon_age) AND ($2 = 0 OR s.timegranularity in ($3)) AND ($4 = 0 OR s.exchange in ($5)) AND ($6 = 0 OR coalesce(bim.code, s.symbol) in ($7)) AND ($8 = 0 OR jp.patternname in ($9)) AND ($10 = 0 OR jr.patternlengthbars <= $11)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2026-03-11 06:00:04 Duration: 0ms
7 13 600.64 MiB 46.20 MiB 46.20 MiB 46.20 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: 2026-03-11 06:01:14 Duration: 0ms
8 13 1019.88 MiB 78.45 MiB 78.45 MiB 78.45 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: 2026-03-11 06:01:17 Duration: 0ms
9 8 1.09 GiB 139.84 MiB 139.91 MiB 139.86 MiB select updateresultsmaterializedview ();-
select updateresultsmaterializedview ();
Date: 2026-03-11 06:02:15 Duration: 0ms
10 4 315.74 MiB 78.88 MiB 79.03 MiB 78.94 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2026-03-11 06:02:05 Duration: 0ms
11 3 11.97 MiB 3.98 MiB 4.00 MiB 3.99 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: 2026-03-11 06:04:25 Duration: 0ms
Queries generating the largest temporary files
Rank Size Query 1 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:09:02 ]
2 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:09:17 ]
3 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:09:32 ]
4 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:09:47 ]
5 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:10:01 ]
6 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:10:17 ]
7 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:10:32 ]
8 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:10:46 ]
9 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:11:02 ]
10 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:11:33 ]
11 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:11:47 ]
12 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:12:18 ]
13 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:12:32 ]
14 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:13:05 ]
15 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:13:32 ]
16 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:13:47 ]
17 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:14:02 ]
18 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:14:17 ]
19 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:14:33 ]
20 617.18 MiB from pg_stat_activity where (state = 'active') and query_start < current_timestamp - INTERVAL '10 minute' and query not like 'autovacuum%';[ Date: 2026-03-11 06:14:47 ]
-
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 (12) Main table analyzed (database acaweb_fx)
- 50 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 12 acaweb_fx.pg_catalog.pg_attribute 6 acaweb_fx.pg_catalog.pg_class 5 acaweb_fx.pg_catalog.pg_type 4 acaweb_fx.public.relevance_keylevels_results 4 acaweb_fx.public.relevance_autochartist_results 4 acaweb_fx.public.datafeeds_latestrun 3 acaweb_fx.pg_catalog.pg_index 2 acaweb_fx.pg_catalog.pg_depend 2 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.public.relevance_fibonacci_results 2 acaweb_fx.public.autochartist_symbolupdates 1 acaweb_fx.public.relevance_consecutivecandles_results 1 acaweb_fx.public.symbollatestupdatetime 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 Total 50 Vacuums per table
Key values
- public.solr_relevance_old (21) Main table vacuumed on database acaweb_fx
- 50 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 13 12,930 0 49 0 60 6,542 12 1,157,278 acaweb_fx.pg_catalog.pg_attribute 5 3 3,620 0 417 0 335 1,249 336 1,894,985 acaweb_fx.pg_catalog.pg_type 3 3 529 0 75 0 0 216 52 295,436 acaweb_fx.public.relevance_keylevels_results 3 3 10,334 0 1,087 2 300 2,252 1,262 3,738,758 acaweb_fx.pg_catalog.pg_class 3 3 1,335 0 101 0 0 404 96 520,676 acaweb_fx.public.relevance_autochartist_results 3 3 10,114 0 207 3 750 1,707 929 2,841,788 acaweb_fx.public.relevance_fibonacci_results 3 3 3,366 0 132 0 183 327 183 686,718 acaweb_fx.pg_toast.pg_toast_2619 2 2 275 0 61 0 0 201 59 226,673 acaweb_fx.public.datafeeds_latestrun 2 0 239 0 11 0 0 26 6 29,642 acaweb_fx.pg_catalog.pg_index 1 1 92 0 13 0 0 27 10 75,346 acaweb_fx.public.solr_imports 1 1 55 0 2 0 0 6 1 6,126 acaweb_fx.pg_catalog.pg_statistic 1 1 946 0 220 0 582 501 218 767,414 acaweb_fx.public.symbollatestupdatetime 1 0 1,325 0 457 0 609 1,109 456 1,286,865 acaweb_fx.public.latest_t15_candle_view 1 1 66 0 3 0 0 6 0 885 Total 50 37 45,226 28,248 2,835 5 2,819 14,573 3,620 13,528,590 Tuples removed per table
Key values
- public.solr_relevance_old (56318) Main table with removed tuples on database acaweb_fx
- 90034 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 21 13 56,318 149,461 45,473 0 3,524 acaweb_fx.public.symbollatestupdatetime 1 0 18,464 103,066 318 0 1,714 acaweb_fx.pg_catalog.pg_attribute 5 3 7,432 57,966 6,176 32 1,387 acaweb_fx.public.relevance_keylevels_results 3 3 3,457 36,637 2,292 0 837 acaweb_fx.public.relevance_autochartist_results 3 3 1,979 25,767 1,549 0 1,140 acaweb_fx.pg_catalog.pg_statistic 1 1 718 3,724 0 0 1,194 acaweb_fx.pg_catalog.pg_type 3 3 671 4,717 352 0 135 acaweb_fx.pg_catalog.pg_class 3 3 542 5,151 183 0 450 acaweb_fx.pg_toast.pg_toast_2619 2 2 140 348 18 3 103 acaweb_fx.public.datafeeds_latestrun 2 0 126 28 0 0 32 acaweb_fx.public.relevance_fibonacci_results 3 3 93 4,216 262 0 306 acaweb_fx.public.solr_imports 1 1 50 3 2 0 2 acaweb_fx.public.latest_t15_candle_view 1 1 42 24 12 0 1 acaweb_fx.pg_catalog.pg_index 1 1 2 829 14 0 22 Total 50 37 90,034 391,937 56,651 35 10,847 Pages removed per table
Key values
- pg_catalog.pg_attribute (32) Main table with removed pages on database acaweb_fx
- 35 pages Total removed
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_catalog.pg_attribute 5 3 7432 32 acaweb_fx.pg_toast.pg_toast_2619 2 2 140 3 acaweb_fx.pg_catalog.pg_index 1 1 2 0 acaweb_fx.pg_catalog.pg_type 3 3 671 0 acaweb_fx.public.datafeeds_latestrun 2 0 126 0 acaweb_fx.public.solr_imports 1 1 50 0 acaweb_fx.pg_catalog.pg_statistic 1 1 718 0 acaweb_fx.public.symbollatestupdatetime 1 0 18464 0 acaweb_fx.public.latest_t15_candle_view 1 1 42 0 acaweb_fx.public.relevance_keylevels_results 3 3 3457 0 acaweb_fx.pg_catalog.pg_class 3 3 542 0 acaweb_fx.public.solr_relevance_old 21 13 56318 0 acaweb_fx.public.relevance_autochartist_results 3 3 1979 0 acaweb_fx.public.relevance_fibonacci_results 3 3 93 0 Total 50 37 90,034 35 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Mar 11 06 50 50 - 0 sec Highest CPU-cost vacuum
-
Locks
Locks by types
Key values
- AccessShareLock Main Lock Type
- 5 locks Total
Most frequent waiting queries (N)
Rank Count Total time Min time Max time Avg duration Query 1 1 14m36s 14m36s 14m36s 14m36s truncate table solr_relevance_old;-
TRUNCATE TABLE solr_relevance_old;
Date: 2026-03-11 06:19:47
2 2 5m15s 2m29s 2m45s 2m37s select datetimeupdate from latest_candle_datetime_per_receng where recognitionengine ilike ?;-
SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'PEPPERSTONE - 1';
Date: 2026-03-11 06:19:48
3 1 2m46s 2m46s 2m46s 2m46s refresh materialized view latest_candle_datetime_per_receng;-
refresh materialized view latest_candle_datetime_per_receng;
Date: 2026-03-11 06:19:47
4 1 2m13s 2m13s 2m13s 2m13s select recognitionengine, to_char(datetimeupdate, ?) from latest_candle_datetime_per_receng;-
select recognitionengine, to_char(datetimeupdate, 'yyyy-mm-dd HH24:MI') from latest_candle_datetime_per_receng;
Date: 2026-03-11 06:19:48
Queries that waited the most
Rank Wait time Query 1 14m36s TRUNCATE TABLE solr_relevance_old;[ Date: 2026-03-11 06:19:47 ]
