pgBadger-
Global information
- Generated on Sun Mar 15 07:59:26 2026
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-03-15_090000.log
- Parsed 833,541 log entries in 25s
- Log start from 2026-03-15 09:00:00 to 2026-03-15 09:59:24
-
Overview
Global Stats
- 189 Number of unique normalized queries
- 114,191 Number of queries
- 59m30s Total query duration
- 2026-03-15 09:00:00 First query
- 2026-03-15 09:59:24 Last query
- 4,510 queries/s at 2026-03-15 09:10:50 Query peak
- 59m30s Total query duration
- 2s467ms Prepare/parse total duration
- 14s323ms Bind total duration
- 59m13s Execute total duration
- 238 Number of events
- 2 Number of unique normalized events
- 237 Max number of times the same event was reported
- 0 Number of cancellation
- 29 Total number of automatic vacuums
- 40 Total number of automatic analyzes
- 1,603 Number temporary file
- 600.62 MiB Max size of temporary file
- 82.54 MiB Average size of temporary file
- 1,717 Total number of sessions
- 12 sessions at 2026-03-15 09:56:45 Session peak
- 23d9h56m1s Total duration of sessions
- 19m38s Average duration of sessions
- 66 Average queries per session
- 2s79ms Average queries duration per session
- 19m36s Average idle time per session
- 1,708 Total number of connections
- 29 connections/s at 2026-03-15 09:48:48 Connection peak
- 3 Total number of databases
SQL Traffic
Key values
- 4,510 queries/s Query Peak
- 2026-03-15 09:10:50 Date
SELECT Traffic
Key values
- 2,252 queries/s Query Peak
- 2026-03-15 09:10:50 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 84 queries/s Query Peak
- 2026-03-15 09:58:50 Date
Queries duration
Key values
- 59m30s 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 15 09 114,191 0ms 24s109ms 31ms 2m15s 2m25s 2m30s Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Mar 15 09 40,900 26 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Mar 15 09 11,384 467 16 96 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Mar 15 09 10,024 40,956 4.09 18.20% Day Hour Count Average / Second Mar 15 09 1,708 0.47/s Day Hour Count Average Duration Average idle time Mar 15 09 1,717 19m38s 19m36s -
Connections
Established Connections
Key values
- 29 connections Connection Peak
- 2026-03-15 09:48:48 Date
Connections per database
Key values
- acaweb_fx Main Database
- 1,708 connections Total
Connections per user
Key values
- postgres Main User
- 1,708 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 632 connections
- 1,708 Total connections
-
Sessions
Simultaneous sessions
Key values
- 12 sessions Session Peak
- 2026-03-15 09:56:45 Date
Histogram of session times
Key values
- 1,317 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 1,717 sessions Total
Sessions per user
Key values
- postgres Main User
- 1,717 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 1,717 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 106 2s516ms 23ms 182.165.1.54 2 23h23m25s 11h41m42s 192.168.0.114 2 10m 5m 192.168.0.216 116 6m25s 3s326ms 192.168.0.74 21 4d3h42m23s 4h44m52s 192.168.0.84 2 23h59m27s 11h59m43s 192.168.1.131 2 23h59m26s 11h59m43s 192.168.1.145 13 4d9h35m 8h7m18s 192.168.1.15 10 5d1h43m19s 12h10m19s 192.168.1.20 34 5d19h3m31s 4h5m23s 192.168.1.238 2 23h59m21s 11h59m40s 192.168.1.239 56 325ms 5ms 192.168.1.90 30 503ms 16ms 192.168.2.126 18 5s139ms 285ms 192.168.3.199 38 23s714ms 624ms 192.168.4.142 632 7m44s 735ms 192.168.4.33 67 59s221ms 883ms 192.168.4.98 330 13s727ms 41ms [local] 236 4m10s 1s61ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 2,116 buffers Checkpoint Peak
- 2026-03-15 09:07:42 Date
- 208.037 seconds Highest write time
- 0.052 seconds Sync time
Checkpoints Wal files
Key values
- 2 files Wal files usage Peak
- 2026-03-15 09:37:43 Date
Checkpoints distance
Key values
- 48.93 Mo Distance Peak
- 2026-03-15 09:07:42 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Mar 15 09 12,600 1,298.64s 0.094s 1,342.787s Day Hour Added Removed Recycled Synced files Longest sync Average sync Mar 15 09 0 0 10 1,202 0.052s 0.001s Day Hour Count Avg time (sec) Mar 15 09 0 0s Day Hour Mean distance Mean estimate Mar 15 09 14,185.55 kB 21,673.00 kB -
Temporary Files
Size of temporary files
Key values
- 600.62 MiB Temp Files size Peak
- 2026-03-15 09:23:59 Date
Number of temporary files
Key values
- 62 per second Temp Files Peak
- 2026-03-15 09:32:10 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Mar 15 09 1,603 129.22 GiB 82.54 MiB Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 237 126.15 GiB 306.36 MiB 600.62 MiB 545.05 MiB classname, case when latestdbwritetime < current_timestamp - interval ? then ? else ? end as is_stale from latest_t15_candle_view order by classname;-
classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;
Date: 2026-03-15 09:00:12 Duration: 0ms
2 96 166.77 MiB 137.65 KiB 4.02 MiB 1.74 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: 2026-03-15 09:01:11 Duration: 0ms
3 32 162.02 MiB 4.91 MiB 5.52 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: 2026-03-15 09:01:19 Duration: 0ms
4 16 623.12 MiB 38.95 MiB 38.95 MiB 38.95 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: 2026-03-15 09:01:16 Duration: 0ms
5 16 1.23 GiB 78.53 MiB 78.53 MiB 78.53 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: 2026-03-15 09:01:19 Duration: 0ms
6 8 30.57 MiB 3.82 MiB 3.82 MiB 3.82 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: 2026-03-15 09:08:55 Duration: 0ms
7 4 567.86 MiB 141.96 MiB 141.97 MiB 141.97 MiB select updateresultsmaterializedview ();-
select updateresultsmaterializedview ();
Date: 2026-03-15 09:02:15 Duration: 0ms
8 4 335.07 MiB 83.76 MiB 83.77 MiB 83.77 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2026-03-15 09:02:05 Duration: 0ms
Queries generating the largest temporary files
Rank Size Query 1 600.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:23:59 ]
2 600.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:32:28 ]
3 600.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:33:12 ]
4 597.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:19:44 ]
5 597.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:30:13 ]
6 594.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:08:58 ]
7 594.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:27:42 ]
8 594.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:52:12 ]
9 594.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:52:42 ]
10 591.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:03:44 ]
11 591.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:17:42 ]
12 591.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:52:27 ]
13 588.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:00:58 ]
14 588.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:18:42 ]
15 588.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:28:27 ]
16 588.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:28:59 ]
