-
Global information
- Generated on Wed Dec 24 00:00:05 2025
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2025-12-24_010000.log
- Parsed 2,844,045 log entries in 1m4s
- Log start from 2025-12-24 01:00:00 to 2025-12-24 02:00:00
-
Overview
Global Stats
- 225 Number of unique normalized queries
- 283,898 Number of queries
- 2h45m55s Total query duration
- 2025-12-24 01:00:00 First query
- 2025-12-24 02:00:00 Last query
- 1,576 queries/s at 2025-12-24 01:30:04 Query peak
- 2h45m55s Total query duration
- 17s711ms Prepare/parse total duration
- 1m23s Bind total duration
- 2h44m14s Execute total duration
- 0 Number of events
- 0 Number of unique normalized events
- 0 Max number of times the same event was reported
- 0 Number of cancellation
- 47 Total number of automatic vacuums
- 60 Total number of automatic analyzes
- 742 Number temporary file
- 171.23 MiB Max size of temporary file
- 7.04 MiB Average size of temporary file
- 7,142 Total number of sessions
- 13 sessions at 2025-12-24 01:48:24 Session peak
- 1d15h53m54s Total duration of sessions
- 20s111ms Average duration of sessions
- 39 Average queries per session
- 1s393ms Average queries duration per session
- 18s717ms Average idle time per session
- 7,141 Total number of connections
- 109 connections/s at 2025-12-24 01:32:40 Connection peak
- 3 Total number of databases
SQL Traffic
Key values
- 1,576 queries/s Query Peak
- 2025-12-24 01:30:04 Date
SELECT Traffic
Key values
- 759 queries/s Query Peak
- 2025-12-24 01:45:04 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 190 queries/s Query Peak
- 2025-12-24 01:00:59 Date
Queries duration
Key values
- 2h45m55s 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) Dec 24 01 283,896 0ms 57s862ms 34ms 4m59s 5m26s 7m7s 02 2 9ms 9ms 4ms 9ms 9ms 9ms Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Dec 24 01 84,470 26 0ms 0ms 0ms 0ms 02 1 0 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Dec 24 01 32,272 2,196 16 96 0ms 0ms 0ms 0ms 02 0 0 0 0 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Dec 24 01 44,567 111,216 2.50 34.49% 02 0 1 1.00 0.00% Day Hour Count Average / Second Dec 24 01 7,141 1.98/s 02 0 0.00/s Day Hour Count Average Duration Average idle time Dec 24 01 7,142 20s111ms 18s731ms 02 0 0ms 0ms -
Connections
Established Connections
Key values
- 109 connections Connection Peak
- 2025-12-24 01:32:40 Date
Connections per database
Key values
- acaweb_fx Main Database
- 7,141 connections Total
Connections per user
Key values
- postgres Main User
- 7,141 connections Total
Connections per host
Key values
- 192.168.0.74 Main host with 3806 connections
- 7,141 Total connections
Host Count 127.0.0.1 113 192.168.0.114 5 192.168.0.216 103 192.168.0.74 3,806 192.168.1.145 6 192.168.1.15 1,117 192.168.1.20 25 192.168.1.239 2 192.168.1.90 50 192.168.2.126 60 192.168.2.182 12 192.168.2.82 48 192.168.3.199 36 192.168.4.142 1,025 192.168.4.150 10 192.168.4.169 1 192.168.4.222 1 192.168.4.238 16 192.168.4.33 97 192.168.4.94 4 192.168.4.98 330 [local] 274 -
Sessions
Simultaneous sessions
Key values
- 13 sessions Session Peak
- 2025-12-24 01:48:24 Date
Histogram of session times
Key values
- 6,119 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 7,142 sessions Total
Sessions per user
Key values
- postgres Main User
- 7,142 sessions Total
Sessions per host
Key values
- 192.168.0.74 Main Host
- 7,142 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 113 8s370ms 74ms 192.168.0.114 5 25m 5m 192.168.0.216 103 2m13s 1s293ms 192.168.0.74 3,806 2h6m59s 2s2ms 192.168.1.145 6 3h30m44s 35m7s 192.168.1.15 1,118 2h35m4s 8s322ms 192.168.1.20 25 10h53m16s 26m7s 192.168.1.239 2 12ms 6ms 192.168.1.90 50 33s287ms 665ms 192.168.2.126 60 6s677ms 111ms 192.168.2.182 12 867ms 72ms 192.168.2.82 48 20s633ms 429ms 192.168.3.199 36 1s634ms 45ms 192.168.4.142 1,025 12m23s 725ms 192.168.4.150 10 20h11s 2h1s 192.168.4.169 1 180ms 180ms 192.168.4.222 1 56s738ms 56s738ms 192.168.4.238 16 21s683ms 1s355ms 192.168.4.33 97 1m25s 880ms 192.168.4.94 4 34ms 8ms 192.168.4.98 330 15s181ms 46ms [local] 274 3m49s 837ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 13,041 buffers Checkpoint Peak
- 2025-12-24 01:06:26 Date
- 209.929 seconds Highest write time
- 0.022 seconds Sync time
Checkpoints Wal files
Key values
- 5 files Wal files usage Peak
- 2025-12-24 01:06:26 Date
Checkpoints distance
Key values
- 175.28 Mo Distance Peak
- 2025-12-24 01:06:26 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Dec 24 01 52,014 1,900.375s 0.079s 1,900.781s 02 0 0s 0s 0s Day Hour Added Removed Recycled Synced files Longest sync Average sync Dec 24 01 0 0 25 1,977 0.005s 0s 02 0 0 0 0 0s 0s Day Hour Count Avg time (sec) Dec 24 01 0 0s 02 0 0s Day Hour Mean distance Mean estimate Dec 24 01 33,979.58 kB 66,063.83 kB 02 0.00 kB 0.00 kB -
Temporary Files
Size of temporary files
Key values
- 184.92 MiB Temp Files size Peak
- 2025-12-24 01:20:07 Date
Number of temporary files
Key values
- 30 per second Temp Files Peak
- 2025-12-24 01:02:17 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Dec 24 01 742 5.10 GiB 7.04 MiB 02 0 0 0 Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 46 150.23 MiB 3.20 MiB 3.32 MiB 3.27 MiB select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ?), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?)), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;-
SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ($2 = 0 OR s.timegranularity in ($3, $4, $5, $6, $7, $8, $9)) AND ($10 = 0 OR s.exchange in ($11)) AND ($12 = 0 OR coalesce(bim.code, s.symbol) in ($13, $14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226, $227, $228, $229, $230, $231, $232, $233, $234, $235, $236, $237, $238, $239, $240, $241, $242, $243, $244, $245, $246, $247, $248, $249, $250, $251, $252, $253, $254, $255, $256, $257, $258, $259, $260, $261, $262, $263, $264, $265, $266, $267, $268, $269, $270, $271, $272, $273, $274, $275, $276, $277, $278, $279, $280, $281, $282, $283, $284, $285, $286, $287, $288, $289, $290, $291, $292, $293, $294, $295, $296, $297, $298, $299, $300, $301, $302, $303, $304, $305, $306, $307, $308, $309, $310, $311, $312, $313, $314, $315, $316, $317, $318, $319, $320, $321, $322)) AND ($323 = 0 OR ccr.patternlengthbars <= $324)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $325 OR relevant = 1) AND ($326 = 0 OR age <= $327) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-12-24 01:01:04 Duration: 0ms
2 45 277.18 MiB 3.03 MiB 9.44 MiB 6.16 MiB jr.resultuid as resultuid, jr.direction as direction, jr.patternendtime as identified, jr.patternlengthbars as length, jr.patternstarttime as patternstarttime, case when jr.trendchangeid = ? then ? else ? end as trendchange, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, jp.patternname as pattern_name, dtt.timezone as timezone, ? as age, cps.pip, g.basegroupname from japsticks_results jr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = jr.symbolid inner join relevance_japsticks_results rar on rar.resultuid = jr.resultuid inner join symbols s on jr.symbolid = s.symbolid and s.nonliquid = ? inner join japsticks_patterns jp on jr.patternid = jp.id inner join downloadersymbolsettings dss on jr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where jr.gmttimefound > now() - interval ? and s.deleted = ? and (jr.simulation = ? or jr.simulation is null) and (rar.relevant = ?) --and (semicolon_age = ? or rar.age <= semicolon_age) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or jp.patternname in (...)) and (? = ? or jr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results order by symbolid, resultuid ) select * from results order by identified desc, length desc ;-