2 2m46s refresh materialized view latest_candle_datetime_per_receng;[ Date: 2026-03-11 06:19:47 ]
3 2m45s SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'IQFEED_FX - 1';[ Date: 2026-03-11 06:19:48 ]
4 2m29s SELECT datetimeupdate FROM latest_candle_datetime_per_receng WHERE recognitionengine ILIKE 'PEPPERSTONE - 1';[ Date: 2026-03-11 06:19:48 ]
5 2m13s select recognitionengine, to_char(datetimeupdate, 'yyyy-mm-dd HH24:MI') from latest_candle_datetime_per_receng;[ Date: 2026-03-11 06:19:48 ]
-
Queries
Queries by type
Key values
- 50,562 Total read queries
- 30,114 Total write queries
Queries by database
Key values
- unknown Main database
- 169,925 Requests
- 3h10m14s (unknown)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 809 0ms copy from 65 0ms copy to 26 0ms cte 85 0ms ddl 13 0ms delete 13 0ms others 166 0ms select 73 0ms tcl 330 0ms update 38 0ms acaweb_fx_integer Total 1 0ms select 1 0ms postgres Total 3 0ms select 3 0ms socialmedia Total 71 0ms select 71 0ms translations Total 1 0ms select 1 0ms unknown Total 169,925 3h10m14s copy from 13 0ms copy to 576 0ms cte 3,287 0ms insert 23,899 0ms others 4,710 0ms select 50,413 0ms tcl 335 0ms update 1,434 0ms Queries by user
Key values
- unknown Main user
- 169,925 Requests
User Request type Count Duration postgres Total 885 0ms copy from 65 0ms copy to 26 0ms cte 85 0ms ddl 13 0ms delete 13 0ms others 166 0ms select 149 0ms tcl 330 0ms update 38 0ms unknown Total 169,925 3h10m14s copy from 13 0ms copy to 576 0ms cte 3,287 0ms insert 23,899 0ms others 4,710 0ms select 50,413 0ms tcl 335 0ms update 1,434 0ms Duration by user
Key values
- 3h10m14s (unknown) Main time consuming user
User Request type Count Duration postgres Total 885 0ms copy from 65 0ms copy to 26 0ms cte 85 0ms ddl 13 0ms delete 13 0ms others 166 0ms select 149 0ms tcl 330 0ms update 38 0ms unknown Total 169,925 3h10m14s copy from 13 0ms copy to 576 0ms cte 3,287 0ms insert 23,899 0ms others 4,710 0ms select 50,413 0ms tcl 335 0ms update 1,434 0ms Queries by host
Key values
- unknown Main host
- 170,810 Requests
- 3h10m14s (unknown)
- Main time consuming host
Queries by application
Key values
- unknown Main application
- 170,487 Requests
- 3h10m14s (unknown)
- Main time consuming application
Application Request type Count Duration pg_dump Total 5 0ms select 5 0ms psql Total 318 0ms copy from 65 0ms copy to 26 0ms cte 85 0ms ddl 13 0ms delete 13 0ms others 4 0ms select 74 0ms update 38 0ms unknown Total 170,487 3h10m14s copy from 13 0ms copy to 576 0ms cte 3,287 0ms insert 23,899 0ms others 4,872 0ms select 50,483 0ms tcl 665 0ms update 1,434 0ms Number of cancelled queries
Key values
- 1 per second Cancelled query Peak
- 2026-03-11 06:16:18 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 53,336 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 1 0ms 0ms 0ms lock table public.stats_hrs_summary_by_groups in access share mode;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 11 06 1 0ms 0ms 2 0ms 2 0ms 0ms 0ms lock table public.timezones_korean in access share mode;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 3 0ms 12 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 #3
Day Hour Count Duration Avg duration Mar 11 06 12 0ms 0ms 4 0ms 2 0ms 0ms 0ms copy public.t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived, pricesadjusted, relevanceprocessed, recengprocessedadjusted, historical) to stdout;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 5 0ms 1 0ms 0ms 0ms copy public.processresults (id, processid, resultdate, shorttext, longtext, title, test) to stdout;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Mar 11 06 1 0ms 0ms 6 0ms 1,997 0ms 0ms 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Mar 11 06 1,997 0ms 0ms 7 0ms 237 0ms 0ms 0ms select * from ( select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity) as k order by timegranularity;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Mar 11 06 237 0ms 0ms 8 0ms 979 0ms 0ms 0ms select oid, tableoid, pol.polname, pol.polcmd, pol.polpermissive, case when pol.polroles = ? then null else pg_catalog.array_to_string(array ( select pg_catalog.quote_ident(rolname) from pg_catalog.pg_roles where oid = any (pol.polroles)), ?) end as polroles, pg_catalog.pg_get_expr(pol.polqual, pol.polrelid) as polqual, pg_catalog.pg_get_expr(pol.polwithcheck, pol.polrelid) as polwithcheck from pg_catalog.pg_policy pol where polrelid = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Mar 11 06 979 0ms 0ms 9 0ms 2 0ms 0ms 0ms copy public.timezones_greek (timezoneid, timezone) to stdout;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 10 0ms 2 0ms 0ms 0ms lock table public.futures_symbols in access share mode;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 11 0ms 2 0ms 0ms 0ms copy archive.autochartist_results (resultid, bandwidth, pattern, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, qtytp, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, symbolid, resultuid, relevancestartdistance, simulation, writtendatetime, old_resultuid) to stdout;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 12 0ms 2 0ms 0ms 0ms copy public.satelliteauthentication (id, satelliteserverid, brokerid, authenticationstatus, maketradeurl, notifications, validusername, validpassword, enabled) to stdout;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 13 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 #13
Day Hour Count Duration Avg duration Mar 11 06 18 0ms 0ms 14 0ms 5 0ms 0ms 0ms select s.tableoid, s.oid, s.subname, ( select rolname from pg_catalog.pg_roles where oid = s.subowner) as rolname, s.subconninfo, s.subslotname, s.subsynccommit, s.subpublications from pg_subscription s where s.subdbid = ( select oid from pg_database where datname = current_database());Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Mar 11 06 5 0ms 0ms 15 0ms 1 0ms 0ms 0ms select usename, array_to_string(array ( select quote_ident(option_name) || ? || quote_literal(option_value) from pg_options_to_table(umoptions) order by option_name), e ?) as umoptions from pg_user_mappings where srvid = ? order by usename;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Mar 11 06 1 0ms 0ms 16 0ms 2 0ms 0ms 0ms copy archive.sa_hist_consecutivecandles (id, symbolid, datetime, image, qty, percentile, direction, lastupdated, height) to stdout;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 17 0ms 1 0ms 0ms 0ms copy public.commoncontenttypeparams (id, name, required, description, "default", type) to stdout;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Mar 11 06 1 0ms 0ms 18 0ms 244 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 #18
Day Hour Count Duration Avg duration Mar 11 06 244 0ms 0ms 19 0ms 2 0ms 0ms 0ms lock table public.powerstats in access share mode;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 20 0ms 4 0ms 0ms 0ms select oid, enumlabel from pg_catalog.pg_enum where enumtypid = ? order by enumsortorder;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Mar 11 06 4 0ms 0ms Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 13,558 0ms 0ms 0ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 11 06 13,558 0ms 0ms 2 6,773 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 Mar 11 06 6,773 0ms 0ms 3 6,626 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 #3
Day Hour Count Duration Avg duration Mar 11 06 6,626 0ms 0ms 4 5,653 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 #4
Day Hour Count Duration Avg duration Mar 11 06 5,653 0ms 0ms 5 5,219 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 #5