17 588.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:55:27 ]
18 585.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:22:59 ]
19 585.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:23:27 ]
20 585.62 MiB classname, CASE WHEN latestdbwritetime < current_timestamp - interval '18 hours' THEN 1 ELSE 0 END AS is_stale FROM latest_t15_candle_view order by classname;[ Date: 2026-03-15 09:27:59 ]
-
Vacuums
Vacuums / Analyzes Distribution
Key values
- 0 sec Highest CPU-cost vacuum
Table
Database - Date
- 0 sec Highest CPU-cost analyze
Table
Database - Date
Analyzes per table
Key values
- public.solr_relevance_old (16) Main table analyzed (database acaweb_fx)
- 40 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 16 acaweb_fx.pg_catalog.pg_attribute 7 acaweb_fx.pg_catalog.pg_type 4 acaweb_fx.pg_catalog.pg_class 4 acaweb_fx.public.datafeeds_latestrun 3 acaweb_fx.pg_catalog.pg_index 1 acaweb_fx.public.latest_t15_candle_view 1 acaweb_fx.pg_catalog.pg_depend 1 acaweb_fx.public.relevance_autochartist_results 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.relevance_fibonacci_results 1 Total 40 Vacuums per table
Key values
- public.solr_relevance_old (16) Main table vacuumed on database acaweb_fx
- 29 vacuums Total
Index Buffer usage Skipped WAL usage Table Vacuums scans hits misses dirtied pins frozen records full page bytes acaweb_fx.public.solr_relevance_old 16 16 10,895 0 48 0 0 6,587 231 2,039,434 acaweb_fx.public.datafeeds_latestrun 3 0 346 0 5 0 0 37 11 41,369 acaweb_fx.pg_catalog.pg_attribute 3 3 2,894 0 376 0 201 1,143 370 2,122,461 acaweb_fx.pg_catalog.pg_type 2 2 369 0 45 0 0 157 42 212,844 acaweb_fx.pg_catalog.pg_class 2 2 922 0 72 0 0 284 72 446,061 acaweb_fx.public.solr_imports 1 1 49 0 1 0 0 6 1 8,929 acaweb_fx.pg_catalog.pg_depend 1 1 413 0 81 0 59 186 72 366,392 acaweb_fx.public.relevance_keylevels_results 1 1 3,386 0 230 0 113 510 220 984,457 Total 29 26 19,274 5,786 858 0 373 8,910 1,019 6,221,947 Tuples removed per table
Key values
- public.solr_relevance_old (12789) Main table with removed tuples on database acaweb_fx
- 21311 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 16 16 12,789 82,454 0 0 2,584 acaweb_fx.pg_catalog.pg_attribute 3 3 5,649 32,221 274 21 809 acaweb_fx.pg_catalog.pg_depend 1 1 882 14,393 0 0 144 acaweb_fx.pg_catalog.pg_type 2 2 771 2,913 3 0 90 acaweb_fx.public.relevance_keylevels_results 1 1 754 11,376 0 0 279 acaweb_fx.pg_catalog.pg_class 2 2 248 3,312 0 0 300 acaweb_fx.public.datafeeds_latestrun 3 0 167 42 0 0 48 acaweb_fx.public.solr_imports 1 1 51 1 0 0 2 Total 29 26 21,311 146,712 277 21 4,256 Pages removed per table
Key values
- pg_catalog.pg_attribute (21) Main table with removed pages on database acaweb_fx
- 21 pages Total removed
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_catalog.pg_attribute 3 3 5649 21 acaweb_fx.pg_catalog.pg_type 2 2 771 0 acaweb_fx.public.datafeeds_latestrun 3 0 167 0 acaweb_fx.public.solr_imports 1 1 51 0 acaweb_fx.pg_catalog.pg_depend 1 1 882 0 acaweb_fx.public.relevance_keylevels_results 1 1 754 0 acaweb_fx.pg_catalog.pg_class 2 2 248 0 acaweb_fx.public.solr_relevance_old 16 16 12789 0 Total 29 26 21,311 21 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Mar 15 09 29 40 - 0 sec Highest CPU-cost vacuum
-
Locks
Locks by types
Key values
- unknown Main Lock Type
- 0 locks Total
Most frequent waiting queries (N)
Rank Count Total time Min time Max time Avg duration Query NO DATASET
Queries that waited the most
Rank Wait time Query NO DATASET
-
Queries
Queries by type
Key values
- 40,900 Total read queries
- 14,166 Total write queries
Queries by database
Key values
- unknown Main database
- 113,240 Requests
- 59m13s (unknown)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 884 0ms copy from 80 0ms copy to 26 0ms cte 100 0ms ddl 16 0ms delete 16 0ms others 214 0ms select 64 0ms tcl 332 0ms update 36 0ms socialmedia Total 67 0ms select 67 0ms unknown Total 113,240 59m13s copy from 16 0ms cte 1,397 0ms insert 11,384 0ms others 1,934 0ms select 40,769 0ms tcl 332 0ms update 431 0ms Queries by user
Key values
- unknown Main user
- 113,240 Requests
User Request type Count Duration postgres Total 951 0ms copy from 80 0ms copy to 26 0ms cte 100 0ms ddl 16 0ms delete 16 0ms others 214 0ms select 131 0ms tcl 332 0ms update 36 0ms unknown Total 113,240 59m13s copy from 16 0ms cte 1,397 0ms insert 11,384 0ms others 1,934 0ms select 40,769 0ms tcl 332 0ms update 431 0ms Duration by user
Key values
- 59m13s (unknown) Main time consuming user
User Request type Count Duration postgres Total 951 0ms copy from 80 0ms copy to 26 0ms cte 100 0ms ddl 16 0ms delete 16 0ms others 214 0ms select 131 0ms tcl 332 0ms update 36 0ms unknown Total 113,240 59m13s copy from 16 0ms cte 1,397 0ms insert 11,384 0ms others 1,934 0ms select 40,769 0ms tcl 332 0ms update 431 0ms Queries by host
Key values
- unknown Main host
- 114,191 Requests
- 59m13s (unknown)
- Main time consuming host
Queries by application
Key values
- unknown Main application
- 113,849 Requests
- 59m13s (unknown)
- Main time consuming application
Number of cancelled queries
Key values
- 1 per second Cancelled query Peak
- 2026-03-15 09:18:57 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 43,843 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 15 0ms 0ms 0ms select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 15 09 15 0ms 0ms 2 0ms 69 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Mar 15 09 69 0ms 0ms 3 0ms 2 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ) select bmr.symbolid, patternstarttime, patternendtime, timegranularity, ? as direction, case when bmr.old_resultuid = ? then bmr.old_resultuid else bmr.resultuid end as uid, s.exchange, s.symbol, s.longname, s.shortname, dtt.timezone, bmr.patternmovement, bmr.statisticalmovement, bmr.fromprice, bmr.toprice, bmr.percentile, bmr.patternlengthbars, case when rbr.age is not null then rbr.age when bmr.resultuid <= rm.resultuid then ? else ? end as age, case when rbr.relevant is not null then rbr.relevant when bmr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from bigmovement_results bmr inner join downloadersymbolsettings dss on bmr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on bmr.symbolid = s.symbolid inner join rar_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid left join currencypips cps on cps.symbol = s.symbol where (bmr.old_resultuid = ? or bmr.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Mar 15 09 2 0ms 0ms 4 0ms 2,419 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 #4