jr.resultuid AS resultuid, jr.direction AS direction, jr.patternendtime AS identified, jr.patternlengthbars AS length, jr.patternstarttime AS patternstarttime, case when jr.trendchangeid = 1 then 'Continuation' else 'Reversal' end AS trendchange, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, jp.patternname AS pattern_name, dtt.timezone AS timezone, 0 AS age, cps.pip, g.basegroupname FROM japsticks_results jr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = jr.symbolid INNER JOIN relevance_japsticks_results rar ON rar.resultuid = jr.resultuid INNER JOIN symbols s ON jr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN japsticks_patterns jp ON jr.patternid = jp.id INNER JOIN downloadersymbolsettings dss ON jr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE jr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (jr.simulation = 0 OR jr.simulation IS NULL) AND (rar.relevant = 1) --AND (semicolon_age = 0 OR rar.age <= semicolon_age) AND ($2 = 0 OR s.timegranularity in ($3)) AND ($4 = 0 OR s.exchange in ($5)) AND ($6 = 0 OR coalesce(bim.code, s.symbol) in ($7)) AND ($8 = 0 OR jp.patternname in ($9)) AND ($10 = 0 OR jr.patternlengthbars <= $11)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-12-24 01:00:00 Duration: 0ms
3 30 1.66 GiB 3.83 MiB 171.23 MiB 56.76 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-12-24 01:00:05 Duration: 0ms
4 16 581.15 MiB 35.52 MiB 36.51 MiB 36.32 MiB update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-12-24 01:01:14 Duration: 0ms
5 16 1.10 GiB 70.68 MiB 70.69 MiB 70.69 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-12-24 01:01:18 Duration: 0ms
6 8 1003.45 MiB 125.40 MiB 125.46 MiB 125.43 MiB select updateresultsmaterializedview ();-
select updateresultsmaterializedview ();
Date: 2025-12-24 01:02:23 Duration: 0ms
7 4 235.18 MiB 58.76 MiB 58.83 MiB 58.79 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2025-12-24 01:02:09 Duration: 0ms
Queries generating the largest temporary files
Rank Size Query 1 171.23 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-12-24 01:50:05 ]
2 162.56 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-12-24 01:00:05 ]
3 129.23 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-12-24 01:30:04 ]
4 125.46 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 01:47:19 ]
5 125.45 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 01:32:22 ]
6 125.44 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 01:50:32 ]
7 125.43 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 01:35:32 ]
8 125.43 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 01:17:21 ]
9 125.42 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 01:02:23 ]
10 125.41 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 01:20:32 ]
11 125.40 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 01:05:32 ]
12 99.55 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-12-24 01:10:04 ]
13 93.99 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-12-24 01:40:05 ]
14 91.05 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-12-24 01:10:04 ]
15 90.41 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-12-24 01:20:04 ]
16 84.97 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-12-24 01:40:05 ]
17 73.31 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-12-24 01:30:07 ]
18 70.69 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2025-12-24 01:11:18 ]
19 70.69 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2025-12-24 01:16:16 ]
20 70.69 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;[ Date: 2025-12-24 01:18:15 ]
-
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 (20) Main table analyzed (database acaweb_fx)
- 60 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 20 acaweb_fx.pg_catalog.pg_attribute 5 acaweb_fx.public.datafeeds_latestrun 4 acaweb_fx.public.relevance_keylevels_results 4 acaweb_fx.pg_catalog.pg_class 4 acaweb_fx.public.relevance_fibonacci_results 4 acaweb_fx.public.relevance_autochartist_results 4 acaweb_fx.pg_catalog.pg_type 3 acaweb_fx.pg_catalog.pg_index 2 acaweb_fx.public.autochartist_symbolupdates 2 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.public.solr_imports 1 socialmedia.public.processes 1 acaweb_fx.pg_catalog.pg_depend 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.relevance_consecutivecandles_results 1 acaweb_fx.public.symbollatestupdatetime 1 Total 60 Vacuums per table
Key values
- public.solr_relevance_old (26) Main table vacuumed on database acaweb_fx
- 47 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 26 20 17,924 0 75 0 275 10,054 16 1,697,619 acaweb_fx.public.datafeeds_latestrun 4 0 483 0 17 0 0 60 12 66,420 acaweb_fx.pg_toast.pg_toast_2619 2 2 304 0 79 0 0 223 75 294,951 acaweb_fx.pg_catalog.pg_attribute 2 2 1,623 0 390 0 134 765 301 1,754,449 acaweb_fx.public.relevance_keylevels_results 2 2 7,800 0 387 2 216 1,971 1,380 3,650,304 acaweb_fx.pg_catalog.pg_class 2 2 939 0 88 0 0 296 82 444,037 acaweb_fx.public.relevance_autochartist_results 2 2 6,935 0 601 2 475 1,380 864 2,449,974 acaweb_fx.public.relevance_fibonacci_results 2 2 2,522 0 48 0 119 392 229 712,798 acaweb_fx.pg_catalog.pg_type 1 1 119 0 22 0 0 49 16 105,117 acaweb_fx.public.autochartist_symbolupdates 1 1 27,069 0 3,676 3 36,939 9,985 1,833 1,350,354 acaweb_fx.pg_catalog.pg_statistic 1 1 1,021 0 204 0 582 537 180 748,053 acaweb_fx.public.relevance_consecutivecandles_results 1 1 76 0 6 0 0 26 11 55,036 acaweb_fx.public.latest_t15_candle_view 1 1 66 0 1 0 0 6 1 9,085 Total 47 37 66,881 45,832 5,594 7 38,740 25,744 5,000 13,338,197 Tuples removed per table
Key values
- public.solr_relevance_old (68601) Main table with removed tuples on database acaweb_fx
- 82266 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 26 20 68,601 185,810 39,608 0 5,056 acaweb_fx.public.autochartist_symbolupdates 1 1 6,468 64,147 47 0 40,691 acaweb_fx.pg_catalog.pg_attribute 2 2 2,975 21,688 0 38 480 acaweb_fx.public.relevance_keylevels_results 2 2 1,780 23,712 0 0 558 acaweb_fx.public.relevance_autochartist_results 2 2 858 17,753 0 0 760 acaweb_fx.pg_catalog.pg_statistic 1 1 534 3,709 0 0 1,194 acaweb_fx.pg_catalog.pg_class 2 2 296 3,296 0 0 300 acaweb_fx.public.datafeeds_latestrun 4 0 246 56 0 0 64 acaweb_fx.public.relevance_fibonacci_results 2 2 163 2,945 0 0 204 acaweb_fx.pg_toast.pg_toast_2619 2 2 142 347 9 0 105 acaweb_fx.pg_catalog.pg_type 1 1 79 1,444 0 0 38 acaweb_fx.public.latest_t15_candle_view 1 1 66 14 0 0 1 acaweb_fx.public.relevance_consecutivecandles_results 1 1 58 323 0 0 7 Total 47 37 82,266 325,244 39,664 38 49,458 Pages removed per table
Key values
- pg_catalog.pg_attribute (38) Main table with removed pages on database acaweb_fx
- 38 pages Total removed
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_catalog.pg_attribute 2 2 2975 38 acaweb_fx.pg_toast.pg_toast_2619 2 2 142 0 acaweb_fx.pg_catalog.pg_type 1 1 79 0 acaweb_fx.public.datafeeds_latestrun 4 0 246 0 acaweb_fx.public.autochartist_symbolupdates 1 1 6468 0 acaweb_fx.pg_catalog.pg_statistic 1 1 534 0 acaweb_fx.public.relevance_consecutivecandles_results 1 1 58 0 acaweb_fx.public.latest_t15_candle_view 1 1 66 0 acaweb_fx.public.relevance_keylevels_results 2 2 1780 0 acaweb_fx.pg_catalog.pg_class 2 2 296 0 acaweb_fx.public.solr_relevance_old 26 20 68601 0 acaweb_fx.public.relevance_autochartist_results 2 2 858 0 acaweb_fx.public.relevance_fibonacci_results 2 2 163 0 Total 47 37 82,266 38 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Dec 24 01 47 60 02 0 0 - 0 sec Highest CPU-cost vacuum
-
Locks
Locks by types
Key values
- unknown Main Lock Type
- 0 locks Total
Most frequent waiting queries (N)
Rank Count Total time Min time Max time Avg duration Query NO DATASET
Queries that waited the most
Rank Wait time Query NO DATASET
-
Queries
Queries by type
Key values
- 84,471 Total read queries
- 44,752 Total write queries
Queries by database
Key values
- unknown Main database
- 282,878 Requests
- 2h44m14s (unknown)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 920 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 205 0ms select 102 0ms tcl 332 0ms update 39 0ms socialmedia Total 100 0ms select 97 0ms tcl 3 0ms unknown Total 282,878 2h44m14s copy from 16 0ms cte 9,318 0ms insert 32,272 0ms others 12,520 0ms select 84,272 0ms tcl 373 0ms update 2,157 0ms Queries by user
Key values
- unknown Main user
- 282,878 Requests
User Request type Count Duration postgres Total 1,020 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 205 0ms select 199 0ms tcl 335 0ms update 39 0ms unknown Total 282,878 2h44m14s copy from 16 0ms cte 9,318 0ms insert 32,272 0ms others 12,520 0ms select 84,272 0ms tcl 373 0ms update 2,157 0ms Duration by user
Key values
- 2h44m14s (unknown) Main time consuming user
User Request type Count Duration postgres Total 1,020 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 205 0ms select 199 0ms tcl 335 0ms update 39 0ms unknown Total 282,878 2h44m14s copy from 16 0ms cte 9,318 0ms insert 32,272 0ms others 12,520 0ms select 84,272 0ms tcl 373 0ms update 2,157 0ms Queries by host