Day Hour Count Duration Avg duration Mar 11 06 5,219 0ms 0ms 6 3,739 0ms 0ms 0ms 0ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Mar 11 06 3,739 0ms 0ms 7 2,994 0ms 0ms 0ms 0ms insert into t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Mar 11 06 2,994 0ms 0ms 8 1,997 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 #8
Day Hour Count Duration Avg duration Mar 11 06 1,997 0ms 0ms 9 1,851 0ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Mar 11 06 1,851 0ms 0ms 10 1,825 0ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 11 06 1,825 0ms 0ms 11 1,696 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 #11
Day Hour Count Duration Avg duration Mar 11 06 1,696 0ms 0ms 12 1,664 0ms 0ms 0ms 0ms select pg_catalog.format_type(?::pg_catalog.oid, null);Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Mar 11 06 1,664 0ms 0ms 13 1,169 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 #13
Day Hour Count Duration Avg duration Mar 11 06 1,169 0ms 0ms 14 1,099 0ms 0ms 0ms 0ms select symbolid, pricedatetime, classname, downloadfrequency, downloadersymbol, open, high, low, close, volume, bsf, sastdatetimereceived from ( select pricedatetime, dss.classname, dss.downloadfrequency, dss.symbolid, dss.downloadersymbol, t.open, t.high, t.low, t.close, t.volume, t.bsf, t.sastdatetimereceived, row_number() over (partition by t.symbolid order by t.pricedatetime desc) as rn from t15 t, downloadersymbolsettings dss, symbols s where dss.classname = ? and dss.downloadfrequency = ? and dss.symbolid = t.symbolid and s.symbolid = dss.symbolid and dss.enabled = ? and s.deleted = ? and dss.downloadersymbol in (...) and t.pricedatetime > now() - interval ?) as ranked_candles_table where rn = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Mar 11 06 1,099 0ms 0ms 15 1,025 0ms 0ms 0ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Mar 11 06 1,025 0ms 0ms 16 979 0ms 0ms 0ms 0ms select oid, tableoid, pol.polname, pol.polcmd, pol.polpermissive, case when pol.polroles = ? then null else pg_catalog.array_to_string(array ( select pg_catalog.quote_ident(rolname) from pg_catalog.pg_roles where oid = any (pol.polroles)), ?) end as polroles, pg_catalog.pg_get_expr(pol.polqual, pol.polrelid) as polqual, pg_catalog.pg_get_expr(pol.polwithcheck, pol.polrelid) as polwithcheck from pg_catalog.pg_policy pol where polrelid = ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 11 06 979 0ms 0ms 17 789 0ms 0ms 0ms 0ms select a.attnum, a.attname, a.atttypmod, a.attstattarget, a.attstorage, t.typstorage, a.attnotnull, a.atthasdef, a.attisdropped, a.attlen, a.attalign, a.attislocal, pg_catalog.format_type(t.oid, a.atttypmod) as atttypname, a.attgenerated, case when a.atthasmissing and not a.attisdropped then a.attmissingval else null end as attmissingval, a.attidentity, pg_catalog.array_to_string(array ( select pg_catalog.quote_ident(option_name) || ? || pg_catalog.quote_literal(option_value) from pg_catalog.pg_options_to_table(attfdwoptions) order by option_name), e ?) as attfdwoptions, case when a.attcollation <> t.typcollation then a.attcollation else ? end as attcollation, array_to_string(a.attoptions, ?) as attoptions from pg_catalog.pg_attribute a left join pg_catalog.pg_type t on a.atttypid = t.oid where a.attrelid = ?::pg_catalog.oid and a.attnum > ?::pg_catalog.int2 order by a.attnum;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Mar 11 06 789 0ms 0ms 18 676 0ms 0ms 0ms 0ms select at.attname, ( select pg_catalog.array_agg(acl order by row_n) from ( select acl, row_n from pg_catalog.unnest(coalesce(at.attacl, pg_catalog.acldefault(?, c.relowner))) with ordinality as perm (acl, row_n) where not exists ( select ? from pg_catalog.unnest(coalesce(pip.initprivs, pg_catalog.acldefault(?, c.relowner))) as init (init_acl) where acl = init_acl)) as foo) as attacl, ( select pg_catalog.array_agg(acl order by row_n) from ( select acl, row_n from pg_catalog.unnest(coalesce(pip.initprivs, pg_catalog.acldefault(?, c.relowner))) with ordinality as initp (acl, row_n) where not exists ( select ? from pg_catalog.unnest(coalesce(at.attacl, pg_catalog.acldefault(?, c.relowner))) as permp (orig_acl) where acl = orig_acl)) as foo) as rattacl, null as initattacl, null as initrattacl from pg_catalog.pg_attribute at join pg_catalog.pg_class c on (at.attrelid = c.oid) left join pg_catalog.pg_init_privs pip on (at.attrelid = pip.objoid and pip.classoid = ?::pg_catalog.regclass and at.attnum = pip.objsubid) where at.attrelid = ?::pg_catalog.oid and not at.attisdropped and (( select pg_catalog.array_agg(acl order by row_n) from ( select acl, row_n from pg_catalog.unnest(coalesce(at.attacl, pg_catalog.acldefault(?, c.relowner))) with ordinality as perm (acl, row_n) where not exists ( select ? from pg_catalog.unnest(coalesce(pip.initprivs, pg_catalog.acldefault(?, c.relowner))) as init (init_acl) where acl = init_acl)) as foo) is not null or ( select pg_catalog.array_agg(acl order by row_n) from ( select acl, row_n from pg_catalog.unnest(coalesce(pip.initprivs, pg_catalog.acldefault(?, c.relowner))) with ordinality as initp (acl, row_n) where not exists ( select ? from pg_catalog.unnest(coalesce(at.attacl, pg_catalog.acldefault(?, c.relowner))) as permp (orig_acl) where acl = orig_acl)) as foo) is not null or null is not null or null is not null) order by at.attnum;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Mar 11 06 676 0ms 0ms 19 653 0ms 0ms 0ms 0ms select proretset, prosrc, probin, pg_catalog.pg_get_function_arguments(oid) as funcargs, pg_catalog.pg_get_function_identity_arguments(oid) as funciargs, pg_catalog.pg_get_function_result(oid) as funcresult, array_to_string(protrftypes, ?) as protrftypes, prokind, provolatile, proisstrict, prosecdef, proleakproof, proconfig, procost, prorows, prosupport, proparallel, ( select lanname from pg_catalog.pg_language where oid = prolang) as lanname from pg_catalog.pg_proc where oid = ?::pg_catalog.oid;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Mar 11 06 653 0ms 0ms 20 632 0ms 0ms 0ms 0ms select downloadersymbol, spike_threshold from price_datafeed_spike_threshold where classname = ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Mar 11 06 632 0ms 0ms Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 0ms 0ms 0ms 1 0ms lock table public.stats_hrs_summary_by_groups in access share mode;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 11 06 1 0ms 0ms 2 0ms 0ms 0ms 2 0ms lock table public.timezones_korean in access share mode;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 3 0ms 0ms 0ms 12 0ms select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Mar 11 06 12 0ms 0ms 4 0ms 0ms 0ms 2 0ms copy public.t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived, pricesadjusted, relevanceprocessed, recengprocessedadjusted, historical) to stdout;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 5 0ms 0ms 0ms 1 0ms copy public.processresults (id, processid, resultdate, shorttext, longtext, title, test) to stdout;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Mar 11 06 1 0ms 0ms 6 0ms 0ms 0ms 1,997 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Mar 11 06 1,997 0ms 0ms 7 0ms 0ms 0ms 237 0ms select * from ( select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity union select timegranularity, extract(day from (max(patternendtime) - min(patternendtime))) from fibonacci_results a inner join symbols s on a.