-
Global information
- Generated on Fri Jan 16 09:59:39 2026
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-01-16_110000.log
- Parsed 1,455,191 log entries in 38s
- Log start from 2026-01-16 11:00:00 to 2026-01-16 11:59:33
-
Overview
Global Stats
- 369 Number of unique normalized queries
- 185,242 Number of queries
- 2h54m9s Total query duration
- 2026-01-16 11:00:00 First query
- 2026-01-16 11:59:33 Last query
- 3,543 queries/s at 2026-01-16 11:30:03 Query peak
- 2h54m9s Total query duration
- 6s483ms Prepare/parse total duration
- 49s464ms Bind total duration
- 2h53m13s Execute total duration
- 37 Number of events
- 3 Number of unique normalized events
- 34 Max number of times the same event was reported
- 0 Number of cancellation
- 47 Total number of automatic vacuums
- 58 Total number of automatic analyzes
- 1,056 Number temporary file
- 190.91 MiB Max size of temporary file
- 6.70 MiB Average size of temporary file
- 2,976 Total number of sessions
- 26 sessions at 2026-01-16 11:22:07 Session peak
- 2d14h38m56s Total duration of sessions
- 1m15s Average duration of sessions
- 62 Average queries per session
- 3s511ms Average queries duration per session
- 1m12s Average idle time per session
- 2,978 Total number of connections
- 43 connections/s at 2026-01-16 11:24:29 Connection peak
- 3 Total number of databases
SQL Traffic
Key values
- 3,543 queries/s Query Peak
- 2026-01-16 11:30:03 Date
SELECT Traffic
Key values
- 1,706 queries/s Query Peak
- 2026-01-16 11:30:03 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 205 queries/s Query Peak
- 2026-01-16 11:00:51 Date
Queries duration
Key values
- 2h54m9s 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) Jan 16 11 185,242 0ms 1m 56ms 5m18s 5m47s 6m7s Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jan 16 11 46,290 26 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jan 16 11 34,327 3,023 16 96 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Jan 16 11 18,716 58,526 3.13 21.20% Day Hour Count Average / Second Jan 16 11 2,978 0.83/s Day Hour Count Average Duration Average idle time Jan 16 11 2,976 1m15s 1m12s -
Connections
Established Connections
Key values
- 43 connections Connection Peak
- 2026-01-16 11:24:29 Date
Connections per database
Key values
- acaweb_fx Main Database
- 2,978 connections Total
Connections per user
Key values
- postgres Main User
- 2,978 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 1400 connections
- 2,978 Total connections
Host Count 104.30.164.187 25 127.0.0.1 113 192.168.0.114 3 192.168.0.216 101 192.168.0.42 1 192.168.0.74 145 192.168.1.145 41 192.168.1.15 78 192.168.1.20 66 192.168.1.231 20 192.168.1.239 3 192.168.1.90 92 192.168.2.126 66 192.168.2.182 12 192.168.2.82 48 192.168.3.199 36 192.168.4.101 4 192.168.4.142 1,400 192.168.4.150 10 192.168.4.238 12 192.168.4.33 89 192.168.4.90 7 192.168.4.93 1 192.168.4.98 330 [local] 275 -
Sessions
Simultaneous sessions
Key values
- 26 sessions Session Peak
- 2026-01-16 11:22:07 Date
Histogram of session times
Key values
- 2,317 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 2,976 sessions Total
Sessions per user
Key values
- postgres Main User
- 2,976 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 2,976 sessions Total
Host Count Total Duration Average Duration 104.30.164.187 25 1h50m2s 4m24s 127.0.0.1 113 9s960ms 88ms 192.168.0.114 1 5m 5m 192.168.0.216 101 1m2s 618ms 192.168.0.42 1 39ms 39ms 192.168.0.74 145 9h29m14s 3m55s 192.168.1.145 41 5h8m7s 7m30s 192.168.1.15 78 2h1m36s 1m33s 192.168.1.20 66 13h47m45s 12m32s 192.168.1.231 20 9h52m47s 29m38s 192.168.1.239 3 18ms 6ms 192.168.1.90 92 40s624ms 441ms 192.168.2.126 66 10s285ms 155ms 192.168.2.182 12 7s799ms 649ms 192.168.2.82 48 20s602ms 429ms 192.168.3.199 36 1s497ms 41ms 192.168.4.101 4 39ms 9ms 192.168.4.142 1,400 10m29s 449ms 192.168.4.150 10 20h5m 2h30s 192.168.4.238 12 14s932ms 1s244ms 192.168.4.33 89 1m21s 913ms 192.168.4.90 7 38s647ms 5s521ms 192.168.4.93 1 258ms 258ms 192.168.4.98 330 17s30ms 51ms [local] 275 3m47s 826ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 11,142 buffers Checkpoint Peak
- 2026-01-16 11:05:37 Date
- 210.054 seconds Highest write time
- 0.102 seconds Sync time
Checkpoints Wal files
Key values
- 20 files Wal files usage Peak
- 2026-01-16 11:40:37 Date