Day Hour Count Duration Avg duration Mar 15 09 2,419 0ms 0ms 5 0ms 165 0ms 0ms 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, timegranularity as interval, direction as direction, patternendtime as patternendtime, patternstartprice as psp, patternendprice as pep, target03 as t03, target16 as t16, patternlengthbars as length, p.patternname as patternname, dtt.timezone, cps.pip from fibonacci_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join fibonaccipatterns p on a.pattern = p.patternname left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Mar 15 09 165 0ms 0ms 6 0ms 238 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 #6
Day Hour Count Duration Avg duration Mar 15 09 238 0ms 0ms 7 0ms 36 0ms 0ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Mar 15 09 36 0ms 0ms 8 0ms 1 0ms 0ms 0ms insert into resultmedia (processresultsid, type, name, filename) values (?, ?, ?, ?) returning id;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Mar 15 09 1 0ms 0ms 9 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 #9
Day Hour Count Duration Avg duration Mar 15 09 18 0ms 0ms 10 0ms 238 0ms 0ms 0ms select v.datname, c.relname, v.phase, v.heap_blks_total, v.heap_blks_scanned, v.heap_blks_vacuumed, v.index_vacuum_count, v.max_dead_tuples, v.num_dead_tuples from pg_stat_progress_vacuum as v join pg_class c on c.oid = v.relid;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 15 09 238 0ms 0ms 11 0ms 231 0ms 0ms 0ms select distinct s.statsid as statsid, sy.exchange as name from stats s inner join broker b on s.brokerid = b.brokerid inner join brokerconfig bc on b.brokerid = bc.brokerid inner join stats_symbols ss on s.statsid = ss.statsid inner join downloadersymbolsettings dss on ss.symbolid = dss.symbolid inner join symbols sy on dss.symbolid = sy.symbolid where dss.enabled = ? and s.brokerid is not null and b.brokerid = ? and s.groupingtype ilike ? and s.description ilike ? || b.name || ? and s.description ilike ? || sy.exchange || ? and s.description not ilike ? || ? || ? union all select distinct s.statsid as statsid, basegroupname as name from stats s inner join broker b on s.brokerid = b.brokerid inner join brokerconfig bc on b.brokerid = bc.brokerid inner join stats_symbols ss on s.statsid = ss.statsid inner join downloadersymbolsettings dss on ss.symbolid = dss.symbolid inner join symbolgroup sg on dss.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bg.brokerid = b.brokerid where dss.enabled = ? and s.brokerid is not null and b.brokerid = ? and s.groupingtype not ilike ? and s.description ilike ? || b.name || ? and s.description ilike ? || g.basegroupname || ? and s.description not ilike ? || ? || ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Mar 15 09 231 0ms 0ms 12 0ms 419 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) and name in (...) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) and name in (...) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Mar 15 09 419 0ms 0ms 13 0ms 24 0ms 0ms 0ms select * from ( select pricedatetime, open, high, low, close, volume, bsf from t60 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Mar 15 09 24 0ms 0ms 14 0ms 332 0ms 0ms 0ms commit;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Mar 15 09 332 0ms 0ms 15 0ms 1 0ms 0ms 0ms select psd.symbolid, psd.hourlysymbolid as intervalsymbolid, s.symbol, dtt.timezone, dtt.absolutetimezoneoffset, psh.hour as index, psh.ave, psh.stddev, ((psh.ave - psh.stddev) / ?.?) as low, ((psh.ave + psh.stddev) / ?.?) as high, ee.timezone as exchangetimezone, ee.mon_t1start as exchangestart, ee.mon_t1end as exchangeend from powerstats_symboldata psd inner join powerstats_hourly psh on psd.hourlysymbolid = psh.symbolid inner join symbols s on psh.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join mat_ps_hourly_symbolid_max_enddate e on psh.enddate = e.enddate and psh.symbolid = e.symbolid inner join exchanges ee on ee.exchange = s.exchange where psd.symbolid = ? and dtt.dayofweek = ? order by hour asc;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Mar 15 09 1 0ms 0ms 16 0ms 107 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 #16
Day Hour Count Duration Avg duration Mar 15 09 107 0ms 0ms 17 0ms 238 0ms 0ms 0ms select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Mar 15 09 238 0ms 0ms 18 0ms 24 0ms 0ms 0ms select * from ( select pricedatetime, open, high, low, close, volume, bsf from t30 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Mar 15 09 24 0ms 0ms 19 0ms 6 0ms 0ms 0ms select pid, datname, client_addr from pg_stat_activity where query ilike ? and pid <> pg_backend_pid() and state = ? and datname = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Mar 15 09 6 0ms 0ms 20 0ms 7 0ms 0ms 0ms update executions set isrunning = false, has_results = false, response = ? where id = ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Mar 15 09 7 0ms 0ms Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 14,232 0ms 0ms 0ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 15 09 14,232 0ms 0ms 2 4,610 0ms 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Mar 15 09 4,610 0ms 0ms 3 2,902 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 #3
Day Hour Count Duration Avg duration Mar 15 09 2,902 0ms 0ms 4 2,671 0ms 0ms 0ms 0ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Mar 15 09 2,671 0ms 0ms 5 2,514 0ms 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Mar 15 09 2,514 0ms 0ms 6 2,452 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 #6
Day Hour Count Duration Avg duration Mar 15 09 2,452 0ms 0ms 7 2,419 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 #7
Day Hour Count Duration Avg duration Mar 15 09 2,419 0ms 0ms 8 1,872 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 #8
Day Hour Count Duration Avg duration Mar 15 09 1,872 0ms 0ms 9 1,798 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 #9
Day Hour Count Duration Avg duration Mar 15 09 1,798 0ms 0ms 10 968 0ms 0ms 0ms 0ms select datetimeupdate from latest_candle_datetime_per_receng where recognitionengine ilike ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 15 09 968 0ms 0ms 11 745 0ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Mar 15 09 745 0ms 0ms 12 733 0ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Mar 15 09 733 0ms 0ms 13 599 0ms 0ms 0ms 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars as length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternstartprice, resy1, supporty1, dtt.timezone, cps.pip, newlevels.profit from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern left join currencypips cps on cps.symbol = s.symbol left join lateral calc_cp_signal (a.resultuid) newlevels on true where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Mar 15 09 599 0ms 0ms 14 461 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 15 09 461 0ms 0ms 15 420 0ms 0ms 0ms 0ms select distinct category from ( select * from stats_hrsapproaches_summary where statsid = ?) as data;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Mar 15 09 420 0ms 0ms 16 420 0ms 0ms 0ms 0ms select absolutetimezoneoffset from symbols s inner join brokersymbollist bsl on s.symbolid = bsl.symbolid inner join downloadersymbolsettings dss on bsl.symbolid = dss.symbolid inner join datafeedstimetable df on dss.classname = df.classname where brokerid = ? and lower(exchange) = lower(?) group by absolutetimezoneoffset;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 15 09 420 0ms 0ms 17 420 0ms 0ms 0ms 0ms select distinct category from ( select * from stats_summary where statsid = ? union select * from stats_hrs_summary where statsid = ?) as data;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Mar 15 09 420 0ms 0ms 18 420 0ms 0ms 0ms 0ms select name from ( select * from ( select * from stats_summary ss where statsid = ? union select * from stats_hrs_summary where statsid = ?) as data where lower(category) = ? order by correct desc limit ?) a;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Mar 15 09 420 0ms 0ms 19 419 0ms 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) and name in (...) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) and name in (...) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Mar 15 09 419 0ms 0ms 20 419 0ms 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = ? and category = lower(?) and name in (...) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Mar 15 09 419 0ms 0ms Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 0ms 0ms 0ms 15 0ms select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Mar 15 09 15 0ms 0ms 2 0ms 0ms 0ms 69 0ms with rar_max as ( select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ? ), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Mar 15 09 69 0ms 0ms 3 0ms 0ms 0ms 2 0ms with rar_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ) select bmr.symbolid, patternstarttime, patternendtime, timegranularity, ? as direction, case when bmr.old_resultuid = ? then bmr.old_resultuid else bmr.resultuid end as uid, s.exchange, s.symbol, s.longname, s.shortname, dtt.timezone, bmr.patternmovement, bmr.statisticalmovement, bmr.fromprice, bmr.toprice, bmr.percentile, bmr.patternlengthbars, case when rbr.age is not null then rbr.age when bmr.resultuid <= rm.resultuid then ? else ? end as age, case when rbr.relevant is not null then rbr.relevant when bmr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from bigmovement_results bmr inner join downloadersymbolsettings dss on bmr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on bmr.symbolid = s.symbolid inner join rar_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid left join currencypips cps on cps.symbol = s.symbol where (bmr.old_resultuid = ? or bmr.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Mar 15 09 2 0ms 0ms 4 0ms 0ms 0ms 2,419 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Mar 15 09 2,419 0ms 0ms 5 0ms 0ms 0ms 165 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, timegranularity as interval, direction as direction, patternendtime as patternendtime, patternstartprice as psp, patternendprice as pep, target03 as t03, target16 as t16, patternlengthbars as length, p.patternname as patternname, dtt.timezone, cps.pip from fibonacci_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join fibonaccipatterns p on a.pattern = p.patternname left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Mar 15 09 165 0ms 0ms 6 0ms 0ms 0ms 238 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 #6
Day Hour Count Duration Avg duration Mar 15 09 238 0ms 0ms 7 0ms 0ms 0ms 36 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Mar 15 09 36 0ms 0ms 8 0ms 0ms 0ms 1 0ms insert into resultmedia (processresultsid, type, name, filename) values (?, ?, ?, ?) returning id;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Mar 15 09 1 0ms 0ms 9 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 #9
Day Hour Count Duration Avg duration Mar 15 09 18 0ms 0ms 10 0ms 0ms 0ms 238 0ms select v.datname, c.relname, v.phase, v.heap_blks_total, v.heap_blks_scanned, v.heap_blks_vacuumed, v.index_vacuum_count, v.max_dead_tuples, v.num_dead_tuples from pg_stat_progress_vacuum as v join pg_class c on c.oid = v.relid;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Mar 15 09 238 0ms 0ms 11 0ms 0ms 0ms 231 0ms select distinct s.statsid as statsid, sy.exchange as name from stats s inner join broker b on s.brokerid = b.brokerid inner join brokerconfig bc on b.brokerid = bc.brokerid inner join stats_symbols ss on s.statsid = ss.statsid inner join downloadersymbolsettings dss on ss.symbolid = dss.symbolid inner join symbols sy on dss.symbolid = sy.symbolid where dss.enabled = ? and s.brokerid is not null and b.brokerid = ? and s.groupingtype ilike ? and s.description ilike ? || b.name || ? and s.description ilike ? || sy.exchange || ? and s.description not ilike ? || ? || ? union all select distinct s.statsid as statsid, basegroupname as name from stats s inner join broker b on s.brokerid = b.brokerid inner join brokerconfig bc on b.brokerid = bc.brokerid inner join stats_symbols ss on s.statsid = ss.statsid inner join downloadersymbolsettings dss on ss.symbolid = dss.symbolid inner join symbolgroup sg on dss.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bg.brokerid = b.brokerid where dss.enabled = ? and s.brokerid is not null and b.brokerid = ? and s.groupingtype not ilike ? and s.description ilike ? || b.name || ? and s.description ilike ? || g.basegroupname || ? and s.description not ilike ? || ? || ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Mar 15 09 231 0ms 0ms 12 0ms 0ms 0ms 419 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) and name in (...) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) and name in (...) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Mar 15 09 419 0ms 0ms 13 0ms 0ms 0ms 24 0ms select * from ( select pricedatetime, open, high, low, close, volume, bsf from t60 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Mar 15 09 24 0ms 0ms 14 0ms 0ms 0ms 332 0ms commit;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Mar 15 09 332 0ms 0ms 15 0ms 0ms 0ms 1 0ms select psd.symbolid, psd.hourlysymbolid as intervalsymbolid, s.symbol, dtt.timezone, dtt.absolutetimezoneoffset, psh.hour as index, psh.ave, psh.stddev, ((psh.ave - psh.stddev) / ?.?) as low, ((psh.ave + psh.stddev) / ?.?) as high, ee.timezone as exchangetimezone, ee.mon_t1start as exchangestart, ee.mon_t1end as exchangeend from powerstats_symboldata psd inner join powerstats_hourly psh on psd.hourlysymbolid = psh.symbolid inner join symbols s on psh.symbolid = s.symbolid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join mat_ps_hourly_symbolid_max_enddate e on psh.enddate = e.enddate and psh.symbolid = e.symbolid inner join exchanges ee on ee.exchange = s.exchange where psd.symbolid = ? and dtt.dayofweek = ? order by hour asc;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Mar 