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid where timegranularity = ? and (dss.archive is null or dss.archive is true) group by timegranularity) as k order by timegranularity;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Mar 11 06 237 0ms 0ms 8 0ms 0ms 0ms 979 0ms select oid, tableoid, pol.polname, pol.polcmd, pol.polpermissive, case when pol.polroles = ? then null else pg_catalog.array_to_string(array ( select pg_catalog.quote_ident(rolname) from pg_catalog.pg_roles where oid = any (pol.polroles)), ?) end as polroles, pg_catalog.pg_get_expr(pol.polqual, pol.polrelid) as polqual, pg_catalog.pg_get_expr(pol.polwithcheck, pol.polrelid) as polwithcheck from pg_catalog.pg_policy pol where polrelid = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Mar 11 06 979 0ms 0ms 9 0ms 0ms 0ms 2 0ms copy public.timezones_greek (timezoneid, timezone) to stdout;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 10 0ms 0ms 0ms 2 0ms lock table public.futures_symbols in access share mode;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 11 0ms 0ms 0ms 2 0ms copy archive.autochartist_results (resultid, bandwidth, pattern, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, qtytp, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, symbolid, resultuid, relevancestartdistance, simulation, writtendatetime, old_resultuid) to stdout;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 12 0ms 0ms 0ms 2 0ms copy public.satelliteauthentication (id, satelliteserverid, brokerid, authenticationstatus, maketradeurl, notifications, validusername, validpassword, enabled) to stdout;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 13 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 #13
Day Hour Count Duration Avg duration Mar 11 06 18 0ms 0ms 14 0ms 0ms 0ms 5 0ms select s.tableoid, s.oid, s.subname, ( select rolname from pg_catalog.pg_roles where oid = s.subowner) as rolname, s.subconninfo, s.subslotname, s.subsynccommit, s.subpublications from pg_subscription s where s.subdbid = ( select oid from pg_database where datname = current_database());Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Mar 11 06 5 0ms 0ms 15 0ms 0ms 0ms 1 0ms select usename, array_to_string(array ( select quote_ident(option_name) || ? || quote_literal(option_value) from pg_options_to_table(umoptions) order by option_name), e ?) as umoptions from pg_user_mappings where srvid = ? order by usename;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Mar 11 06 1 0ms 0ms 16 0ms 0ms 0ms 2 0ms copy archive.sa_hist_consecutivecandles (id, symbolid, datetime, image, qty, percentile, direction, lastupdated, height) to stdout;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 17 0ms 0ms 0ms 1 0ms copy public.commoncontenttypeparams (id, name, required, description, "default", type) to stdout;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Mar 11 06 1 0ms 0ms 18 0ms 0ms 0ms 244 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 #18
Day Hour Count Duration Avg duration Mar 11 06 244 0ms 0ms 19 0ms 0ms 0ms 2 0ms lock table public.powerstats in access share mode;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Mar 11 06 2 0ms 0ms 20 0ms 0ms 0ms 4 0ms select oid, enumlabel from pg_catalog.pg_enum where enumtypid = ? order by enumsortorder;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Mar 11 06 4 0ms 0ms Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 2m13s 20 0ms 2m13s 6s658ms select recognitionengine, to_char(datetimeupdate, 'yyyy-mm-dd HH24:MI') from latest_candle_datetime_per_receng;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Mar 11 06 20 2m13s 6s658ms -
select recognitionengine, to_char(datetimeupdate, 'yyyy-mm-dd HH24:MI') from latest_candle_datetime_per_receng;
Date: 2026-03-11 06:19:48 Duration: 2m13s Database: postgres
-
select recognitionengine, to_char(datetimeupdate, 'yyyy-mm-dd HH24:MI') from latest_candle_datetime_per_receng;
Date: 2026-03-11 06:54:25 Duration: 2ms Database: postgres
-
select recognitionengine, to_char(datetimeupdate, 'yyyy-mm-dd HH24:MI') from latest_candle_datetime_per_receng;
Date: 2026-03-11 06:59:26 Duration: 0ms Database: postgres
2 2s444ms 1,763 0ms 17ms 1ms WITH rar_max as ( ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 06 1,763 2s444ms 1ms -
WITH rar_max as ( ;
Date: 2026-03-11 06:28:39 Duration: 17ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-03-11 06:11:49 Duration: 12ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-03-11 06:18:04 Duration: 12ms Database: postgres
3 1s516ms 1,209 0ms 7ms 1ms SELECT symbolid, ;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 06 1,209 1s516ms 1ms -
SELECT symbolid, ;
Date: 2026-03-11 06:47:06 Duration: 7ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-03-11 06:40:38 Duration: 7ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-03-11 06:40:50 Duration: 3ms Database: postgres
4 862ms 2,762 0ms 14ms 0ms SELECT ;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 06 2,762 862ms 0ms -
SELECT ;
Date: 2026-03-11 06:05:36 Duration: 14ms Database: postgres
-
SELECT ;
Date: 2026-03-11 06:15:26 Duration: 11ms Database: postgres
-
SELECT ;
Date: 2026-03-11 06:40:38 Duration: 10ms Database: postgres
5 715ms 632 0ms 3ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 06 632 715ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-11 06:31:23 Duration: 3ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-11 06:15:54 Duration: 2ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-11 06:15:39 Duration: 1ms Database: postgres
6 388ms 48 4ms 56ms 8ms with sym_info as ( ;Times Reported Time consuming prepare #6
Day Hour Count Duration Avg duration 06 48 388ms 8ms -
with sym_info as ( ;
Date: 2026-03-11 06:41:36 Duration: 56ms Database: postgres
-
with sym_info as ( ;
Date: 2026-03-11 06:22:36 Duration: 18ms Database: postgres
-
with sym_info as ( ;
Date: 2026-03-11 06:11:32 Duration: 12ms Database: postgres
7 308ms 1,851 0ms 16ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 06 1,851 308ms 0ms -
SET extra_float_digits = 3;
Date: 2026-03-11 06:14:18 Duration: 16ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-03-11 06:02:12 Duration: 15ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-03-11 06:30:23 Duration: 3ms Database: postgres
8 279ms 2,854 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #8
Day Hour Count Duration Avg duration 06 2,854 279ms 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: 2026-03-11 06:00:25 Duration: 0ms Database: postgres
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-11 06:15:54 Duration: 0ms Database: postgres
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-11 06:15:31 Duration: 0ms Database: postgres
9 199ms 1,843 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 #9
Day Hour Count Duration Avg duration 06 1,843 199ms 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: 2026-03-11 06:00:26 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: 2026-03-11 06:02:11 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: 2026-03-11 06:01:55 Duration: 0ms Database: postgres
10 175ms 1,116 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 #10
Day Hour Count Duration Avg duration 06 1,116 175ms 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: 2026-03-11 06:15:42 Duration: 0ms Database: postgres
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-11 06:32:33 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: 2026-03-11 06:32:39 Duration: 0ms Database: postgres
11 122ms 464 0ms 10ms 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 #11