Key values
- unknown Main host
- 283,898 Requests
- 2h44m14s (unknown)
- Main time consuming host
Queries by application
Key values
- unknown Main application
- 283,511 Requests
- 2h44m14s (unknown)
- Main time consuming application
Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2025-12-24 01:12:50 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 95,708 0-1ms duration
Slowest individual queries
Rank Duration Query NO DATASET
Time consuming queries
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 0ms 1 0ms 0ms 0ms insert into t30 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Dec 24 01 1 0ms 0ms 2 0ms 51 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 #2
Day Hour Count Duration Avg duration Dec 24 01 51 0ms 0ms 3 0ms 356 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 #3
Day Hour Count Duration Avg duration Dec 24 01 356 0ms 0ms 4 0ms 3 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 #4
Day Hour Count Duration Avg duration Dec 24 01 3 0ms 0ms 5 0ms 2,261 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 #5
Day Hour Count Duration Avg duration Dec 24 01 2,261 0ms 0ms 6 0ms 44 0ms 0ms 0ms select count(*) from datafeeds_latestrun where feedname ilike ? and ((latestrxtime > current_timestamp - interval ? and latestdbwritetime > current_timestamp - interval ?) or (latestdbwritetime > current_timestamp - interval ? and lateststartuptime > current_timestamp - interval ?));Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Dec 24 01 44 0ms 0ms 7 0ms 86 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 #7
Day Hour Count Duration Avg duration Dec 24 01 86 0ms 0ms 8 0ms 4 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 #8
Day Hour Count Duration Avg duration Dec 24 01 4 0ms 0ms 9 0ms 4 0ms 0ms 0ms select updaterelevantforrelevantresults ();Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Dec 24 01 4 0ms 0ms 10 0ms 1,587 0ms 0ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Dec 24 01 1,587 0ms 0ms 11 0ms 2 0ms 0ms 0ms insert into t15 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?.?, ?, ?.?, ?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Dec 24 01 2 0ms 0ms 12 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 #12
Day Hour Count Duration Avg duration Dec 24 01 18 0ms 0ms 13 0ms 240 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 #13
Day Hour Count Duration Avg duration Dec 24 01 240 0ms 0ms 14 0ms 41 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 #14
Day Hour Count Duration Avg duration Dec 24 01 41 0ms 0ms 15 0ms 1 0ms 0ms 0ms with pre_symbols as ( select s.symbolid, s.symbol, s.timegranularity, dss.downloadersymbol, dtt.timezone, s.exchange, s.longname 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 and brokerid = ? where dss.classname in (...) and (dss.downloadersymbol in (...) or s.symbol in (...)) and dss.enabled = ? and s.nonliquid = ? and s.deleted = ? ), report_symbols as ( select ps1.*, ps2.symbolid as price_symbol_id from pre_symbols ps1 inner join pre_symbols ps2 on ps1.symbol = ps2.symbol and ps1.downloadersymbol = ps2.downloadersymbol and ps2.timegranularity = ? ), rbr_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ) select bmr.resultuid as ruid, ? as direction, rs.symbol as sym, rs.downloadersymbol, rs.symbolid as sid, rs.timegranularity as tg, rs.timezone, rs.exchange as e, rs.longname, bmr.patternendtime as pet, lpi.latestpricedatetime as lpdt, bmr.patternlengthbars as l, bmr.breakout >= ? as complete, rbr.age as age from bigmovement_results bmr inner join report_symbols rs on rs.symbolid = bmr.symbolid inner join autochartist_symbolupdates lpi on lpi.symbolid = rs.price_symbol_id inner join rbr_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid where patternendtime >= (now() - ? * interval ?) -- results can't be more than ? days old and (bmr.resultuid > rm.resultuid or rbr.relevant = ?) ;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Dec 24 01 1 0ms 0ms 16 0ms 354 0ms 0ms 0ms commit;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Dec 24 01 354 0ms 0ms 17 0ms 479 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 #17
Day Hour Count Duration Avg duration Dec 24 01 479 0ms 0ms 18 0ms 14 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 #18
Day Hour Count Duration Avg duration Dec 24 01 14 0ms 0ms 19 0ms 2 0ms 0ms 0ms select (cast(substring(tz.gmoffset from ? for ?) as float) * ? + cast(substring(tz.gmoffset from ? for ?) as float)) / ? as offset from timezones tz where tz.timezone = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Dec 24 01 2 0ms 0ms 20 0ms 240 0ms 0ms 0ms select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Dec 24 01 240 0ms 0ms Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 40,902 0ms 0ms 0ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Dec 24 01 40,901 0ms 0ms 02 1 0ms 0ms 2 29,336 0ms 0ms 0ms 0ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Dec 24 01 29,336 0ms 0ms 3 8,414 0ms 0ms 0ms 0ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Dec 24 01 8,414 0ms 0ms 4 6,473 0ms 0ms 0ms 0ms insert into autochartist_results (resultid, symbolid, bandwidth, pattern, qtytp, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, relevancestartdistance, simulation, writtendatetime) values (?, ?, ?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Dec 24 01 6,473 0ms 0ms 5 6,037 0ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Dec 24 01 6,037 0ms 0ms 6 6,011 0ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Dec 24 01 6,011 0ms 0ms 7 5,905 0ms 0ms 0ms 0ms insert into t15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Dec 24 01 5,905 0ms 0ms 8 4,842 0ms 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ) select a.symbolid, pattern, patternid, resy0, resy1, resx0, resx1, supporty0, supporty1, supportx0, supportx1, predictiontimeto, patternstarttime, timegranularity, patternendtime, direction, trendchange, patternlengthbars, patternquality, case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, s.exchange, s.symbol, s.longname, s.shortname, breakout, dtt.timezone, patternstartprice, patternendprice, qtytp, newlevels.profit, newlevels.stop, newlevels.filtered, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern inner join rar_max rm on ? = ? left outer join relevance_autochartist_results rar on rar.resultuid = a.resultuid left join lateral calc_cp_signal (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Dec 24 01 4,842 0ms 0ms 9 3,400 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 #9
Day Hour Count Duration Avg duration Dec 24 01 3,400 0ms 0ms 10 2,261 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 #10
Day Hour Count Duration Avg duration Dec 24 01 2,261 0ms 0ms 11 2,169 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 #11
Day Hour Count Duration Avg duration Dec 24 01 2,169 0ms 0ms 12 2,082 0ms 0ms 0ms 0ms insert into fibonacci_results (bandwidth, pattern, gmttimefound, direction, patternstarttime, patternendtime, patternstartprice, patternendprice, qtytp, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, patternlengthbars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) values (?.?, ?, ?::timestamp without time zone, ?, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?, ?, ?, ?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Dec 24 01 2,082 0ms 0ms 13 1,841 0ms 0ms 0ms 0ms insert into keylevels_results (bandwidth, breakout, patternid, gmttimefound, approachingtimestamp, approachingregion, qtytp, patternlengthbars, patternprice, x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, breakoutbars, breakoutprice, patternendtime, atbaridentified, atpriceidentified, errormargin, direction, symbolid, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimebars, uniquepointsvalue, furthestprice, relevancestartdistance, patternclassid, patternstarttime, stoplosslevel, simulation, writtendatetime) values (?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?, ?, ?.?