15 09 1 0ms 0ms 16 0ms 0ms 0ms 107 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Mar 15 09 107 0ms 0ms 17 0ms 0ms 0ms 238 0ms select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Mar 15 09 238 0ms 0ms 18 0ms 0ms 0ms 24 0ms select * from ( select pricedatetime, open, high, low, close, volume, bsf from t30 where symbolid = ? and (bsf = ? or bsf is null) order by pricedatetime desc limit ?) a order by pricedatetime asc;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Mar 15 09 24 0ms 0ms 19 0ms 0ms 0ms 6 0ms select pid, datname, client_addr from pg_stat_activity where query ilike ? and pid <> pg_backend_pid() and state = ? and datname = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Mar 15 09 6 0ms 0ms 20 0ms 0ms 0ms 7 0ms update executions set isrunning = false, has_results = false, response = ? where id = ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Mar 15 09 7 0ms 0ms Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 871ms 566 0ms 3ms 1ms SELECT symbolid, ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Mar 15 09 566 871ms 1ms -
SELECT symbolid, ;
Date: 2026-03-15 09:05:36 Duration: 3ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-03-15 09:17:51 Duration: 2ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-03-15 09:32:28 Duration: 2ms Database: postgres
2 292ms 335 0ms 5ms 0ms WITH rar_max as ( ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 09 335 292ms 0ms -
WITH rar_max as ( ;
Date: 2026-03-15 09:20:32 Duration: 5ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-03-15 09:20:18 Duration: 5ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-03-15 09:10:47 Duration: 4ms Database: postgres
3 240ms 2,320 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 #3
Day Hour Count Duration Avg duration 09 2,320 240ms 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: 2026-03-15 09:01:31 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: 2026-03-15 09:10:57 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: 2026-03-15 09:10:33 Duration: 0ms Database: postgres
4 199ms 2,417 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 #4
Day Hour Count Duration Avg duration 09 2,417 199ms 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: 2026-03-15 09:02:21 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: 2026-03-15 09:11:58 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: 2026-03-15 09:41:57 Duration: 0ms Database: postgres
5 135ms 480 0ms 2ms 0ms SELECT ;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 09 480 135ms 0ms -
SELECT ;
Date: 2026-03-15 09:26:00 Duration: 2ms Database: postgres
-
SELECT ;
Date: 2026-03-15 09:02:07 Duration: 2ms Database: postgres
-
SELECT ;
Date: 2026-03-15 09:45:03 Duration: 2ms Database: postgres
6 128ms 116 0ms 1ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #6
Day Hour Count Duration Avg duration 09 116 128ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-15 09:32:32 Duration: 1ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-15 09:46:01 Duration: 1ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-15 09:30:28 Duration: 1ms Database: postgres
7 107ms 666 0ms 2ms 0ms select category, ;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 09 666 107ms 0ms -
select category, ;
Date: 2026-03-15 09:10:51 Duration: 2ms Database: postgres
-
select category, ;
Date: 2026-03-15 09:10:51 Duration: 2ms Database: postgres
-
select category, ;
Date: 2026-03-15 09:10:51 Duration: 0ms Database: postgres
8 104ms 745 0ms 0ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #8
Day Hour Count Duration Avg duration 09 745 104ms 0ms -
SET extra_float_digits = 3;
Date: 2026-03-15 09:32:28 Duration: 0ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-03-15 09:15:50 Duration: 0ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-03-15 09:06:50 Duration: 0ms Database: postgres
9 98ms 518 0ms 0ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 09 518 98ms 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: 2026-03-15 09:17:36 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: 2026-03-15 09:46:36 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: 2026-03-15 09:32:36 Duration: 0ms Database: postgres
10 43ms 18 1ms 2ms 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 #10
Day Hour Count Duration Avg duration 09 18 43ms 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: 2026-03-15 09:41:03 Duration: 2ms Database: postgres
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-03-15 09:51:01 Duration: 2ms Database: postgres
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-03-15 09:11:01 Duration: 2ms Database: postgres
11 36ms 288 0ms 0ms 0ms INSERT INTO T1440_underlying (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 09 288 36ms 0ms -
INSERT INTO T1440_underlying (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-15 09:32:22 Duration: 0ms Database: postgres
-
INSERT INTO T1440_underlying (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-15 09:32:36 Duration: 0ms Database: postgres
-
INSERT INTO T1440_underlying (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-15 09:16:38 Duration: 0ms Database: postgres
12 29ms 288 0ms 0ms 0ms INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 09 288 29ms 0ms -
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-15 09:32:32 Duration: 0ms Database: postgres
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-15 09:47:36 Duration: 0ms Database: postgres
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-15 09:30:35 Duration: 0ms Database: postgres
13 23ms 24 0ms 1ms 0ms 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 #13
Day Hour Count Duration Avg duration 09 24 23ms 0ms -
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: 2026-03-15 09:03:37 Duration: 1ms Database: postgres
-
select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2026-03-15 09:53:51 Duration: 1ms Database: postgres
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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: 2026-03-15 09:53:51 Duration: 1ms Database: postgres
14 21ms 40 0ms 1ms 0ms select distinct s.statsid as statsid, sy.exchange as name;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 09 40 21ms 0ms -
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-03-15 09:36:46 Duration: 1ms Database: postgres
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-03-15 09:00:45 Duration: 1ms Database: postgres
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-03-15 09:00:45 Duration: 1ms Database: postgres
15 20ms 9 1ms 4ms 2ms with wh_patitioned as ( ;Times Reported Time consuming prepare #15
Day Hour Count Duration Avg duration 09 9 20ms 2ms -
with wh_patitioned as ( ;
Date: 2026-03-15 09:15:03 Duration: 4ms Database: postgres
-
with wh_patitioned as ( ;
Date: 2026-03-15 09:05:03 Duration: 4ms Database: postgres