Day Hour Count Duration Avg duration 06 464 122ms 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: 2026-03-11 06:11:56 Duration: 10ms 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: 2026-03-11 06:11:54 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: 2026-03-11 06:11:54 Duration: 0ms Database: postgres
12 74ms 1,446 0ms 5ms 0ms select 1;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 06 1,446 74ms 0ms -
select 1;
Date: 2026-03-11 06:00:32 Duration: 5ms Database: postgres
-
select 1;
Date: 2026-03-11 06:45:22 Duration: 2ms Database: postgres
-
select 1;
Date: 2026-03-11 06:01:13 Duration: 1ms Database: postgres
13 52ms 24 0ms 9ms 2ms WITH last_candle AS ( ;Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 06 24 52ms 2ms -
WITH last_candle AS ( ;
Date: 2026-03-11 06:32:00 Duration: 9ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-03-11 06:48:00 Duration: 6ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-03-11 06:16:01 Duration: 4ms 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 06 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: 2026-03-11 06:20:03 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: 2026-03-11 06:40:03 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: 2026-03-11 06:30:03 Duration: 4ms Database: postgres
15 29ms 20 0ms 4ms 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 06 20 29ms 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: 2026-03-11 06:17:34 Duration: 4ms 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: 2026-03-11 06:10:29 Duration: 2ms 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: 2026-03-11 06:54:25 Duration: 1ms Database: postgres
16 24ms 15 0ms 3ms 1ms WITH rcr_max as ( ;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 06 15 24ms 1ms -
WITH rcr_max as ( ;
Date: 2026-03-11 06:45:38 Duration: 3ms Database: postgres
-
WITH rcr_max as ( ;
Date: 2026-03-11 06:15:38 Duration: 3ms Database: postgres
-
WITH rcr_max as ( ;
Date: 2026-03-11 06:22:11 Duration: 3ms Database: postgres
17 23ms 1,825 0ms 0ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 06 1,825 23ms 0ms -
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-03-11 06:15:02 Duration: 0ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-03-11 06:30:51 Duration: 0ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-03-11 06:00:22 Duration: 0ms Database: postgres
18 22ms 6 2ms 5ms 3ms 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;Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 06 6 22ms 3ms -
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: 2026-03-11 06:40:02 Duration: 5ms Database: postgres
-
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: 2026-03-11 06:30:02 Duration: 4ms Database: postgres
-
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: 2026-03-11 06:50:02 Duration: 3ms Database: postgres
19 21ms 20 0ms 2ms 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 #19
Day Hour Count Duration Avg duration 06 20 21ms 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: 2026-03-11 06:17:34 Duration: 2ms 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: 2026-03-11 06:20:32 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: 2026-03-11 06:54:25 Duration: 1ms Database: postgres
20 18ms 6 2ms 3ms 3ms select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 06 6 18ms 3ms -
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2026-03-11 06:20:04 Duration: 3ms Database: postgres
-
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2026-03-11 06:50:05 Duration: 3ms Database: postgres
-
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2026-03-11 06:30:05 Duration: 3ms Database: postgres
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 27s286ms 2,232 0ms 52ms 12ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Mar 11 06 2,232 27s286ms 12ms -
WITH rar_max as ( ;
Date: 2026-03-11 06:32:07 Duration: 52ms Database: postgres parameters: $1 = 't', $2 = '558', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '160', $14 = 'AUDSGD', $15 = 'CHFSGD', $16 = 'EURDKK', $17 = 'EURHKD', $18 = 'EURNOK', $19 = 'EURPLN', $20 = 'EURSEK', $21 = 'EURSGD', $22 = 'EURTRY', $23 = 'EURZAR', $24 = 'GBPDKK', $25 = 'GBPNOK', $26 = 'GBPSEK', $27 = 'GBPSGD', $28 = 'NOKJPY', $29 = 'NOKSEK', $30 = 'SEKJPY', $31 = 'SGDJPY', $32 = 'USDCNH', $33 = 'USDCZK', $34 = 'USDDKK', $35 = 'USDHKD', $36 = 'USDHUF', $37 = 'USDMXN', $38 = 'USDNOK', $39 = 'USDPLN', $40 = 'USDRUB', $41 = 'USDSEK', $42 = 'USDTHB', $43 = 'USDTRY', $44 = 'USDZAR', $45 = 'AUDUSD', $46 = 'EURUSD', $47 = 'GBPUSD', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDJPY', $51 = 'AUDCAD', $52 = 'AUDCHF', $53 = 'AUDJPY', $54 = 'AUDNZD', $55 = 'CADCHF', $56 = 'CADJPY', $57 = 'CHFJPY', $58 = 'EURAUD', $59 = 'EURCAD', $60 = 'EURCHF', $61 = 'EURGBP', $62 = 'EURJPY', $63 = 'EURNZD', $64 = 'GBPAUD', $65 = 'GBPCAD', $66 = 'GBPCHF', $67 = 'GBPJPY', $68 = 'GBPNZD', $69 = 'NZDCAD', $70 = 'NZDCHF', $71 = 'NZDJPY', $72 = 'NZDUSD', $73 = 'USDSGD', $74 = 'AUS200', $75 = 'DE30', $76 = 'ES35', $77 = 'F40', $78 = 'HK50', $79 = 'IT40', $80 = 'JP225', $81 = 'STOXX50', $82 = 'UK100', $83 = 'US2000', $84 = 'US30', $85 = 'US500', $86 = 'CHINA50', $87 = 'USTEC', $88 = 'XAGEUR', $89 = 'XAGUSD', $90 = 'XAUUSD', $91 = 'XAUEUR', $92 = 'XPDUSD', $93 = 'XPTUSD', $94 = 'AUDSGD', $95 = 'CHFSGD', $96 = 'EURDKK', $97 = 'EURHKD', $98 = 'EURNOK', $99 = 'EURPLN', $100 = 'EURSEK', $101 = 'EURSGD', $102 = 'EURTRY', $103 = 'EURZAR', $104 = 'GBPDKK', $105 = 'GBPNOK', $106 = 'GBPSEK', $107 = 'GBPSGD', $108 = 'NOKJPY', $109 = 'NOKSEK', $110 = 'SEKJPY', $111 = 'SGDJPY', $112 = 'USDCNH', $113 = 'USDCZK', $114 = 'USDDKK', $115 = 'USDHKD', $116 = 'USDHUF', $117 = 'USDMXN', $118 = 'USDNOK', $119 = 'USDPLN', $120 = 'USDRUB', $121 = 'USDSEK', $122 = 'USDTHB', $123 = 'USDTRY', $124 = 'USDZAR', $125 = 'AUDUSD', $126 = 'EURUSD', $127 = 'GBPUSD', $128 = 'USDCAD', $129 = 'USDCHF', $130 = 'USDJPY', $131 = 'AUDCAD', $132 = 'AUDCHF', $133 = 'AUDJPY', $134 = 'AUDNZD', $135 = 'CADCHF', $136 = 'CADJPY', $137 = 'CHFJPY', $138 = 'EURAUD', $139 = 'EURCAD', $140 = 'EURCHF', $141 = 'EURGBP', $142 = 'EURJPY', $143 = 'EURNZD', $144 = 'GBPAUD', $145 = 'GBPCAD', $146 = 'GBPCHF', $147 = 'GBPJPY', $148 = 'GBPNZD', $149 = 'NZDCAD', $150 = 'NZDCHF', $151 = 'NZDJPY', $152 = 'NZDUSD', $153 = 'USDSGD', $154 = 'AUS200', $155 = 'DE30', $156 = 'ES35', $157 = 'F40', $158 = 'HK50', $159 = 'IT40', $160 = 'JP225', $161 = 'STOXX50', $162 = 'UK100', $163 = 'US2000', $164 = 'US30', $165 = 'US500', $166 = 'CHINA50', $167 = 'USTEC', $168 = 'XAGEUR', $169 = 'XAGUSD', $170 = 'XAUUSD', $171 = 'XAUEUR', $172 = 'XPDUSD', $173 = 'XPTUSD', $174 = '0', $175 = '', $176 = '500', $177 = '500', $178 = '0', $179 = '0', $180 = '0', $181 = 't', $182 = '10', $183 = '10'
-
WITH rar_max as ( ;
Date: 2026-03-11 06:45:26 Duration: 51ms Database: postgres parameters: $1 = '607816624850010301', $2 = '607816624850010301', $3 = '607816624850010301'
-
WITH rar_max as ( ;
Date: 2026-03-11 06:45:26 Duration: 48ms Database: postgres parameters: $1 = '607817331739211301', $2 = '607817331739211301', $3 = '607817331739211301'
2 7s442ms 15,356 0ms 23ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 06 15,356 7s442ms 0ms -
SELECT ;
Date: 2026-03-11 06:26:12 Duration: 23ms Database: postgres parameters: $1 = '515840245933369300', $2 = '0'
-
SELECT ;
Date: 2026-03-11 06:16:16 Duration: 20ms Database: postgres parameters: $1 = '558', $2 = '0', $3 = '0', $4 = 'NZDJPY', $5 = 'NZDJPY'
-
SELECT ;
Date: 2026-03-11 06:16:17 Duration: 20ms Database: postgres parameters: $1 = '558', $2 = '0', $3 = '0', $4 = 'NOKSEK', $5 = 'NOKSEK'
3 2s806ms 1,209 1ms 25ms 2ms SELECT symbolid, ;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 06 1,209 2s806ms 2ms -