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?.?, ?::timestamp without time zone, ?, ?.?, ?.?, ?, ?, ?.?, ?.?, ?::timestamp without time zone, ?, ?, ?.?, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Dec 24 01 1,841 0ms 0ms 14 1,587 0ms 0ms 0ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Dec 24 01 1,587 0ms 0ms 15 1,311 0ms 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ) select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as ruid, s.symbolid as sid, s.symbol as sym, longname, shortname, exchange as e, timegranularity as tg, a.patternid as pid, a.direction as d, a.patternprice as pp, atbaridentified as pet, case when (x9 != ?) then x9 when (x8 != ?) then x8 when (x7 != ?) then x7 when (x6 != ?) then x6 when (x5 != ?) then x5 when (x4 != ?) then x4 when (x3 != ?) then x3 when (x2 != ?) then x2 end as pst, patternprice as patp, x0, x1, x2, case when (x3 != ?) then x3 else ? end as x3, case when (x4 != ?) then x4 else ? end as x4, case when (x5 != ?) then x5 else ? end as x5, case when (x6 != ?) then x6 else ? end as x6, case when (x7 != ?) then x7 else ? end as x7, case when (x8 != ?) then x8 else ? end as x8, errormargin as erm, breakoutprice as pe, breakoutbars as be, breakout, atbaridentified as atbar, atpriceidentified as atprice, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzos, dtt.timezone as timezone, approachingtimestamp as apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, furthestprice as fp, newlevels.filtered, a.uniquepointsvalue as upv, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from keylevels_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join hrspatterns p on a.patternid = p.patternid inner join rar_max rm on ? = ? left outer join relevance_keylevels_results rar on a.resultuid = rar.resultuid left join lateral calc_kl_signal_filter (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Dec 24 01 1,311 0ms 0ms 16 880 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 #16
Day Hour Count Duration Avg duration Dec 24 01 880 0ms 0ms 17 862 0ms 0ms 0ms 0ms select t.pricedatetime as pricedatetime, t.open as open, t.high as high, t.low as low, t.close "..." close, t.volume as volume, t.bsf as bsf from t60 t where t.symbolid = ? and (bsf = ? or bsf is null) and pricedatetime >= ? and pricedatetime <= ? order by pricedatetime desc limit ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Dec 24 01 862 0ms 0ms 18 519 0ms 0ms 0ms 0ms select downloadersymbol, spike_threshold from price_datafeed_spike_threshold where classname = ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Dec 24 01 519 0ms 0ms 19 519 0ms 0ms 0ms 0ms select s.symbolid, dss.downloadfrequency, dss.downloadersymbol from downloadersymbolsettings dss inner join symbols s on dss.symbolid = s.symbolid where dss.classname = ? and s.deleted = ? and dss.enabled = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Dec 24 01 519 0ms 0ms 20 479 0ms 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 #20
Day Hour Count Duration Avg duration Dec 24 01 479 0ms 0ms Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 0ms 0ms 0ms 1 0ms insert into t30 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Dec 24 01 1 0ms 0ms 2 0ms 0ms 0ms 51 0ms select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Dec 24 01 51 0ms 0ms 3 0ms 0ms 0ms 356 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 #3
Day Hour Count Duration Avg duration Dec 24 01 356 0ms 0ms 4 0ms 0ms 0ms 3 0ms with rar_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ) select bmr.symbolid, patternstarttime, patternendtime, timegranularity, ? as direction, case when bmr.old_resultuid = ? then bmr.old_resultuid else bmr.resultuid end as uid, s.exchange, s.symbol, s.longname, s.shortname, dtt.timezone, bmr.patternmovement, bmr.statisticalmovement, bmr.fromprice, bmr.toprice, bmr.percentile, bmr.patternlengthbars, case when rbr.age is not null then rbr.age when bmr.resultuid <= rm.resultuid then ? else ? end as age, case when rbr.relevant is not null then rbr.relevant when bmr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from bigmovement_results bmr inner join downloadersymbolsettings dss on bmr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on bmr.symbolid = s.symbolid inner join rar_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid left join currencypips cps on cps.symbol = s.symbol where (bmr.old_resultuid = ? or bmr.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Dec 24 01 3 0ms 0ms 5 0ms 0ms 0ms 2,261 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Dec 24 01 2,261 0ms 0ms 6 0ms 0ms 0ms 44 0ms select count(*) from datafeeds_latestrun where feedname ilike ? and ((latestrxtime > current_timestamp - interval ? and latestdbwritetime > current_timestamp - interval ?) or (latestdbwritetime > current_timestamp - interval ? and lateststartuptime > current_timestamp - interval ?));Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Dec 24 01 44 0ms 0ms 7 0ms 0ms 0ms 86 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 #7
Day Hour Count Duration Avg duration Dec 24 01 86 0ms 0ms 8 0ms 0ms 0ms 4 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 #8
Day Hour Count Duration Avg duration Dec 24 01 4 0ms 0ms 9 0ms 0ms 0ms 4 0ms select updaterelevantforrelevantresults ();Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Dec 24 01 4 0ms 0ms 10 0ms 0ms 0ms 1,587 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Dec 24 01 1,587 0ms 0ms 11 0ms 0ms 0ms 2 0ms insert into t15 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?.?, ?, ?.?, ?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Dec 24 01 2 0ms 0ms 12 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 #12
Day Hour Count Duration Avg duration Dec 24 01 18 0ms 0ms 13 0ms 0ms 0ms 240 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 #13
Day Hour Count Duration Avg duration Dec 24 01 240 0ms 0ms 14 0ms 0ms 0ms 41 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 #14
Day Hour Count Duration Avg duration Dec 24 01 41 0ms 0ms 15 0ms 0ms 0ms 1 0ms with pre_symbols as ( select s.symbolid, s.symbol, s.timegranularity, dss.downloadersymbol, dtt.timezone, s.exchange, s.longname 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 and brokerid = ? where dss.classname in (...) and (dss.downloadersymbol in (...) or s.symbol in (...)) and dss.enabled = ? and s.nonliquid = ? and s.deleted = ? ), report_symbols as ( select ps1.*, ps2.symbolid as price_symbol_id from pre_symbols ps1 inner join pre_symbols ps2 on ps1.symbol = ps2.symbol and ps1.downloadersymbol = ps2.downloadersymbol and ps2.timegranularity = ? ), rbr_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ) select bmr.resultuid as ruid, ? as direction, rs.symbol as sym, rs.downloadersymbol, rs.symbolid as sid, rs.timegranularity as tg, rs.timezone, rs.exchange as e, rs.longname, bmr.patternendtime as pet, lpi.latestpricedatetime as lpdt, bmr.patternlengthbars as l, bmr.breakout >= ? as complete, rbr.age as age from bigmovement_results bmr inner join report_symbols rs on rs.symbolid = bmr.symbolid inner join autochartist_symbolupdates lpi on lpi.symbolid = rs.price_symbol_id inner join rbr_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid where patternendtime >= (now() - ? * interval ?) -- results can't be more than ? days old and (bmr.resultuid > rm.resultuid or rbr.relevant = ?) ;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Dec 24 01 1 0ms 0ms 16 0ms 0ms 0ms 354 0ms commit;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Dec 24 01 354 0ms 0ms 17 0ms 0ms 0ms 479 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 #17
Day Hour Count Duration Avg duration Dec 24 01 479 0ms 0ms 18 0ms 0ms 0ms 14 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 #18
Day Hour Count Duration Avg duration Dec 24 01 14 0ms 0ms 19 0ms 0ms 0ms 2 0ms select (cast(substring(tz.gmoffset from ? for ?) as float) * ? + cast(substring(tz.gmoffset from ? for ?) as float)) / ? as offset from timezones tz where tz.timezone = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Dec 24 01 2 0ms 0ms 20 0ms 0ms 0ms 240 0ms select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Dec 24 01 240 0ms 0ms Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 8s100ms 9,652 0ms 21ms 0ms SELECT ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Dec 24 01 9,652 8s100ms 0ms -
SELECT ;
Date: 2025-12-24 01:26:24 Duration: 21ms Database: postgres
-
SELECT ;
Date: 2025-12-24 01:15:50 Duration: 19ms Database: postgres
-
SELECT ;
Date: 2025-12-24 01:31:56 Duration: 18ms Database: postgres