-
with wh_patitioned as ( ;
Date: 2026-03-15 09:30:02 Duration: 2ms Database: postgres
16 18ms 24 0ms 1ms 0ms select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 09 24 18ms 0ms -
select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2026-03-15 09:53:51 Duration: 1ms Database: postgres
-
select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2026-03-15 09:03:37 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: 2026-03-15 09:53:51 Duration: 1ms Database: postgres
17 18ms 13 0ms 5ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 09 13 18ms 1ms -
WITH last_candle AS ( ;
Date: 2026-03-15 09:15:05 Duration: 5ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-03-15 09:15:03 Duration: 3ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-03-15 09:52:00 Duration: 2ms Database: postgres
18 15ms 6 2ms 3ms 2ms select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 09 6 15ms 2ms -
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2026-03-15 09:30:05 Duration: 3ms Database: postgres
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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: 2026-03-15 09:00:04 Duration: 3ms Database: postgres
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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: 2026-03-15 09:10:05 Duration: 2ms Database: postgres
19 11ms 175 0ms 1ms 0ms select 1;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 09 175 11ms 0ms -
select 1;
Date: 2026-03-15 09:30:02 Duration: 1ms Database: postgres
-
select 1;
Date: 2026-03-15 09:45:05 Duration: 0ms Database: postgres
-
select 1;
Date: 2026-03-15 09:32:34 Duration: 0ms Database: postgres
20 8ms 40 0ms 0ms 0ms select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 09 40 8ms 0ms -
select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;
Date: 2026-03-15 09:36:46 Duration: 0ms Database: postgres
-
select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;
Date: 2026-03-15 09:00:45 Duration: 0ms Database: postgres
-
select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;
Date: 2026-03-15 09:10:45 Duration: 0ms Database: postgres
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 7s206ms 515 0ms 35ms 13ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Mar 15 09 515 7s206ms 13ms -
WITH rar_max as ( ;
Date: 2026-03-15 09:20:32 Duration: 35ms 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 = '80', $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 = '0', $95 = '', $96 = '0', $97 = '0', $98 = '0', $99 = '0', $100 = '0', $101 = 't', $102 = '10', $103 = '10'
-
WITH rar_max as ( ;
Date: 2026-03-15 09:50:58 Duration: 31ms 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 = '0', $177 = '0', $178 = '0', $179 = '700', $180 = '700', $181 = 't', $182 = '10', $183 = '10'
-
WITH rar_max as ( ;
Date: 2026-03-15 09:35:43 Duration: 29ms 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 = '80', $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 = '0', $95 = '', $96 = '0', $97 = '0', $98 = '0', $99 = '0', $100 = '0', $101 = 't', $102 = '10', $103 = '10'
2 1s778ms 5,128 0ms 6ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 09 5,128 1s778ms 0ms -
SELECT ;
Date: 2026-03-15 09:31:46 Duration: 6ms Database: postgres parameters: $1 = '515840243198780300'
-
SELECT ;
Date: 2026-03-15 09:26:00 Duration: 6ms Database: postgres parameters: $1 = '607840747110274302', $2 = '607840747110274302', $3 = '607840747110274302'
-
SELECT ;
Date: 2026-03-15 09:31:46 Duration: 5ms Database: postgres parameters: $1 = '515840243198780300'
3 1s507ms 566 1ms 5ms 2ms SELECT symbolid, ;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 09 566 1s507ms 2ms -
SELECT symbolid, ;
Date: 2026-03-15 09:32:21 Duration: 5ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'GBPUSD.ID', $4 = 'NZDUSD', $5 = 'NZDCAD.FX', $6 = 'NASDAQ100', $7 = 'NZDUSD.ID', $8 = 'NZDJPY', $9 = 'NZDJPY.FX', $10 = 'NZDUSD.FX', $11 = 'NZDJPY.ID'
-
SELECT symbolid, ;
Date: 2026-03-15 09:32:21 Duration: 4ms Database: postgres parameters: $1 = 'ATFX', $2 = '15', $3 = 'SPX500', $4 = 'US30'
-
SELECT symbolid, ;
Date: 2026-03-15 09:15:51 Duration: 4ms Database: postgres parameters: $1 = 'PEPPERSTONEMT5', $2 = '15', $3 = 'ABNB.US', $4 = 'AAPL.US'
4 1s62ms 231 0ms 21ms 4ms select distinct s.statsid as statsid, sy.exchange as name;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 09 231 1s62ms 4ms -
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-03-15 09:00:45 Duration: 21ms Database: postgres parameters: $1 = '1436', $2 = '1436'
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-03-15 09:00:45 Duration: 21ms Database: postgres parameters: $1 = '1436', $2 = '1436'
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-03-15 09:10:46 Duration: 20ms Database: postgres parameters: $1 = '1504', $2 = '1504'
5 649ms 7,962 0ms 4ms 0ms select category, ;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 09 7,962 649ms 0ms -
select category, ;
Date: 2026-03-15 09:10:51 Duration: 4ms Database: postgres parameters: $1 = '515852059309933307', $2 = 'symbol', $3 = 'NZDJPY', $4 = 'XAUUSD', $5 = 'GBPJPY', $6 = 'USDJPY', $7 = 'XAGUSD', $8 = 'CHFJPY', $9 = 'CADJPY', $10 = 'EURJPY', $11 = 'GBPNZD', $12 = 'EURNZD', $13 = 'USDCAD', $14 = 'EURCHF', $15 = 'GBPCAD', $16 = 'CADJPY', $17 = 'EURCAD', $18 = 'CADCHF', $19 = 'GBPUSD', $20 = 'EURNZD', $21 = 'EURCAD', $22 = 'GBPCAD', $23 = 'NZDJPY', $24 = 'GBPCHF', $25 = 'GBPCHF', $26 = 'NZDUSD', $27 = 'EURUSD', $28 = 'GBPUSD', $29 = 'XAUUSD', $30 = 'USDJPY', $31 = 'GBPJPY', $32 = 'EURJPY', $33 = 'CHFJPY', $34 = 'XAGUSD', $35 = 'USDCHF', $36 = 'GBPNZD', $37 = 'USDCAD', $38 = 'AUDUSD', $39 = 'EURUSD', $40 = 'AUDUSD', $41 = 'USDCHF', $42 = 'NZDUSD', $43 = 'EURCHF', $44 = 'CADCHF'
-
select category, ;
Date: 2026-03-15 09:10:51 Duration: 3ms Database: postgres parameters: $1 = '515852059310228307', $2 = 'quality', $3 = '515852059310228307', $4 = 'quality'
-
select category, ;
Date: 2026-03-15 09:00:50 Duration: 2ms Database: postgres parameters: $1 = '515852059324351307', $2 = 'symbol', $3 = 'NGAS', $4 = 'DOW', $5 = 'XAUUSD', $6 = 'SP', $7 = 'NIKKEI', $8 = 'CL', $9 = 'XAGUSD', $10 = 'NSDQ', $11 = 'ASX', $12 = 'DAX', $13 = 'XPTUSD', $14 = 'XPDUSD', $15 = 'FTSE', $16 = 'CAC', $17 = 'NGAS', $18 = 'ASX', $19 = 'CL', $20 = 'XPDUSD', $21 = 'NIKKEI', $22 = 'XAGUSD', $23 = 'FTSE', $24 = 'XAUUSD', $25 = 'DOW', $26 = 'SP', $27 = 'NSDQ', $28 = 'XPTUSD', $29 = 'DAX', $30 = 'CAC', $31 = '515852059324351307', $32 = 'symbol', $33 = 'NGAS', $34 = 'DOW', $35 = 'XAUUSD', $36 = 'SP', $37 = 'NIKKEI', $38 = 'CL', $39 = 'XAGUSD', $40 = 'NSDQ', $41 = 'ASX', $42 = 'DAX', $43 = 'XPTUSD', $44 = 'XPDUSD', $45 = 'FTSE', $46 = 'CAC', $47 = 'NGAS', $48 = 'ASX', $49 = 'CL', $50 = 'XPDUSD', $51 = 'NIKKEI', $52 = 'XAGUSD', $53 = 'FTSE', $54 = 'XAUUSD', $55 = 'DOW', $56 = 'SP', $57 = 'NSDQ', $58 = 'XPTUSD', $59 = 'DAX', $60 = 'CAC'