SELECT symbolid, ;
Date: 2026-03-11 06:40:38 Duration: 25ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '15', $3 = 'AUS_200'
-
SELECT symbolid, ;
Date: 2026-03-11 06:45:32 Duration: 19ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'LTCUSD', $4 = 'LTCJPY', $5 = 'JP225'
-
SELECT symbolid, ;
Date: 2026-03-11 06:47:06 Duration: 10ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'EURJPY.ID', $4 = 'EURUSD', $5 = 'EURNZD.FX', $6 = 'EURUSD.FX'
4 2s186ms 48 28ms 250ms 45ms with sym_info as ( ;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 06 48 2s186ms 45ms -
with sym_info as ( ;
Date: 2026-03-11 06:41:36 Duration: 250ms 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: 2026-03-11 06:23:04 Duration: 77ms Database: postgres parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'
-
with sym_info as ( ;
Date: 2026-03-11 06:36:50 Duration: 72ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
5 1s166ms 632 1ms 7ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 06 632 1s166ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-11 06:15:39 Duration: 7ms Database: postgres parameters: $1 = 'AXIORY'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-11 06:40:38 Duration: 7ms Database: postgres parameters: $1 = 'BDSWISS'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-11 06:00:50 Duration: 4ms Database: postgres parameters: $1 = 'BDSWISS'
6 759ms 80 4ms 29ms 9ms WITH last_candle AS ( ;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 06 80 759ms 9ms -
WITH last_candle AS ( ;
Date: 2026-03-11 06:08:11 Duration: 29ms Database: postgres parameters: $1 = '538', $2 = '538'
-
WITH last_candle AS ( ;
Date: 2026-03-11 06:32:00 Duration: 20ms Database: postgres parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2026-03-11 06:08:00 Duration: 20ms Database: postgres parameters: $1 = '558', $2 = '558'
7 599ms 21 0ms 53ms 28ms with wh_patitioned as ( ;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 06 21 599ms 28ms -
with wh_patitioned as ( ;
Date: 2026-03-11 06:10:07 Duration: 53ms 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: 2026-03-11 06:21:24 Duration: 46ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
-
with wh_patitioned as ( ;
Date: 2026-03-11 06:49:09 Duration: 44ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
8 547ms 39 10ms 21ms 14ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 06 39 547ms 14ms -
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-03-11 06:52:14 Duration: 21ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-03-11 06:30:24 Duration: 19ms Database: postgres parameters: $1 = '489', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-03-11 06:51:54 Duration: 19ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
9 391ms 13,449 0ms 7ms 0ms select 1;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 06 13,449 391ms 0ms -
select 1;
Date: 2026-03-11 06:51:49 Duration: 7ms Database: postgres
-
select 1;
Date: 2026-03-11 06:12:37 Duration: 6ms Database: postgres
-
select 1;
Date: 2026-03-11 06:12:42 Duration: 6ms Database: postgres
10 316ms 464 0ms 18ms 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 #10
Day Hour Count Duration Avg duration 06 464 316ms 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: 2026-03-11 06:11:56 Duration: 18ms 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: 2026-03-11 06:12:01 Duration: 11ms 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: 2026-03-11 06:11:56 Duration: 3ms Database: postgres
11 265ms 5,219 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 #11
Day Hour Count Duration Avg duration 06 5,219 265ms 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: 2026-03-11 06:47:31 Duration: 0ms Database: postgres parameters: $1 = '2026-03-11 07:30:00', $2 = '1.16321', $3 = '1.16334', $4 = '1.163125', $5 = '1.16331', $6 = '493', $7 = '515840249372435300', $8 = '0', $9 = '2026-03-11 06:47:31.21', $10 = '2026-03-11 06:47:31.101', $11 = '1.16321', $12 = '1.16334', $13 = '1.163125', $14 = '1.16331', $15 = '493', $16 = '0', $17 = '2026-03-11 06:47:31.21', $18 = '2026-03-11 06:47:31.101'
-
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: 2026-03-11 06:56:38 Duration: 0ms Database: postgres parameters: $1 = '2026-03-11 06:30:00', $2 = '8737.4', $3 = '8743.9', $4 = '8736.2', $5 = '8741.9', $6 = '1479', $7 = '515840248015086300', $8 = '0', $9 = '2026-03-11 06:56:38.918', $10 = '2026-03-11 06:56:38.845', $11 = '8737.4', $12 = '8743.9', $13 = '8736.2', $14 = '8741.9', $15 = '1479', $16 = '0', $17 = '2026-03-11 06:56:38.918', $18 = '2026-03-11 06:56:38.845'
-
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: 2026-03-11 06:32:33 Duration: 0ms Database: postgres parameters: $1 = '2026-03-11 07:15:00', $2 = '53.799', $3 = '54.0825', $4 = '53.771', $5 = '54.044', $6 = '274', $7 = '515840249395930300', $8 = '0', $9 = '2026-03-11 06:32:33.619', $10 = '2026-03-11 06:32:33.566', $11 = '53.799', $12 = '54.0825', $13 = '53.771', $14 = '54.044', $15 = '274', $16 = '0', $17 = '2026-03-11 06:32:33.619', $18 = '2026-03-11 06:32:33.566'
12 246ms 2,994 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 06 2,994 246ms 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: 2026-03-11 06:11:39 Duration: 0ms Database: postgres parameters: $1 = '2026-03-11 05:00:00', $2 = '8737.4', $3 = '8751.9', $4 = '8735.25', $5 = '8749.7', $6 = '2589', $7 = '515840248015340300', $8 = '0', $9 = '2026-03-11 06:11:39.469', $10 = '2026-03-11 06:11:39.388', $11 = '8737.4', $12 = '8751.9', $13 = '8735.25', $14 = '8749.7', $15 = '2589', $16 = '0', $17 = '2026-03-11 06:11:39.469', $18 = '2026-03-11 06:11:39.388'
-
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: 2026-03-11 06:48:51 Duration: 0ms Database: postgres parameters: $1 = '2026-03-10 22:30:00', $2 = '137.07', $3 = '137.44', $4 = '136.635', $5 = '136.845', $6 = '1136', $7 = '515840249416853300', $8 = '0', $9 = '2026-03-11 06:48:51.187', $10 = '2026-03-11 06:48:51.082', $11 = '137.07', $12 = '137.44', $13 = '136.635', $14 = '136.845', $15 = '1136', $16 = '0', $17 = '2026-03-11 06:48:51.187', $18 = '2026-03-11 06:48:51.082'
-
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: 2026-03-11 06:00:07 Duration: 0ms Database: postgres parameters: $1 = '2026-03-11 06:30:00', $2 = '212.75', $3 = '212.837', $4 = '212.731', $5 = '212.808', $6 = '6762', $7 = '515840243917702300', $8 = '0', $9 = '2026-03-11 06:00:07.788', $10 = '2026-03-11 06:00:07.775', $11 = '212.75', $12 = '212.837', $13 = '212.731', $14 = '212.808', $15 = '6762', $16 = '0', $17 = '2026-03-11 06:00:07.788', $18 = '2026-03-11 06:00:07.775'
13 238ms 30 0ms 34ms 7ms select distinct s.statsid as statsid, sy.exchange as name;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 06 30 238ms 7ms -
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-03-11 06:22:06 Duration: 34ms Database: postgres parameters: $1 = '1506', $2 = '1506'
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-03-11 06:22:05 Duration: 32ms Database: postgres parameters: $1 = '1436', $2 = '1436'
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-03-11 06:22:06 Duration: 29ms Database: postgres parameters: $1 = '489', $2 = '489'
14 176ms 1,997 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 #14
Day Hour Count Duration Avg duration 06 1,997 176ms 0ms -