2 5s380ms 5,059 0ms 16ms 1ms WITH rar_max as ( ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 01 5,059 5s380ms 1ms -
WITH rar_max as ( ;
Date: 2025-12-24 01:20:13 Duration: 16ms Database: postgres
-
WITH rar_max as ( ;
Date: 2025-12-24 01:26:54 Duration: 13ms Database: postgres
-
WITH rar_max as ( ;
Date: 2025-12-24 01:15:33 Duration: 11ms Database: postgres
3 1s179ms 1,005 0ms 2ms 1ms SELECT symbolid, ;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 01 1,005 1s179ms 1ms -
SELECT symbolid, ;
Date: 2025-12-24 01:01:49 Duration: 2ms Database: postgres
-
SELECT symbolid, ;
Date: 2025-12-24 01:16:08 Duration: 2ms Database: postgres
-
SELECT symbolid, ;
Date: 2025-12-24 01:00:44 Duration: 2ms Database: postgres
4 826ms 6,037 0ms 9ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 01 6,037 826ms 0ms -
SET extra_float_digits = 3;
Date: 2025-12-24 01:14:11 Duration: 9ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2025-12-24 01:43:16 Duration: 6ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2025-12-24 01:31:56 Duration: 4ms Database: postgres
5 533ms 519 0ms 1ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 01 519 533ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-12-24 01:16:17 Duration: 1ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-12-24 01:01:02 Duration: 1ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-12-24 01:32:01 Duration: 1ms Database: postgres
6 532ms 9,110 0ms 9ms 0ms select 1;Times Reported Time consuming prepare #6
Day Hour Count Duration Avg duration 01 9,110 532ms 0ms -
select 1;
Date: 2025-12-24 01:06:18 Duration: 9ms Database: postgres
-
select 1;
Date: 2025-12-24 01:13:08 Duration: 7ms Database: postgres
-
select 1;
Date: 2025-12-24 01:00:47 Duration: 4ms Database: postgres
7 297ms 3,133 0ms 5ms 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 #7
Day Hour Count Duration Avg duration 01 3,133 297ms 0ms -
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 01:31:52 Duration: 5ms 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: 2025-12-24 01:00:45 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: 2025-12-24 01:02:12 Duration: 0ms Database: postgres
8 224ms 2,077 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 #8
Day Hour Count Duration Avg duration 01 2,077 224ms 0ms -
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 01:11:30 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: 2025-12-24 01:01:22 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: 2025-12-24 01:00:47 Duration: 0ms Database: postgres
9 143ms 897 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 01 897 143ms 0ms -
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 01:41:49 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: 2025-12-24 01:02:27 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: 2025-12-24 01:31:57 Duration: 0ms Database: postgres
10 110ms 6,011 0ms 6ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 01 6,011 110ms 0ms -
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-12-24 01:32:55 Duration: 6ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-12-24 01:31:56 Duration: 3ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-12-24 01:31:56 Duration: 3ms Database: postgres
11 101ms 16 4ms 7ms 6ms with sym_info as ( ;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 01 16 101ms 6ms -
with sym_info as ( ;
Date: 2025-12-24 01:21:41 Duration: 7ms Database: postgres
-
with sym_info as ( ;
Date: 2025-12-24 01:51:42 Duration: 7ms Database: postgres
-
with sym_info as ( ;
Date: 2025-12-24 01:51:44 Duration: 6ms Database: postgres
12 62ms 418 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 #12
Day Hour Count Duration Avg duration 01 418 62ms 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: 2025-12-24 01:16:10 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: 2025-12-24 01:02:54 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: 2025-12-24 01:02:37 Duration: 0ms Database: postgres
13 49ms 429 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 #13
Day Hour Count Duration Avg duration 01 429 49ms 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: 2025-12-24 01:31:18 Duration: 0ms Database: postgres
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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: 2025-12-24 01:15:58 Duration: 0ms Database: postgres
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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: 2025-12-24 01:16:51 Duration: 0ms Database: postgres
14 44ms 18 1ms 3ms 2ms select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 01 18 44ms 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: 2025-12-24 01:51:01 Duration: 3ms Database: postgres
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-12-24 01:20:03 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: 2025-12-24 01:41:08 Duration: 2ms Database: postgres
15 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 #15
Day Hour Count Duration Avg duration 01 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: 2025-12-24 01:20:05 Duration: 3ms Database: postgres
-
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2025-12-24 01:50:04 Duration: 3ms Database: postgres
-
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2025-12-24 01:00:04 Duration: 2ms Database: postgres
16 14ms 24 0ms 0ms 0ms select count(*) from datafeed_restarter_events where is_current_entry = 1;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 01 24 14ms 0ms -
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-12-24 01:00:02 Duration: 0ms Database: postgres
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-12-24 01:40:02 Duration: 0ms Database: postgres
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select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-12-24 01:40:02 Duration: 0ms Database: postgres
17 13ms 6 2ms 2ms 2ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 01 6 13ms 2ms -
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-12-24 01:40:02 Duration: 2ms Database: postgres
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-12-24 01:20:02 Duration: 2ms Database: postgres
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-12-24 01:30:03 Duration: 2ms Database: postgres
18 5ms 3 0ms 3ms 1ms select brokerid from processes where "uuid" = '0aff8a66-2dcc-405a-80b8-9bf344f698d2' limit 1000;Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 01 3 5ms 1ms -
select brokerid from processes where "uuid" = '0aff8a66-2dcc-405a-80b8-9bf344f698d2' limit 1000;
Date: 2025-12-24 01:53:27 Duration: 3ms Database: postgres
-
select brokerid from processes where "uuid" = '0aff8a66-2dcc-405a-80b8-9bf344f698d2' limit 1000;
Date: 2025-12-24 01:13:50 Duration: 1ms Database: postgres
-
select brokerid from processes where "uuid" = '0aff8a66-2dcc-405a-80b8-9bf344f698d2' limit 1000;
Date: 2025-12-24 01:02:48 Duration: 0ms Database: postgres
19 5ms 4 0ms 3ms 1ms WITH pre_symbols AS ( /* find relevant symbols */ ;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 01 4 5ms 1ms -
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-12-24 01:01:09 Duration: 3ms Database: postgres
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-12-24 01:01:09 Duration: 0ms Database: postgres
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-12-24 01:01:09 Duration: 0ms Database: postgres
20 4ms 13 0ms 0ms 0ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 01 13 4ms 0ms -
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-12-24 01:21:45 Duration: 0ms Database: postgres
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-12-24 01:39:34 Duration: 0ms Database: postgres
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-12-24 01:18:44 Duration: 0ms Database: postgres
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 55s872ms 8,351 0ms 65ms 6ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Dec 24 01 8,351 55s872ms 6ms -
WITH rar_max as ( ;