6 300ms 420 0ms 2ms 0ms SELECT absolutetimezoneoffset;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 09 420 300ms 0ms -
SELECT absolutetimezoneoffset;
Date: 2026-03-15 09:00:51 Duration: 2ms Database: postgres parameters: $1 = '632', $2 = 'Forex'
-
SELECT absolutetimezoneoffset;
Date: 2026-03-15 09:45:50 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'BROKER'
-
SELECT absolutetimezoneoffset;
Date: 2026-03-15 09:10:48 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'BROKER'
7 294ms 10 23ms 35ms 29ms with wh_patitioned as ( ;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 09 10 294ms 29ms -
with wh_patitioned as ( ;
Date: 2026-03-15 09:05:03 Duration: 35ms 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: 2026-03-15 09:15:03 Duration: 35ms 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: 2026-03-15 09:07:35 Duration: 33ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
8 227ms 14,131 0ms 7ms 0ms select 1;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 09 14,131 227ms 0ms -
select 1;
Date: 2026-03-15 09:50:57 Duration: 7ms Database: postgres
-
select 1;
Date: 2026-03-15 09:41:06 Duration: 6ms Database: postgres
-
select 1;
Date: 2026-03-15 09:36:00 Duration: 6ms Database: postgres
9 219ms 29 4ms 15ms 7ms WITH last_candle AS ( ;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 09 29 219ms 7ms -
WITH last_candle AS ( ;
Date: 2026-03-15 09:36:00 Duration: 15ms Database: postgres parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2026-03-15 09:08:08 Duration: 14ms Database: postgres parameters: $1 = '667', $2 = '667'
-
WITH last_candle AS ( ;
Date: 2026-03-15 09:15:05 Duration: 14ms Database: postgres parameters: $1 = '558', $2 = '558'
10 213ms 116 1ms 2ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 09 116 213ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-15 09:46:01 Duration: 2ms Database: postgres parameters: $1 = 'ICMARKETS'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-15 09:32:32 Duration: 2ms Database: postgres parameters: $1 = 'GLOBALGTMT5'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-03-15 09:30:28 Duration: 2ms Database: postgres parameters: $1 = 'FPMARKETS'
11 190ms 2,419 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 #11
Day Hour Count Duration Avg duration 09 2,419 190ms 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: 2026-03-15 09:32:36 Duration: 1ms Database: postgres parameters: $1 = '2026-03-13 23:00:00', $2 = '46566.2', $3 = '46570.25', $4 = '46474.7', $5 = '46474.7', $6 = '4279', $7 = '515840249388246300', $8 = '0', $9 = '2026-03-15 09:32:36.807', $10 = '2026-03-15 09:32:36.733', $11 = '46566.2', $12 = '46570.25', $13 = '46474.7', $14 = '46474.7', $15 = '4279', $16 = '0', $17 = '2026-03-15 09:32:36.807', $18 = '2026-03-15 09:32:36.733'
-
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: 2026-03-15 09:50:06 Duration: 0ms Database: postgres parameters: $1 = '2026-03-13 22:00:00', $2 = '81.042', $3 = '81.107', $4 = '79.873', $5 = '80.2835', $6 = '18604', $7 = '515840230625682300', $8 = '0', $9 = '2026-03-15 09:50:06.779', $10 = '2026-03-15 09:50:06.778', $11 = '81.042', $12 = '81.107', $13 = '79.873', $14 = '80.2835', $15 = '18604', $16 = '0', $17 = '2026-03-15 09:50:06.779', $18 = '2026-03-15 09:50:06.778'
-
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: 2026-03-15 09:01:31 Duration: 0ms Database: postgres parameters: $1 = '2026-03-13 20:00:00', $2 = '105.84', $3 = '106.28', $4 = '105.49', $5 = '105.58', $6 = '4005', $7 = '515840247879403300', $8 = '0', $9 = '2026-03-15 09:01:31.769', $10 = '2026-03-15 09:01:31.704', $11 = '105.84', $12 = '106.28', $13 = '105.49', $14 = '105.58', $15 = '4005', $16 = '0', $17 = '2026-03-15 09:01:31.769', $18 = '2026-03-15 09:01:31.704'
12 164ms 2,452 0ms 1ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 09 2,452 164ms 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: 2026-03-15 09:31:21 Duration: 1ms Database: postgres parameters: $1 = '2026-03-13 22:30:00', $2 = '0.57897', $3 = '0.57912', $4 = '0.57844', $5 = '0.57848', $6 = '909', $7 = '515840230540903300', $8 = '0', $9 = '2026-03-15 09:31:21.763', $10 = '2026-03-15 09:31:21.659', $11 = '0.57897', $12 = '0.57912', $13 = '0.57844', $14 = '0.57848', $15 = '909', $16 = '0', $17 = '2026-03-15 09:31:21.763', $18 = '2026-03-15 09:31:21.659'
-
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: 2026-03-15 09:11:58 Duration: 0ms Database: postgres parameters: $1 = '2026-03-13 18:00:00', $2 = '25438.9', $3 = '25523.8', $4 = '25413.8', $5 = '25473.3', $6 = '11496', $7 = '515840247933633300', $8 = '0', $9 = '2026-03-15 09:11:58.147', $10 = '2026-03-15 09:11:58.051', $11 = '25438.9', $12 = '25523.8', $13 = '25413.8', $14 = '25473.3', $15 = '11496', $16 = '0', $17 = '2026-03-15 09:11:58.147', $18 = '2026-03-15 09:11:58.051'
-
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: 2026-03-15 09:02:58 Duration: 0ms Database: postgres parameters: $1 = '2026-03-13 18:00:00', $2 = '25438.9', $3 = '25523.8', $4 = '25413.8', $5 = '25473.3', $6 = '11496', $7 = '515840247933633300', $8 = '0', $9 = '2026-03-15 09:02:58.532', $10 = '2026-03-15 09:02:58.452', $11 = '25438.9', $12 = '25523.8', $13 = '25413.8', $14 = '25473.3', $15 = '11496', $16 = '0', $17 = '2026-03-15 09:02:58.532', $18 = '2026-03-15 09:02:58.452'
13 126ms 2,902 0ms 0ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 09 2,902 126ms 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: 2026-03-15 09:17:36 Duration: 0ms Database: postgres parameters: $1 = '2026-03-13 23:30:00', $2 = '2018.19', $3 = '2025.01', $4 = '2015.81', $5 = '2023.5', $6 = '1591', $7 = '500991628263605200', $8 = '0', $9 = '2026-03-15 09:17:36.156', $10 = '2026-03-15 09:17:36.087', $11 = '2018.19', $12 = '2025.01', $13 = '2015.81', $14 = '2023.5', $15 = '1591', $16 = '0', $17 = '2026-03-15 09:17:36.156', $18 = '2026-03-15 09:17:36.087'
-
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: 2026-03-15 09:46:36 Duration: 0ms Database: postgres parameters: $1 = '2026-03-13 23:30:00', $2 = '2018.19', $3 = '2025.01', $4 = '2015.81', $5 = '2023.5', $6 = '1591', $7 = '500991628263605200', $8 = '0', $9 = '2026-03-15 09:46:36', $10 = '2026-03-15 09:46:35.934', $11 = '2018.19', $12 = '2025.01', $13 = '2015.81', $14 = '2023.5', $15 = '1591', $16 = '0', $17 = '2026-03-15 09:46:36', $18 = '2026-03-15 09:46:35.934'
-
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: 2026-03-15 09:01:32 Duration: 0ms Database: postgres parameters: $1 = '2026-03-13 22:00:00', $2 = '44307.51', $3 = '44310.01', $4 = '44277.49', $5 = '44287.51', $6 = '724', $7 = '500991628285199200', $8 = '0', $9 = '2026-03-15 09:01:32.564', $10 = '2026-03-15 09:01:32.499', $11 = '44307.51', $12 = '44310.01', $13 = '44277.49', $14 = '44287.51', $15 = '724', $16 = '0', $17 = '2026-03-15 09:01:32.564', $18 = '2026-03-15 09:01:32.499'