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-11 06:00:50 Duration: 1ms Database: postgres parameters: $1 = '2026-03-11 06:00:00', $2 = '0.71652', $3 = '0.71766', $4 = '0.71625', $5 = '0.71754', $6 = '2646', $7 = '515840230435374300', $8 = '0', $9 = '2026-03-11 06:00:50.59', $10 = '2026-03-11 06:00:50.589', $11 = '0.71652', $12 = '0.71766', $13 = '0.71625', $14 = '0.71754', $15 = '2646', $16 = '0', $17 = '2026-03-11 06:00:50.59', $18 = '2026-03-11 06:00:50.589'
-
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: 2026-03-11 06:15:22 Duration: 1ms Database: postgres parameters: $1 = '2026-03-11 06:00:00', $2 = '11057530.5', $3 = '11068773.5', $4 = '11001288.5', $5 = '11009789', $6 = '5536', $7 = '515840249393612300', $8 = '0', $9 = '2026-03-11 06:15:22.615', $10 = '2026-03-11 06:15:22.614', $11 = '11057530.5', $12 = '11068773.5', $13 = '11001288.5', $14 = '11009789', $15 = '5536', $16 = '0', $17 = '2026-03-11 06:15:22.615', $18 = '2026-03-11 06:15:22.614'
-
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: 2026-03-11 06:02:11 Duration: 0ms Database: postgres parameters: $1 = '2026-03-11 06:00:00', $2 = '25097.7', $3 = '25122.45', $4 = '25084.7', $5 = '25114.7', $6 = '10331', $7 = '500991628277679200', $8 = '0', $9 = '2026-03-11 06:02:11.679', $10 = '2026-03-11 06:02:11.678', $11 = '25097.7', $12 = '25122.45', $13 = '25084.7', $14 = '25114.7', $15 = '10331', $16 = '0', $17 = '2026-03-11 06:02:11.679', $18 = '2026-03-11 06:02:11.678'
15 92ms 1,064 0ms 1ms 0ms select category, ;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 06 1,064 92ms 0ms -
select category, ;
Date: 2026-03-11 06:22:06 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307', $2 = 'symbol', $3 = 'XAUUSD', $4 = 'DOW30', $5 = 'XAGUSD', $6 = 'USDJPY', $7 = 'AUDJPY', $8 = 'GBPJPY', $9 = 'NZDJPY', $10 = 'SP500', $11 = 'NASDAQ100', $12 = 'OIL', $13 = 'CHFJPY', $14 = 'EURJPY', $15 = 'GBPAUD', $16 = 'EURAUD', $17 = 'GBPCHF', $18 = 'USDCAD', $19 = 'EURCHF', $20 = 'EURGBP', $21 = 'OIL', $22 = 'EURCAD', $23 = 'EURCAD', $24 = 'DOW30', $25 = 'GBPUSD', $26 = 'EURJPY', $27 = 'NZDUSD', $28 = 'EURUSD', $29 = 'XAGUSD', $30 = 'CHFJPY', $31 = 'GBPUSD', $32 = 'GBPAUD', $33 = 'EURAUD', $34 = 'AUDJPY', $35 = 'EURUSD', $36 = 'USDCHF', $37 = 'SP500', $38 = 'NZDJPY', $39 = 'RK_SSI', $40 = 'R_SSI', $41 = 'GBPJPY', $42 = 'XAUUSD', $43 = 'AUDNZD', $44 = 'USDCAD', $45 = 'AUDUSD', $46 = 'NASDAQ100', $47 = 'USDJPY', $48 = 'NZDUSD', $49 = 'AUDUSD', $50 = 'GBPCHF', $51 = 'USDCHF', $52 = 'AUDNZD', $53 = '515852059317765307', $54 = 'symbol', $55 = 'XAUUSD', $56 = 'DOW30', $57 = 'XAGUSD', $58 = 'USDJPY', $59 = 'AUDJPY', $60 = 'GBPJPY', $61 = 'NZDJPY', $62 = 'SP500', $63 = 'NASDAQ100', $64 = 'OIL', $65 = 'CHFJPY', $66 = 'EURJPY', $67 = 'GBPAUD', $68 = 'EURAUD', $69 = 'GBPCHF', $70 = 'USDCAD', $71 = 'EURCHF', $72 = 'EURGBP', $73 = 'OIL', $74 = 'EURCAD', $75 = 'EURCAD', $76 = 'DOW30', $77 = 'GBPUSD', $78 = 'EURJPY', $79 = 'NZDUSD', $80 = 'EURUSD', $81 = 'XAGUSD', $82 = 'CHFJPY', $83 = 'GBPUSD', $84 = 'GBPAUD', $85 = 'EURAUD', $86 = 'AUDJPY', $87 = 'EURUSD', $88 = 'USDCHF', $89 = 'SP500', $90 = 'NZDJPY', $91 = 'RK_SSI', $92 = 'R_SSI', $93 = 'GBPJPY', $94 = 'XAUUSD', $95 = 'AUDNZD', $96 = 'USDCAD', $97 = 'AUDUSD', $98 = 'NASDAQ100', $99 = 'USDJPY', $100 = 'NZDUSD', $101 = 'AUDUSD', $102 = 'GBPCHF', $103 = 'USDCHF', $104 = 'AUDNZD'
-
select category, ;
Date: 2026-03-11 06:22:10 Duration: 1ms Database: postgres parameters: $1 = '515852059324736307', $2 = 'symbol', $3 = 'USDMXN', $4 = 'CHFZAR', $5 = 'AUDJPY', $6 = 'USDZAR', $7 = 'USDJPY', $8 = 'ZARJPY', $9 = 'CADJPY', $10 = 'CHFJPY', $11 = 'GBPZAR', $12 = 'EURCNH', $13 = 'EURMXN', $14 = 'NZDJPY', $15 = 'TRYJPY', $16 = 'GBPJPY', $17 = 'AUDZAR', $18 = 'USDHUF', $19 = 'USDNOK', $20 = 'EURNOK', $21 = 'EURZAR', $22 = 'USDCZK', $23 = 'USDSEK', $24 = 'EURHKD', $25 = 'EURTRY', $26 = 'EURSEK', $27 = 'SGDJPY', $28 = 'USDDKK', $29 = 'NZDSEK', $30 = 'EURJPY', $31 = 'CHFHUF', $32 = 'EURHUF', $33 = 'USDPLN', $34 = 'GBPNZD', $35 = 'USDCNH', $36 = 'EURCZK', $37 = 'USDILS', $38 = 'EURNZD', $39 = 'EURGBP', $40 = 'EURPLN', $41 = 'GBPAUD', $42 = 'EURCZK', $43 = 'TRYJPY', $44 = 'EURAUD', $45 = 'CHFHUF', $46 = 'GBPCAD', $47 = 'EURHUF', $48 = 'ZARJPY', $49 = 'USDCAD', $50 = 'EURDKK', $51 = 'AUDZAR', $52 = 'USDZAR', $53 = '515852059324736307', $54 = 'symbol', $55 = 'USDMXN', $56 = 'CHFZAR', $57 = 'AUDJPY', $58 = 'USDZAR', $59 = 'USDJPY', $60 = 'ZARJPY', $61 = 'CADJPY', $62 = 'CHFJPY', $63 = 'GBPZAR', $64 = 'EURCNH', $65 = 'EURMXN', $66 = 'NZDJPY', $67 = 'TRYJPY', $68 = 'GBPJPY', $69 = 'AUDZAR', $70 = 'USDHUF', $71 = 'USDNOK', $72 = 'EURNOK', $73 = 'EURZAR', $74 = 'USDCZK', $75 = 'USDSEK', $76 = 'EURHKD', $77 = 'EURTRY', $78 = 'EURSEK', $79 = 'SGDJPY', $80 = 'USDDKK', $81 = 'NZDSEK', $82 = 'EURJPY', $83 = 'CHFHUF', $84 = 'EURHUF', $85 = 'USDPLN', $86 = 'GBPNZD', $87 = 'USDCNH', $88 = 'EURCZK', $89 = 'USDILS', $90 = 'EURNZD', $91 = 'EURGBP', $92 = 'EURPLN', $93 = 'GBPAUD', $94 = 'EURCZK', $95 = 'TRYJPY', $96 = 'EURAUD', $97 = 'CHFHUF', $98 = 'GBPCAD', $99 = 'EURHUF', $100 = 'ZARJPY', $101 = 'USDCAD', $102 = 'EURDKK', $103 = 'AUDZAR', $104 = 'USDZAR'
-
select category, ;
Date: 2026-03-11 06:22:10 Duration: 1ms Database: postgres parameters: $1 = '515852059296080307', $2 = 'symbol', $3 = 'AUDJPY', $4 = 'NZDJPY', $5 = 'USDMXN', $6 = 'EURMXN', $7 = 'USDNOK', $8 = 'USDJPY', $9 = 'NOKJPY', $10 = 'CADJPY', $11 = 'ZARJPY', $12 = 'GBPJPY', $13 = 'CHFJPY', $14 = 'USDZAR', $15 = 'EURNOK', $16 = 'HKDJPY', $17 = 'GBPZAR', $18 = 'EURSEK', $19 = 'USDSEK', $20 = 'USDDKK', $21 = 'USDPLN', $22 = 'EURTRY', $23 = 'EURJPY', $24 = 'GBPAUD', $25 = 'USDCNH', $26 = 'GBPNZD', $27 = 'EURNZD', $28 = 'ZARJPY', $29 = 'EURAUD', $30 = 'EURPLN', $31 = 'EURGBP', $32 = 'GBPCAD', $33 = 'EURNOK', $34 = 'USDZAR', $35 = 'USDCAD', $36 = 'EURCAD', $37 = 'EURNZD', $38 = 'EURCHF', $39 = 'EURSEK', $40 = 'NOKJPY', $41 = 'EURMXN', $42 = 'GBPZAR', $43 = 'USDMXN', $44 = 'HKDJPY', $45 = 'CADJPY', $46 = 'GBPUSD', $47 = 'USDSGD', $48 = 'CADCHF', $49 = 'USDPLN', $50 = 'AUDJPY', $51 = 'EURPLN', $52 = 'EURCAD', $53 = '515852059296080307', $54 = 'symbol', $55 = 'AUDJPY', $56 = 'NZDJPY', $57 = 'USDMXN', $58 = 'EURMXN', $59 = 'USDNOK', $60 = 'USDJPY', $61 = 'NOKJPY', $62 = 'CADJPY', $63 = 'ZARJPY', $64 = 'GBPJPY', $65 = 'CHFJPY', $66 = 'USDZAR', $67 = 'EURNOK', $68 = 'HKDJPY', $69 = 'GBPZAR', $70 = 'EURSEK', $71 = 'USDSEK', $72 = 'USDDKK', $73 = 'USDPLN', $74 = 'EURTRY', $75 = 'EURJPY', $76 = 'GBPAUD', $77 = 'USDCNH', $78 = 'GBPNZD', $79 = 'EURNZD', $80 = 'ZARJPY', $81 = 'EURAUD', $82 = 'EURPLN', $83 = 'EURGBP', $84 = 'GBPCAD', $85 = 'EURNOK', $86 = 'USDZAR', $87 = 'USDCAD', $88 = 'EURCAD', $89 = 'EURNZD', $90 = 'EURCHF', $91 = 'EURSEK', $92 = 'NOKJPY', $93 = 'EURMXN', $94 = 'GBPZAR', $95 = 'USDMXN', $96 = 'HKDJPY', $97 = 'CADJPY', $98 = 'GBPUSD', $99 = 'USDSGD', $100 = 'CADCHF', $101 = 'USDPLN', $102 = 'AUDJPY', $103 = 'EURPLN', $104 = 'EURCAD'
16 89ms 15 1ms 19ms 5ms WITH rcr_max as ( ;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 06 15 89ms 5ms -
WITH rcr_max as ( ;
Date: 2026-03-11 06:14:18 Duration: 19ms Database: postgres parameters: $1 = '607817333427533305', $2 = '607817333427533305', $3 = '607817333427533305'
-
WITH rcr_max as ( ;
Date: 2026-03-11 06:45:38 Duration: 12ms Database: postgres parameters: $1 = '607817330925884305', $2 = '607817330925884305', $3 = '607817330925884305'
-
WITH rcr_max as ( ;
Date: 2026-03-11 06:15:20 Duration: 11ms Database: postgres parameters: $1 = '607817333336010305', $2 = '607817333336010305', $3 = '607817333336010305'
17 71ms 59 0ms 4ms 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 #17
Day Hour Count Duration Avg duration 06 59 71ms 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: 2026-03-11 06:10:40 Duration: 4ms Database: postgres parameters: $1 = '689', $2 = 'XAUUSD', $3 = '689'