Date: 2025-12-24 01:15:58 Duration: 65ms Database: postgres parameters: $1 = 't', $2 = '538', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '125', $14 = 'ANGLO', $15 = 'BARC', $16 = 'BAY', $17 = 'BPLON', $18 = 'HSBCL', $19 = 'LLOY', $20 = 'RIO', $21 = 'RollsRoyce', $22 = 'TESCO', $23 = 'VOD', $24 = 'AUDCAD', $25 = 'AUDCHF', $26 = 'AUDJPY', $27 = 'AUDNZD', $28 = 'AUDUSD', $29 = 'CADCHF', $30 = 'CADJPY', $31 = 'CHFJPY', $32 = 'EURAUD', $33 = 'EURCAD', $34 = 'EURCHF', $35 = 'EURDKK', $36 = 'EURGBP', $37 = 'EURHUF', $38 = 'EURJPY', $39 = 'EURNOK', $40 = 'EURNZD', $41 = 'EURPLN', $42 = 'EURUSD', $43 = 'GBPAUD', $44 = 'GBPCAD', $45 = 'GBPCHF', $46 = 'GBPJPY', $47 = 'GBPNZD', $48 = 'GBPUSD', $49 = 'GBPZAR', $50 = 'NZDCAD', $51 = 'NZDCHF', $52 = 'NZDJPY', $53 = 'NZDUSD', $54 = 'USDCAD', $55 = 'USDCHF', $56 = 'USDCNH', $57 = 'USDCZK', $58 = 'USDDKK', $59 = 'USDHKD', $60 = 'USDHUF', $61 = 'USDJPY', $62 = 'USDMXN', $63 = 'USDNOK', $64 = 'USDPLN', $65 = 'USDSEK', $66 = 'USDSGD', $67 = 'USDTRY', $68 = 'USDZAR', $69 = 'XAGEUR', $70 = 'XAGUSD', $71 = 'XAUEUR', $72 = 'XAUUSD', $73 = 'ZARJPY', $74 = 'Cocoa', $75 = 'Coffee', $76 = 'Copper', $77 = 'Palladium', $78 = 'Platinum', $79 = 'Sugar', $80 = 'UKOIL', $81 = 'USOIL', $82 = 'AUS200', $83 = 'FRA40', $84 = 'JPN225', $85 = 'NETH25', $86 = 'SPA35', $87 = 'SUI20', $88 = 'UK100', $89 = 'USA100', $90 = 'USA30', $91 = 'USDIndex', $92 = 'ALCOA', $93 = 'ALIBABA', $94 = 'AMAZON', $95 = 'AMEX', $96 = 'APPLE', $97 = 'BBVA', $98 = 'BOA', $99 = 'BOEING', $100 = 'CHEVRON', $101 = 'CISCO', $102 = 'COKE', $103 = 'EBAY', $104 = 'GE', $105 = 'GOOGLE', $106 = 'GS', $107 = 'HLT', $108 = 'IBM', $109 = 'ILMN', $110 = 'INTEL', $111 = 'Iberdrola', $112 = 'MCARD', $113 = 'MCDON', $114 = 'META', $115 = 'MSFT', $116 = 'Mapfre', $117 = 'Netflix', $118 = 'PFIZER', $119 = 'QCOM', $120 = 'Santander', $121 = 'TEVA', $122 = 'Telefonica', $123 = 'Tesla', $124 = 'AUDUSD', $125 = 'EURGBP', $126 = 'EURUSD', $127 = 'GBPUSD', $128 = 'NZDUSD', $129 = 'USDCAD', $130 = 'USDCHF', $131 = 'USDJPY', $132 = 'Adidas', $133 = 'Bayer', $134 = 'Daimler', $135 = 'Danone', $136 = 'LVMH', $137 = 'Lufthansa', $138 = 'Volksw', $139 = '0', $140 = '', $141 = '0', $142 = '0', $143 = '0', $144 = '700', $145 = '700', $146 = 't', $147 = '10', $148 = '10'
-
WITH rar_max as ( ;
Date: 2025-12-24 01:02:08 Duration: 61ms Database: postgres parameters: $1 = 't', $2 = '689', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '310', $14 = '#AAPL', $15 = '#ADS', $16 = '#AIG', $17 = '#ALV', $18 = '#AMZN', $19 = '#AXP', $20 = '#BA', $21 = '#BABA', $22 = '#BAC', $23 = '#BAS', $24 = '#BAYN', $25 = '#BEI', $26 = '#BIDU', $27 = '#BMW', $28 = '#C', $29 = '#CAT', $30 = '#CBK', $31 = '#CL', $32 = '#CSCO', $33 = '#CVX', $34 = '#DAI', $35 = '#DB1', $36 = '#DBK', $37 = '#DIS', $38 = '#DPW', $39 = '#DTE', $40 = '#EBAY', $41 = '#EON', $42 = '#F', $43 = '#FB', $44 = '#FDX', $45 = '#FME', $46 = '#GE', $47 = '#GM', $48 = '#GOOG', $49 = '#GS', $50 = '#HPQ', $51 = '#IBM', $52 = '#IFX', $53 = '#INTC', $54 = '#JD', $55 = '#JNJ', $56 = '#JPM', $57 = '#KO', $58 = '#LHA', $59 = '#LMT', $60 = '#MA', $61 = '#MCD', $62 = '#META', $63 = '#MMM', $64 = '#MSFT', $65 = '#MUV2', $66 = '#NFLX', $67 = '#NKE', $68 = '#NTES', $69 = '#ORCL', $70 = '#PFE', $71 = '#PG', $72 = '#QCOM', $73 = '#RACE', $74 = '#RWE', $75 = '#SAP', $76 = '#SIE', $77 = '#T', $78 = '#UBER', $79 = '#V', $80 = '#VOW', $81 = '#WB', $82 = '#XOM', $83 = 'AUDCAD', $84 = 'AUDCHF', $85 = 'AUDJPY', $86 = 'AUDNZD', $87 = 'AUDUSD', $88 = 'AUS200', $89 = 'BRENT', $90 = 'BTCUSD', $91 = 'CADCHF', $92 = 'CADJPY', $93 = 'CHFJPY', $94 = 'CHI50', $95 = 'ESP35', $96 = 'ETHUSD', $97 = 'EU50', $98 = 'EURAUD', $99 = 'EURCAD', $100 = 'EURCHF', $101 = 'EURGBP', $102 = 'EURHUF', $103 = 'EURJPY', $104 = 'EURNZD', $105 = 'EURPLN', $106 = 'EURUSD', $107 = 'FRA40', $108 = 'GBPAUD', $109 = 'GBPCAD', $110 = 'GBPCHF', $111 = 'GBPJPY', $112 = 'GBPNZD', $113 = 'GBPUSD', $114 = 'GER30', $115 = 'HK50', $116 = 'HKCH50', $117 = 'IT40', $118 = 'JP225', $119 = 'LTCUSD', $120 = 'NAS100', $121 = 'NZDCAD', $122 = 'NZDCHF', $123 = 'NZDJPY', $124 = 'NZDUSD', $125 = 'SPX500', $126 = 'UK100', $127 = 'US30', $128 = 'USDCAD', $129 = 'USDCHF', $130 = 'USDCNH', $131 = 'USDCZK', $132 = 'USDDKK', $133 = 'USDHKD', $134 = 'USDHUF', $135 = 'USDJPY', $136 = 'USDMXN', $137 = 'USDNOK', $138 = 'USDPLN', $139 = 'USDSEK', $140 = 'USDSGD', $141 = 'USDTRY', $142 = 'USDX', $143 = 'USDZAR', $144 = 'WTI', $145 = 'XAGUSD', $146 = 'XAUUSD', $147 = '#ADS', $148 = '#ALV', $149 = '#BAS', $150 = '#BAYN', $151 = '#BEI', $152 = '#BMW', $153 = '#CBK', $154 = '#DAI', $155 = '#DB1', $156 = '#DBK', $157 = '#DPW', $158 = '#DTE', $159 = '#EON', $160 = '#FME', $161 = '#IFX', $162 = '#LHA', $163 = '#MUV2', $164 = '#RWE', $165 = '#SAP', $166 = '#SIE', $167 = '#VOW', $168 = 'AUDCAD', $169 = 'AUDCHF', $170 = 'AUDJPY', $171 = 'AUDNZD', $172 = 'AUDUSD', $173 = 'CADCHF', $174 = 'CADJPY', $175 = 'CHFJPY', $176 = 'EURAUD', $177 = 'EURCAD', $178 = 'EURCHF', $179 = 'EURGBP', $180 = 'EURHUF', $181 = 'EURJPY', $182 = 'EURNZD', $183 = 'EURPLN', $184 = 'EURUSD', $185 = 'GBPAUD', $186 = 'GBPCAD', $187 = 'GBPCHF', $188 = 'GBPJPY', $189 = 'GBPNZD', $190 = 'GBPUSD', $191 = 'NZDCAD', $192 = 'NZDCHF', $193 = 'NZDJPY', $194 = 'NZDUSD', $195 = 'USDCAD', $196 = 'USDCHF', $197 = 'USDCNH', $198 = 'USDCZK', $199 = 'USDDKK', $200 = 'USDHKD', $201 = 'USDHUF', $202 = 'USDJPY', $203 = 'USDMXN', $204 = 'USDNOK', $205 = 'USDPLN', $206 = 'USDSEK', $207 = 'USDSGD', $208 = 'USDTRY', $209 = 'USDX', $210 = 'USDZAR', $211 = 'XAGUSD', $212 = 'XAUUSD', $213 = 'BTCUSD', $214 = 'ETHUSD', $215 = 'LTCUSD', $216 = 'AUDCAD', $217 = 'AUDCHF', $218 = 'AUDJPY', $219 = 'AUDNZD', $220 = 'CADCHF', $221 = 'CADJPY', $222 = 'CHFJPY', $223 = 'EURAUD', $224 = 'EURCAD', $225 = 'EURCHF', $226 = 'EURGBP', $227 = 'EURHUF', $228 = 'EURJPY', $229 = 'EURNZD', $230 = 'EURPLN', $231 = 'GBPAUD', $232 = 'GBPCAD', $233 = 'GBPCHF', $234 = 'GBPJPY', $235 = 'GBPNZD', $236 = 'NZDCAD', $237 = 'NZDCHF', $238 = 'NZDJPY', $239 = 'USDCNH', $240 = 'USDCZK', $241 = 'USDDKK', $242 = 'USDHKD', $243 = 'USDHUF', $244 = 'USDMXN', $245 = 'USDNOK', $246 = 'USDPLN', $247 = 'USDSEK', $248 = 'USDSGD', $249 = 'USDTRY', $250 = 'USDX', $251 = 'USDZAR', $252 = 'XAGUSD', $253 = 'XAUUSD', $254 = 'BRENT', $255 = 'WTI', $256 = 'AUS200', $257 = 'CHI50', $258 = 'ESP35', $259 = 'EU50', $260 = 'FRA40', $261 = 'GER30', $262 = 'HK50', $263 = 'HKCH50', $264 = 'IT40', $265 = 'JP225', $266 = 'NAS100', $267 = 'SPX500', $268 = 'UK100', $269 = 'US30', $270 = 'AUDUSD', $271 = 'EURUSD', $272 = 'GBPUSD', $273 = 'NZDUSD', $274 = 'USDCAD', $275 = 'USDCHF', $276 = 'USDJPY', $277 = '#AAPL', $278 = '#AIG', $279 = '#AMZN', $280 = '#AXP', $281 = '#BA', $282 = '#BABA', $283 = '#BAC', $284 = '#BIDU', $285 = '#C', $286 = '#CAT', $287 = '#CL', $288 = '#CSCO', $289 = '#CVX', $290 = '#DIS', $291 = '#EBAY', $292 = '#F', $293 = '#FB', $294 = '#FDX', $295 = '#GE', $296 = '#GM', $297 = '#GOOG', $298 = '#GS', $299 = '#HPQ', $300 = '#IBM', $301 = '#INTC', $302 = '#JD', $303 = '#JNJ', $304 = '#JPM', $305 = '#KO', $306 = '#LMT', $307 = '#MA', $308 = '#MCD', $309 = '#MMM', $310 = '#MSFT', $311 = '#NFLX', $312 = '#NKE', $313 = '#NTES', $314 = '#ORCL', $315 = '#PFE', $316 = '#PG', $317 = '#QCOM', $318 = '#RACE', $319 = '#T', $320 = '#UBER', $321 = '#V', $322 = '#WB', $323 = '#XOM', $324 = '0', $325 = '', $326 = '0', $327 = '0', $328 = '0', $329 = '700', $330 = '700', $331 = 't', $332 = '10', $333 = '10'
-
WITH rar_max as ( ;
Date: 2025-12-24 01:02:07 Duration: 61ms Database: postgres parameters: $1 = '558', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '160', $13 = 'AUDSGD', $14 = 'CHFSGD', $15 = 'EURDKK', $16 = 'EURHKD', $17 = 'EURNOK', $18 = 'EURPLN', $19 = 'EURSEK', $20 = 'EURSGD', $21 = 'EURTRY', $22 = 'EURZAR', $23 = 'GBPDKK', $24 = 'GBPNOK', $25 = 'GBPSEK', $26 = 'GBPSGD', $27 = 'NOKJPY', $28 = 'NOKSEK', $29 = 'SEKJPY', $30 = 'SGDJPY', $31 = 'USDCNH', $32 = 'USDCZK', $33 = 'USDDKK', $34 = 'USDHKD', $35 = 'USDHUF', $36 = 'USDMXN', $37 = 'USDNOK', $38 = 'USDPLN', $39 = 'USDRUB', $40 = 'USDSEK', $41 = 'USDTHB', $42 = 'USDTRY', $43 = 'USDZAR', $44 = 'AUDUSD', $45 = 'EURUSD', $46 = 'GBPUSD', $47 = 'USDCAD', $48 = 'USDCHF', $49 = 'USDJPY', $50 = 'AUDCAD', $51 = 'AUDCHF', $52 = 'AUDJPY', $53 = 'AUDNZD', $54 = 'CADCHF', $55 = 'CADJPY', $56 = 'CHFJPY', $57 = 'EURAUD', $58 = 'EURCAD', $59 = 'EURCHF', $60 = 'EURGBP', $61 = 'EURJPY', $62 = 'EURNZD', $63 = 'GBPAUD', $64 = 'GBPCAD', $65 = 'GBPCHF', $66 = 'GBPJPY', $67 = 'GBPNZD', $68 = 'NZDCAD', $69 = 'NZDCHF', $70 = 'NZDJPY', $71 = 'NZDUSD', $72 = 'USDSGD', $73 = 'AUS200', $74 = 'DE30', $75 = 'ES35', $76 = 'F40', $77 = 'HK50', $78 = 'IT40', $79 = 'JP225', $80 = 'STOXX50', $81 = 'UK100', $82 = 'US2000', $83 = 'US30', $84 = 'US500', $85 = 'CHINA50', $86 = 'USTEC', $87 = 'XAGEUR', $88 = 'XAGUSD', $89 = 'XAUUSD', $90 = 'XAUEUR', $91 = 'XPDUSD', $92 = 'XPTUSD', $93 = 'AUDSGD', $94 = 'CHFSGD', $95 = 'EURDKK', $96 = 'EURHKD', $97 = 'EURNOK', $98 = 'EURPLN', $99 = 'EURSEK', $100 = 'EURSGD', $101 = 'EURTRY', $102 = 'EURZAR', $103 = 'GBPDKK', $104 = 'GBPNOK', $105 = 'GBPSEK', $106 = 'GBPSGD', $107 = 'NOKJPY', $108 = 'NOKSEK', $109 = 'SEKJPY', $110 = 'SGDJPY', $111 = 'USDCNH', $112 = 'USDCZK', $113 = 'USDDKK', $114 = 'USDHKD', $115 = 'USDHUF', $116 = 'USDMXN', $117 = 'USDNOK', $118 = 'USDPLN', $119 = 'USDRUB', $120 = 'USDSEK', $121 = 'USDTHB', $122 = 'USDTRY', $123 = 'USDZAR', $124 = 'AUDUSD', $125 = 'EURUSD', $126 = 'GBPUSD', $127 = 'USDCAD', $128 = 'USDCHF', $129 = 'USDJPY', $130 = 'AUDCAD', $131 = 'AUDCHF', $132 = 'AUDJPY', $133 = 'AUDNZD', $134 = 'CADCHF', $135 = 'CADJPY', $136 = 'CHFJPY', $137 = 'EURAUD', $138 = 'EURCAD', $139 = 'EURCHF', $140 = 'EURGBP', $141 = 'EURJPY', $142 = 'EURNZD', $143 = 'GBPAUD', $144 = 'GBPCAD', $145 = 'GBPCHF', $146 = 'GBPJPY', $147 = 'GBPNZD', $148 = 'NZDCAD', $149 = 'NZDCHF', $150 = 'NZDJPY', $151 = 'NZDUSD', $152 = 'USDSGD', $153 = 'AUS200', $154 = 'DE30', $155 = 'ES35', $156 = 'F40', $157 = 'HK50', $158 = 'IT40', $159 = 'JP225', $160 = 'STOXX50', $161 = 'UK100', $162 = 'US2000', $163 = 'US30', $164 = 'US500', $165 = 'CHINA50', $166 = 'USTEC', $167 = 'XAGEUR', $168 = 'XAGUSD', $169 = 'XAUUSD', $170 = 'XAUEUR', $171 = 'XPDUSD', $172 = 'XPTUSD', $173 = '700', $174 = '700', $175 = 't', $176 = '10', $177 = '10'
2 20s119ms 34,350 0ms 33ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 01 34,350 20s119ms 0ms -
SELECT ;
Date: 2025-12-24 01:32:28 Duration: 33ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840249433958300'
-
SELECT ;
Date: 2025-12-24 01:32:28 Duration: 22ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840243162072300'
-
SELECT ;
Date: 2025-12-24 01:44:37 Duration: 22ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840248167614300'
3 2s261ms 1,005 0ms 9ms 2ms SELECT symbolid, ;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 01 1,005 2s261ms 2ms -
SELECT symbolid, ;
Date: 2025-12-24 01:32:28 Duration: 9ms Database: postgres parameters: $1 = 'ATFX', $2 = '15', $3 = 'NAS100', $4 = 'JP225'
-
SELECT symbolid, ;
Date: 2025-12-24 01:46:03 Duration: 6ms Database: postgres parameters: $1 = 'FPMARKETS', $2 = '15', $3 = 'EURTRY'
-
SELECT symbolid, ;
Date: 2025-12-24 01:01:17 Duration: 5ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'GBPUSD.ID'
4 946ms 40,777 0ms 10ms 0ms select 1;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 01 40,776 946ms 0ms 02 1 0ms 0ms -
select 1;
Date: 2025-12-24 01:51:07 Duration: 10ms Database: postgres
-
select 1;
Date: 2025-12-24 01:06:32 Duration: 3ms Database: postgres
-
select 1;
Date: 2025-12-24 01:16:29 Duration: 3ms Database: postgres
5 894ms 519 1ms 3ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 01 519 894ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-12-24 01:01:47 Duration: 3ms Database: postgres parameters: $1 = 'PEPPERSTONE'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-12-24 01:31:05 Duration: 2ms Database: postgres parameters: $1 = 'FPMARKETS'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-12-24 01:16:51 Duration: 2ms Database: postgres parameters: $1 = 'BDSWISS'
6 839ms 120 4ms 9ms 6ms WITH last_candle AS ( ;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 01 120 839ms 6ms -
WITH last_candle AS ( ;
Date: 2025-12-24 01:16:00 Duration: 9ms Database: postgres parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2025-12-24 01:36:02 Duration: 9ms Database: postgres parameters: $1 = '538', $2 = '538'
-
WITH last_candle AS ( ;
Date: 2025-12-24 01:48:02 Duration: 9ms Database: postgres parameters: $1 = '538', $2 = '538'
7 674ms 16 28ms 50ms 42ms with sym_info as ( ;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 01 16 674ms 42ms -
with sym_info as ( ;
Date: 2025-12-24 01:06:43 Duration: 50ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
-
with sym_info as ( ;
Date: 2025-12-24 01:21:41 Duration: 44ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
-
with sym_info as ( ;
Date: 2025-12-24 01:51:44 Duration: 44ms Database: postgres parameters: $1 = '617', $2 = 'Forex', $3 = 'Forex', $4 = '617', $5 = 'Forex', $6 = '617', $7 = '617', $8 = 'Forex', $9 = '617'
8 458ms 67 0ms 19ms 6ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 01 67 458ms 6ms -
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-12-24 01:56:35 Duration: 19ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-12-24 01:57:14 Duration: 19ms Database: postgres parameters: $1 = '489', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-12-24 01:26:30 Duration: 19ms Database: postgres parameters: $1 = '489', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
9 400ms 17 0ms 40ms 23ms with wh_patitioned as ( ;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 01 17 400ms 23ms -
with wh_patitioned as ( ;
Date: 2025-12-24 01:51:51 Duration: 40ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
-
with wh_patitioned as ( ;
Date: 2025-12-24 01:32:52 Duration: 40ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
-
with wh_patitioned as ( ;
Date: 2025-12-24 01:15:01 Duration: 36ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
10 263ms 3,400 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 01 3,400 263ms 0ms -
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 01:41:47 Duration: 0ms Database: postgres parameters: $1 = '2025-12-23 18:00:00', $2 = '25713.8', $3 = '25729.9', $4 = '25701.9', $5 = '25716.7', $6 = '2662', $7 = '515840247933633300', $8 = '0', $9 = '2025-12-24 01:41:47.937', $10 = '2025-12-24 01:41:47.846', $11 = '25713.8', $12 = '25729.9', $13 = '25701.9', $14 = '25716.7', $15 = '2662', $16 = '0', $17 = '2025-12-24 01:41:47.937', $18 = '2025-12-24 01:41:47.846'
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 01:46:59 Duration: 0ms Database: postgres parameters: $1 = '2025-12-23 22:30:00', $2 = '80.6', $3 = '80.935', $4 = '80.585', $5 = '80.88', $6 = '511', $7 = '515840249442657300', $8 = '0', $9 = '2025-12-24 01:46:59.079', $10 = '2025-12-24 01:46:58.935', $11 = '80.6', $12 = '80.935', $13 = '80.585', $14 = '80.88', $15 = '511', $16 = '0', $17 = '2025-12-24 01:46:59.08', $18 = '2025-12-24 01:46:58.935'
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 01:11:36 Duration: 0ms Database: postgres parameters: $1 = '2025-12-23 21:30:00', $2 = '8780.4', $3 = '8781.4', $4 = '8777.4', $5 = '8777.75', $6 = '704', $7 = '515840248015340300', $8 = '0', $9 = '2025-12-24 01:11:36.932', $10 = '2025-12-24 01:11:36.864', $11 = '8780.4', $12 = '8781.4', $13 = '8777.4', $14 = '8777.75', $15 = '704', $16 = '0', $17 = '2025-12-24 01:11:36.932', $18 = '2025-12-24 01:11:36.864'
11 255ms 5,905 0ms 0ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #11
Day Hour Count Duration Avg duration 01 5,905 255ms 0ms -
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 01:02:37 Duration: 0ms Database: postgres parameters: $1 = '2025-12-23 23:45:00', $2 = '24320.36', $3 = '24321.59', $4 = '24319.13', $5 = '24321.59', $6 = '58', $7 = '605679104902026300', $8 = '0', $9 = '2025-12-24 01:02:37.462', $10 = '2025-12-24 01:02:37.371', $11 = '24320.36', $12 = '24321.59', $13 = '24319.13', $14 = '24321.59', $15 = '58', $16 = '0', $17 = '2025-12-24 01:02:37.462', $18 = '2025-12-24 01:02:37.371'
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 01:16:00 Duration: 0ms Database: postgres parameters: $1 = '2025-12-24 01:00:00', $2 = '9.14317', $3 = '9.14671', $4 = '9.14191', $5 = '9.14372', $6 = '407', $7 = '515840233483920300', $8 = '0', $9 = '2025-12-24 01:16:00.015', $10 = '2025-12-24 01:15:59.396', $11 = '9.14317', $12 = '9.14671', $13 = '9.14191', $14 = '9.14372', $15 = '407', $16 = '0', $17 = '2025-12-24 01:16:00.015', $18 = '2025-12-24 01:15:59.396'
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 01:41:49 Duration: 0ms Database: postgres parameters: $1 = '2025-12-24 01:15:00', $2 = '48407.7', $3 = '48413.9', $4 = '48405.95', $5 = '48409.5', $6 = '719', $7 = '515840248000537300', $8 = '0', $9 = '2025-12-24 01:41:49.942', $10 = '2025-12-24 01:41:49.862', $11 = '48407.7', $12 = '48413.9', $13 = '48405.95', $14 = '48409.5', $15 = '719', $16 = '0', $17 = '2025-12-24 01:41:49.942', $18 = '2025-12-24 01:41:49.862'