Checkpoints distance
Key values
- 633.34 Mo Distance Peak
- 2026-01-16 11:40:37 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Jan 16 11 55,227 2,038.105s 0.172s 2,038.709s Day Hour Added Removed Recycled Synced files Longest sync Average sync Jan 16 11 0 0 58 2,046 0.086s 0s Day Hour Count Avg time (sec) Jan 16 11 0 0s Day Hour Mean distance Mean estimate Jan 16 11 79,466.33 kB 171,860.67 kB -
Temporary Files
Size of temporary files
Key values
- 481.05 MiB Temp Files size Peak
- 2026-01-16 11:29:33 Date
Number of temporary files
Key values
- 31 per second Temp Files Peak
- 2026-01-16 11:29:22 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Jan 16 11 1,056 6.91 GiB 6.70 MiB Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 127 706.81 MiB 7.92 KiB 120.77 MiB 5.57 MiB create materialized view brokers_best5trades_pricing_mv as select distinct p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / ?::double precision as half_price from t15 p join symbols s on p.symbolid = s.symbolid join downloadersymbolsettings d on s.symbolid = d.symbolid join brokersymbollist bsl on bsl.symbolid = s.symbolid join mongo_config_live_brokers mclb on bsl.brokerid = mclb.broker_id::bigint join mongo_config_brokers_best5 mcb5 on mclb.broker_id = mcb5.broker_id where s.nonliquid = ? and d.enabled = ? and p.pricedatetime >= (current_timestamp - ?::interval) union select distinct p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / ?::double precision as half_price from t30 p join symbols s on p.symbolid = s.symbolid join downloadersymbolsettings d on s.symbolid = d.symbolid join brokersymbollist bsl on bsl.symbolid = s.symbolid join mongo_config_live_brokers mclb on bsl.brokerid = mclb.broker_id::bigint join mongo_config_brokers_best5 mcb5 on mclb.broker_id = mcb5.broker_id where s.nonliquid = ? and d.enabled = ? and p.pricedatetime >= (current_timestamp - ?::interval) union select distinct p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / ?::double precision as half_price from t60 p join symbols s on p.symbolid = s.symbolid join downloadersymbolsettings d on s.symbolid = d.symbolid join brokersymbollist bsl on bsl.symbolid = s.symbolid join mongo_config_live_brokers mclb on bsl.brokerid = mclb.broker_id::bigint join mongo_config_brokers_best5 mcb5 on mclb.broker_id = mcb5.broker_id where s.nonliquid = ? and d.enabled = ? and p.pricedatetime >= (current_timestamp - ?::interval) union select distinct p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / ?::double precision as half_price from t240 p join symbols s on p.symbolid = s.symbolid join downloadersymbolsettings d on s.symbolid = d.symbolid join brokersymbollist bsl on bsl.symbolid = s.symbolid join mongo_config_live_brokers mclb on bsl.brokerid = mclb.broker_id::bigint join mongo_config_brokers_best5 mcb5 on mclb.broker_id = mcb5.broker_id where s.nonliquid = ? and d.enabled = ? and p.pricedatetime >= (current_timestamp - ?::interval) union select distinct p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / ?::double precision as half_price from t1440 p join symbols s on p.symbolid = s.symbolid join downloadersymbolsettings d on s.symbolid = d.symbolid join brokersymbollist bsl on bsl.symbolid = s.symbolid join mongo_config_live_brokers mclb on bsl.brokerid = mclb.broker_id::bigint join mongo_config_brokers_best5 mcb5 on mclb.broker_id = mcb5.broker_id where s.nonliquid = ? and d.enabled = ? and p.pricedatetime >= (current_timestamp - ?::interval) order by ?, ?, ?;-
create materialized view brokers_best5trades_pricing_mv as SELECT DISTINCT p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t15 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '20 days'::interval) UNION SELECT DISTINCT p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t30 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '40 days'::interval) UNION SELECT DISTINCT p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t60 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '80 days'::interval) UNION SELECT DISTINCT p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t240 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '320 days'::interval) UNION SELECT DISTINCT p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t1440 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '720 days'::interval) ORDER BY 7, 6, 1;