14 44ms 420 0ms 3ms 0ms SELECT name;Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 09 420 44ms 0ms -
SELECT name;
Date: 2026-03-15 09:00:46 Duration: 3ms Database: postgres parameters: $1 = '515852059317765307', $2 = '515852059317765307'
-
SELECT name;
Date: 2026-03-15 09:53:25 Duration: 0ms Database: postgres parameters: $1 = '515852059324253307', $2 = '515852059324253307'
-
SELECT name;
Date: 2026-03-15 09:38:59 Duration: 0ms Database: postgres parameters: $1 = '515852059317765307', $2 = '515852059317765307'
15 44ms 840 0ms 1ms 0ms select distinct category;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 09 840 44ms 0ms -
select distinct category;
Date: 2026-03-15 09:00:46 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307'
-
select distinct category;
Date: 2026-03-15 09:00:46 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307'
-
select distinct category;
Date: 2026-03-15 09:45:51 Duration: 0ms Database: postgres parameters: $1 = '515852059305993307', $2 = '515852059305993307'
16 41ms 5 0ms 18ms 8ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 09 5 41ms 8ms -
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-03-15 09:04:26 Duration: 18ms 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: 2026-03-15 09:08:27 Duration: 11ms 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: 2026-03-15 09:06:33 Duration: 10ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
17 33ms 288 0ms 0ms 0ms INSERT INTO T1440_underlying (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 09 288 33ms 0ms -
INSERT INTO T1440_underlying (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-15 09:46:35 Duration: 0ms Database: postgres parameters: $1 = '2026-03-13 00:00:00', $2 = '101.775', $3 = '103.925', $4 = '97.815', $5 = '103.815', $6 = '62052', $7 = '515840249390663300', $8 = '0', $9 = '2026-03-15 09:46:35.814', $10 = '2026-03-15 09:46:35.814', $11 = '101.775', $12 = '103.925', $13 = '97.815', $14 = '103.815', $15 = '62052', $16 = '0', $17 = '2026-03-15 09:46:35.814', $18 = '2026-03-15 09:46:35.814'
-
INSERT INTO T1440_underlying (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-15 09:32:36 Duration: 0ms Database: postgres parameters: $1 = '2026-03-13 00:00:00', $2 = '46744.65', $3 = '47123.25', $4 = '46421.75', $5 = '46474.7', $6 = '238469', $7 = '515840249388574300', $8 = '0', $9 = '2026-03-15 09:32:36.791', $10 = '2026-03-15 09:32:36.791', $11 = '46744.65', $12 = '47123.25', $13 = '46421.75', $14 = '46474.7', $15 = '238469', $16 = '0', $17 = '2026-03-15 09:32:36.791', $18 = '2026-03-15 09:32:36.791'
-
INSERT INTO T1440_underlying (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-15 09:16:38 Duration: 0ms Database: postgres parameters: $1 = '2026-03-13 00:00:00', $2 = '83.714', $3 = '85.4695', $4 = '79.439', $5 = '80.559', $6 = '331462', $7 = '515840249469364300', $8 = '0', $9 = '2026-03-15 09:16:38.68', $10 = '2026-03-15 09:16:38.679', $11 = '83.714', $12 = '85.4695', $13 = '79.439', $14 = '80.559', $15 = '331462', $16 = '0', $17 = '2026-03-15 09:16:38.68', $18 = '2026-03-15 09:16:38.679'
18 27ms 288 0ms 0ms 0ms INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 09 288 27ms 0ms -
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-15 09:15:26 Duration: 0ms Database: postgres parameters: $1 = '2026-03-13 20:00:00', $2 = '1215361.365', $3 = '1220662.695', $4 = '1197610.785', $5 = '1208363.04', $6 = '49905', $7 = '515840249474385300', $8 = '0', $9 = '2026-03-15 09:15:26.302', $10 = '2026-03-15 09:15:26.187', $11 = '1215361.365', $12 = '1220662.695', $13 = '1197610.785', $14 = '1208363.04', $15 = '49905', $16 = '0', $17 = '2026-03-15 09:15:26.302', $18 = '2026-03-15 09:15:26.187'
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-15 09:32:32 Duration: 0ms Database: postgres parameters: $1 = '2026-03-13 20:00:00', $2 = '0.58011', $3 = '0.58059', $4 = '0.577325', $5 = '0.57745', $6 = '9139', $7 = '515840249465227300', $8 = '0', $9 = '2026-03-15 09:32:32.823', $10 = '2026-03-15 09:32:32.757', $11 = '0.58011', $12 = '0.58059', $13 = '0.577325', $14 = '0.57745', $15 = '9139', $16 = '0', $17 = '2026-03-15 09:32:32.823', $18 = '2026-03-15 09:32:32.757'
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INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-03-15 09:45:37 Duration: 0ms Database: postgres parameters: $1 = '2026-03-13 20:00:00', $2 = '46630.75', $3 = '46743.25', $4 = '46474.7', $5 = '46474.7', $6 = '50664', $7 = '515840249388410300', $8 = '0', $9 = '2026-03-15 09:45:37.554', $10 = '2026-03-15 09:45:37.433', $11 = '46630.75', $12 = '46743.25', $13 = '46474.7', $14 = '46474.7', $15 = '50664', $16 = '0', $17 = '2026-03-15 09:45:37.554', $18 = '2026-03-15 09:45:37.433'
19 26ms 231 0ms 3ms 0ms select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 09 231 26ms 0ms -
select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;
Date: 2026-03-15 09:00:45 Duration: 3ms Database: postgres parameters: $1 = '1436'
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select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;
Date: 2026-03-15 09:00:45 Duration: 1ms Database: postgres parameters: $1 = '1436'
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select coalesce(min(calcfrom), current_timestamp - interval '12 months') as from_date, ;
Date: 2026-03-15 09:36:46 Duration: 1ms Database: postgres parameters: $1 = '1436'
20 22ms 60 0ms 4ms 0ms /*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 09 60 22ms 0ms -
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2026-03-15 09:50:35 Duration: 4ms Database: postgres parameters: $1 = '607832199572033301'
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2026-03-15 09:41:24 Duration: 3ms Database: postgres parameters: $1 = '607831489497729301'
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2026-03-15 09:50:34 Duration: 2ms Database: postgres parameters: $1 = '607832608077176301'
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Events
Log levels
Key values
- 224,101 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 238 ERROR entries
- 0 WARNING entries
Most Frequent Errors/Events
Key values
- 237 Max number of times the same event was reported
- 238 Total events found
Rank Times reported Error 1 237 ERROR: canceling statement due to statement timeout
Times Reported Most Frequent Error / Event #1
Day Hour Count Mar 15 09 237 - 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: 2026-03-15 09:00:12
2 1 ERROR: relation "..." does not exist
Times Reported Most Frequent Error / Event #2
Day Hour Count Mar 15 09 1 - ERROR: relation "t0" does not exist at character 83
Statement: SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T0 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050 ) a ORDER BY PriceDateTime ASC
Date: 2026-03-15 09:42:11