12 193ms 2,261 0ms 0ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 01 2,261 193ms 0ms -
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 01:01:56 Duration: 0ms Database: postgres parameters: $1 = '2025-12-23 23:00:00', $2 = '4497.8', $3 = '4498.96', $4 = '4483.67', $5 = '4484.88', $6 = '7299', $7 = '515840230627943300', $8 = '0', $9 = '2025-12-24 01:01:56.102', $10 = '2025-12-24 01:01:55.766', $11 = '4497.8', $12 = '4498.96', $13 = '4483.67', $14 = '4484.88', $15 = '7299', $16 = '0', $17 = '2025-12-24 01:01:56.102', $18 = '2025-12-24 01:01:55.766'
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 01:01:53 Duration: 0ms Database: postgres parameters: $1 = '2025-12-23 23:00:00', $2 = '58.534', $3 = '58.624', $4 = '58.524', $5 = '58.539', $6 = '286', $7 = '515840247976420300', $8 = '0', $9 = '2025-12-24 01:01:53.989', $10 = '2025-12-24 01:01:53.714', $11 = '58.534', $12 = '58.624', $13 = '58.524', $14 = '58.539', $15 = '286', $16 = '0', $17 = '2025-12-24 01:01:53.989', $18 = '2025-12-24 01:01:53.714'
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 01:01:02 Duration: 0ms Database: postgres parameters: $1 = '2025-12-24 01:00:00', $2 = '211.1255', $3 = '211.164', $4 = '210.959', $5 = '211.013', $6 = '2253', $7 = '515840249381832300', $8 = '0', $9 = '2025-12-24 01:01:02.507', $10 = '2025-12-24 01:01:02.506', $11 = '211.1255', $12 = '211.164', $13 = '210.959', $14 = '211.013', $15 = '2253', $16 = '0', $17 = '2025-12-24 01:01:02.507', $18 = '2025-12-24 01:01:02.506'
13 65ms 12 3ms 7ms 5ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 01 12 65ms 5ms -
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-12-24 01:12:03 Duration: 7ms Database: postgres parameters: $1 = '958', $2 = '958'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-12-24 01:59:59 Duration: 6ms Database: postgres parameters: $1 = '538', $2 = '538'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-12-24 01:12:03 Duration: 6ms Database: postgres parameters: $1 = '958', $2 = '958'
14 63ms 472 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 #14
Day Hour Count Duration Avg duration 01 472 63ms 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: 2025-12-24 01:16:10 Duration: 0ms Database: postgres parameters: $1 = '2025-12-23 00:00:00', $2 = '58.036', $3 = '58.644', $4 = '57.834', $5 = '58.564', $6 = '15126', $7 = '500991628282832200', $8 = '0', $9 = '2025-12-24 01:16:10.79', $10 = '2025-12-24 01:16:10.789', $11 = '58.036', $12 = '58.644', $13 = '57.834', $14 = '58.564', $15 = '15126', $16 = '0', $17 = '2025-12-24 01:16:10.79', $18 = '2025-12-24 01:16:10.789'
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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: 2025-12-24 01:01:57 Duration: 0ms Database: postgres parameters: $1 = '2025-12-23 00:00:00', $2 = '58.7435', $3 = '60.717', $4 = '58.4775', $5 = '60.615', $6 = '246357', $7 = '605679104919890300', $8 = '0', $9 = '2025-12-24 01:01:57.31', $10 = '2025-12-24 01:01:57.31', $11 = '58.7435', $12 = '60.717', $13 = '58.4775', $14 = '60.615', $15 = '246357', $16 = '0', $17 = '2025-12-24 01:01:57.31', $18 = '2025-12-24 01:01:57.31'
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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: 2025-12-24 01:02:37 Duration: 0ms Database: postgres parameters: $1 = '2025-12-23 00:00:00', $2 = '24290.96', $3 = '24362.8', $4 = '24252.54', $5 = '24321.59', $6 = '37513', $7 = '605679104902751300', $8 = '0', $9 = '2025-12-24 01:02:37.496', $10 = '2025-12-24 01:02:37.496', $11 = '24290.96', $12 = '24362.8', $13 = '24252.54', $14 = '24321.59', $15 = '37513', $16 = '0', $17 = '2025-12-24 01:02:37.496', $18 = '2025-12-24 01:02:37.496'
15 56ms 429 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 #15
Day Hour Count Duration Avg duration 01 429 56ms 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: 2025-12-24 01:31:18 Duration: 0ms Database: postgres parameters: $1 = '2025-12-23 16:00:00', $2 = '50562.5', $3 = '50707.5', $4 = '50442.5', $5 = '50442.5', $6 = '2198', $7 = '515840230556263300', $8 = '0', $9 = '2025-12-24 01:31:18.284', $10 = '2025-12-24 01:31:18.283', $11 = '50562.5', $12 = '50707.5', $13 = '50442.5', $14 = '50442.5', $15 = '2198', $16 = '0', $17 = '2025-12-24 01:31:18.284', $18 = '2025-12-24 01:31:18.283'
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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: 2025-12-24 01:16:51 Duration: 0ms Database: postgres parameters: $1 = '2025-12-23 20:00:00', $2 = '272.14', $3 = '272.435', $4 = '271.115', $5 = '272.265', $6 = '4704', $7 = '515840249386763300', $8 = '0', $9 = '2025-12-24 01:16:51.233', $10 = '2025-12-24 01:16:51.022', $11 = '272.14', $12 = '272.435', $13 = '271.115', $14 = '272.265', $15 = '4704', $16 = '0', $17 = '2025-12-24 01:16:51.233', $18 = '2025-12-24 01:16:51.022'
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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: 2025-12-24 01:16:03 Duration: 0ms Database: postgres parameters: $1 = '2025-12-23 20:00:00', $2 = '15409', $3 = '15423', $4 = '15404', $5 = '15404', $6 = '1012', $7 = '500991628279121200', $8 = '0', $9 = '2025-12-24 01:16:03.692', $10 = '2025-12-24 01:16:03.558', $11 = '15409', $12 = '15423', $13 = '15404', $14 = '15404', $15 = '1012', $16 = '0', $17 = '2025-12-24 01:16:03.692', $18 = '2025-12-24 01:16:03.558'
16 44ms 45 0ms 1ms 0ms SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 01 45 44ms 0ms -
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2025-12-24 01:15:51 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'XAUUSD.a', $3 = '558'
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SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2025-12-24 01:54:01 Duration: 1ms Database: postgres parameters: $1 = '689', $2 = 'XAUUSD', $3 = '689'
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SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2025-12-24 01:17:26 Duration: 1ms Database: postgres parameters: $1 = '632', $2 = 'GBPUSD', $3 = '632'
17 31ms 1 31ms 31ms 31ms with maxwhid as ( ;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 01 1 31ms 31ms -
with maxwhid as ( ;
Date: 2025-12-24 01:12:45 Duration: 31ms Database: postgres parameters: $1 = '335', $2 = '621', $3 = '637', $4 = '642', $5 = '660', $6 = '666', $7 = '643', $8 = '630', $9 = '680', $10 = '641', $11 = '431', $12 = '622', $13 = '489', $14 = '529', $15 = '576', $16 = '665', $17 = '667', $18 = '558', $19 = '620', $20 = '125', $21 = '488', $22 = '567', $23 = '689', $24 = '700', $25 = '758', $26 = '763', $27 = '765', $28 = '817', $29 = '914', $30 = '972'
18 28ms 6,037 0ms 0ms 0ms SET extra_float_digits = 3;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 01 6,037 28ms 0ms -
SET extra_float_digits = 3;
Date: 2025-12-24 01:09:19 Duration: 0ms Database: postgres
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SET extra_float_digits = 3;
Date: 2025-12-24 01:03:17 Duration: 0ms Database: postgres
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SET extra_float_digits = 3;
Date: 2025-12-24 01:24:23 Duration: 0ms Database: postgres
19 27ms 6,011 0ms 2ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 01 6,011 27ms 0ms -
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-12-24 01:27:24 Duration: 2ms Database: postgres
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-12-24 01:48:11 Duration: 1ms Database: postgres
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-12-24 01:00:16 Duration: 0ms Database: postgres
20 22ms 6 3ms 3ms 3ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 01 6 22ms 3ms -
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-12-24 01:50:02 Duration: 3ms Database: postgres
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-12-24 01:10:02 Duration: 3ms Database: postgres
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with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-12-24 01:30:03 Duration: 3ms Database: postgres
-
Events
Log levels
Key values
- 579,617 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 0 ERROR entries
- 0 WARNING entries
Errors per 5 minutes
NO DATASET
Most Frequent Errors/Events
Key values
- 0 Max number of times the same event was reported
- 0 Total events found
Rank Times reported Error NO DATASET