-
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: 2026-03-11 06:39:39 Duration: 3ms 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: 2026-03-11 06:06:49 Duration: 2ms Database: postgres parameters: $1 = '667', $2 = 'GBPJPY', $3 = '667'
18 52ms 6 5ms 11ms 8ms 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;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 06 6 52ms 8ms -
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: 2026-03-11 06:50:02 Duration: 11ms Database: postgres
-
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: 2026-03-11 06:40:02 Duration: 10ms Database: postgres
-
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: 2026-03-11 06:30:02 Duration: 9ms Database: postgres
19 51ms 1 51ms 51ms 51ms with maxwhid as ( ;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 06 1 51ms 51ms -
with maxwhid as ( ;
Date: 2026-03-11 06:11:58 Duration: 51ms Database: postgres parameters: $1 = '335', $2 = '621', $3 = '637', $4 = '642', $5 = '666', $6 = '660', $7 = '643', $8 = '630', $9 = '680', $10 = '641', $11 = '431', $12 = '622', $13 = '489', $14 = '529', $15 = '576', $16 = '665', $17 = '667', $18 = '558', $19 = '620', $20 = '125', $21 = '488', $22 = '567', $23 = '689', $24 = '700', $25 = '758', $26 = '763', $27 = '765', $28 = '817', $29 = '914', $30 = '972'
20 44ms 56 0ms 1ms 0ms SELECT absolutetimezoneoffset;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 06 56 44ms 0ms -
SELECT absolutetimezoneoffset;
Date: 2026-03-11 06:22:08 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'BROKER'
-
SELECT absolutetimezoneoffset;
Date: 2026-03-11 06:22:06 Duration: 1ms Database: postgres parameters: $1 = '489', $2 = 'BROKER'
-
SELECT absolutetimezoneoffset;
Date: 2026-03-11 06:22:38 Duration: 0ms Database: postgres parameters: $1 = '972', $2 = 'Indices'
-
Events
Log levels
Key values
- 316,916 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 357 ERROR entries
- 0 WARNING entries
Most Frequent Errors/Events
Key values
- 292 Max number of times the same event was reported
- 357 Total events found
Rank Times reported Error 1 292 ERROR: canceling statement due to statement timeout
Times Reported Most Frequent Error / Event #1
Day Hour Count Mar 11 06 292 - ERROR: canceling statement due to statement timeout
Statement: /* service='datadog-agent' */ select count(*) from (select *, row_number() over (partition by whid order by id desc) r from whatshot_probability where "type" = 'cp' union select *, row_number() over (partition by whid order by id desc) r from whatshot_probability where "type" = 'ekl' union select *, row_number() over (partition by whid order by id desc) r from whatshot_probability where type = 'kl') as k where r > 3;
Date: 2026-03-11 06:00:13
2 62 LOG: process ... still waiting for AccessShareLock on relation ... of database ... after ... ms
Times Reported Most Frequent Error / Event #2
Day Hour Count Mar 11 06 62 - LOG: process 20058 still waiting for AccessShareLock on relation 5883477 of database 5881926 after 1000.044 ms
- LOG: process 20058 still waiting for AccessShareLock on relation 5883477 of database 5881926 after 1440.079 ms
- LOG: process 20058 still waiting for AccessShareLock on relation 5883477 of database 5881926 after 1000.056 ms
Detail: Process holding the lock: 10190. Wait queue: 10298, 20058.
Statement: /* service='datadog-agent' */ SELECT current_database(), s.schemaname, s.table, s.partition_of, s.relpages, s.reltuples, s.relallvisible, s.relation_size + s.toast_size, s.relation_size, s.index_size, s.toast_size, s.relation_size + s.index_size + s.toast_size FROM (SELECT N.nspname as schemaname, relname as table, I.inhparent::regclass AS partition_of, C.relpages, C.reltuples, C.relallvisible, pg_relation_size(C.oid) as relation_size, CASE WHEN C.relhasindex THEN pg_indexes_size(C.oid) ELSE 0 END as index_size, CASE WHEN C.reltoastrelid > 0 THEN pg_relation_size(C.reltoastrelid) ELSE 0 END as toast_size FROM pg_class C LEFT JOIN pg_namespace N ON (N.oid = C.relnamespace) LEFT JOIN pg_inherits I ON (I.inhrelid = C.oid) LEFT JOIN pg_locks L ON C.oid = L.relation AND L.locktype = 'relation' WHERE NOT (nspname = ANY('{pg_catalog,information_schema}')) AND (L.relation IS NULL OR L.mode <> 'AccessExclusiveLock' OR NOT L.granted) AND relkind = 'r' AND (( relname ~ '.*' )) LIMIT 300) as sDate: 2026-03-11 06:05:20
Detail: Process holding the lock: 10190. Wait queue: 10298, 20058.
Statement: /* service='datadog-agent' */ SELECT current_database(), s.schemaname, s.table, s.partition_of, s.relpages, s.reltuples, s.relallvisible, s.relation_size + s.toast_size, s.relation_size, s.index_size, s.toast_size, s.relation_size + s.index_size + s.toast_size FROM (SELECT N.nspname as schemaname, relname as table, I.inhparent::regclass AS partition_of, C.relpages, C.reltuples, C.relallvisible, pg_relation_size(C.oid) as relation_size, CASE WHEN C.relhasindex THEN pg_indexes_size(C.oid) ELSE 0 END as index_size, CASE WHEN C.reltoastrelid > 0 THEN pg_relation_size(C.reltoastrelid) ELSE 0 END as toast_size FROM pg_class C LEFT JOIN pg_namespace N ON (N.oid = C.relnamespace) LEFT JOIN pg_inherits I ON (I.inhrelid = C.oid) LEFT JOIN pg_locks L ON C.oid = L.relation AND L.locktype = 'relation' WHERE NOT (nspname = ANY('{pg_catalog,information_schema}')) AND (L.relation IS NULL OR L.mode <> 'AccessExclusiveLock' OR NOT L.granted) AND relkind = 'r' AND (( relname ~ '.*' )) LIMIT 300) as sDate: 2026-03-11 06:05:20
Detail: Process holding the lock: 10190. Wait queue: 10298, 20058.
Statement: /* service='datadog-agent' */ SELECT current_database(), s.schemaname, s.table, s.partition_of, s.relpages, s.reltuples, s.relallvisible, s.relation_size + s.toast_size, s.relation_size, s.index_size, s.toast_size, s.relation_size + s.index_size + s.toast_size FROM (SELECT N.nspname as schemaname, relname as table, I.inhparent::regclass AS partition_of, C.relpages, C.reltuples, C.relallvisible, pg_relation_size(C.oid) as relation_size, CASE WHEN C.relhasindex THEN pg_indexes_size(C.oid) ELSE 0 END as index_size, CASE WHEN C.reltoastrelid > 0 THEN pg_relation_size(C.reltoastrelid) ELSE 0 END as toast_size FROM pg_class C LEFT JOIN pg_namespace N ON (N.oid = C.relnamespace) LEFT JOIN pg_inherits I ON (I.inhrelid = C.oid) LEFT JOIN pg_locks L ON C.oid = L.relation AND L.locktype = 'relation' WHERE NOT (nspname = ANY('{pg_catalog,information_schema}')) AND (L.relation IS NULL OR L.mode <> 'AccessExclusiveLock' OR NOT L.granted) AND relkind = 'r' AND (( relname ~ '.*' )) LIMIT 300) as sDate: 2026-03-11 06:05:35
3 3 LOG: process ... still waiting for AccessExclusiveLock on relation ... of database ... after ... ms
Times Reported Most Frequent Error / Event #3
Day Hour Count Mar 11 06 3 - LOG: process 10298 still waiting for AccessExclusiveLock on relation 5883477 of database 5881926 after 1000.058 ms
- LOG: process 10298 still waiting for AccessExclusiveLock on relation 5883477 of database 5881926 after 9325.478 ms
- LOG: process 16496 still waiting for AccessExclusiveLock on relation 5894441 of database 5881926 after 1000.044 ms
Detail: Process holding the lock: 10190. Wait queue: 10298.
Statement: TRUNCATE TABLE solr_relevance_old;Date: 2026-03-11 06:05:12
Detail: Process holding the lock: 10190. Wait queue: 10298, 20058.
Statement: TRUNCATE TABLE solr_relevance_old;Date: 2026-03-11 06:05:20
Detail: Process holding the lock: 10190. Wait queue: 16496.
Statement: refresh materialized view latest_candle_datetime_per_recengDate: 2026-03-11 06:17:02