Date: 2026-01-16 11:29:22 Duration: 0ms
2 93 328.80 MiB 3.10 MiB 4.01 MiB 3.54 MiB select resultuid from relevance_consecutivecandles_results order by resultuid desc limit ?), all_results as ( select ccr.resultuid as resultuid, ccr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ccr.patternendtime as identified, dtt.timezone as timezone, ccr.qtyconsecutivecandles as length, g.basegroupname, case when rcr.age is not null then rcr.age when ccr.resultuid <= rm.resultuid then ? else ? end as age, case when rcr.relevant is not null then rcr.relevant when ccr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip, newlevels.filtered from consecutivecandles_results ccr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = ccr.symbolid inner join symbols s on ccr.symbolid = s.symbolid and s.nonliquid = ? inner join downloadersymbolsettings dss on ccr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on ccr.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join rar_max rm on ? = ? left outer join relevance_consecutivecandles_results rcr on rcr.resultuid = ccr.resultuid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? left join lateral calc_cc_signal_filter (ccr.resultuid) newlevels on true where ccr.gmttimefound > now() - interval ? and s.deleted = ? and (ccr.simulation = ? or ccr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ccr.patternlengthbars <= ?)), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;-
SELECT resultuid FROM relevance_consecutivecandles_results ORDER BY resultuid DESC LIMIT 1), all_results AS ( SELECT ccr.resultuid AS resultuid, ccr.direction AS direction, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ccr.patternendtime AS identified, dtt.timezone AS timezone, ccr.qtyconsecutivecandles AS length, g.basegroupname, CASE WHEN rcr.age IS NOT NULL THEN rcr.age WHEN ccr.resultuid <= rm.resultuid THEN 1 ELSE 0 END as age, CASE WHEN rcr.relevant IS NOT NULL THEN rcr.relevant WHEN ccr.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant, cps.pip, newLevels.filtered FROM consecutivecandles_results ccr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = ccr.symbolid INNER JOIN symbols s ON ccr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN downloadersymbolsettings dss ON ccr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on ccr.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN relevance_consecutivecandles_results rcr ON rcr.resultuid = ccr.resultuid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' LEFT JOIN LATERAL calc_cc_signal_filter (ccr.resultuid) newLevels on true WHERE ccr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (ccr.simulation = 0 OR ccr.simulation IS NULL) AND ($2 = 0 OR s.timegranularity in ($3, $4, $5, $6, $7, $8, $9)) AND ($10 = 0 OR s.exchange in ($11)) AND ($12 = 0 OR coalesce(bim.code, s.symbol) in ($13, $14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25, $26, $27, $28, $29, $30, $31, $32, $33, $34, $35, $36, $37, $38, $39, $40, $41, $42, $43, $44, $45, $46, $47, $48, $49, $50, $51, $52, $53, $54, $55, $56, $57, $58, $59, $60, $61, $62, $63, $64, $65, $66, $67, $68, $69, $70, $71, $72, $73, $74, $75, $76, $77, $78, $79, $80, $81, $82, $83, $84, $85, $86, $87, $88, $89, $90, $91, $92, $93, $94, $95, $96, $97, $98, $99, $100, $101, $102, $103, $104, $105, $106, $107, $108, $109, $110, $111, $112, $113, $114, $115, $116, $117, $118, $119, $120, $121, $122, $123, $124, $125, $126, $127, $128, $129, $130, $131, $132, $133, $134, $135, $136, $137, $138, $139, $140, $141, $142, $143, $144, $145, $146, $147, $148, $149, $150, $151, $152, $153, $154, $155, $156, $157, $158, $159, $160, $161, $162, $163, $164, $165, $166, $167, $168, $169, $170, $171, $172, $173, $174, $175, $176, $177, $178, $179, $180, $181, $182, $183, $184, $185, $186, $187, $188, $189, $190, $191, $192, $193, $194, $195, $196, $197, $198, $199, $200, $201, $202, $203, $204, $205, $206, $207, $208, $209, $210, $211, $212, $213, $214, $215, $216, $217, $218, $219, $220, $221, $222, $223, $224, $225, $226, $227, $228, $229, $230, $231, $232, $233, $234, $235, $236, $237, $238, $239, $240, $241, $242, $243, $244, $245, $246, $247, $248, $249, $250, $251, $252, $253, $254, $255, $256, $257, $258, $259, $260, $261, $262, $263, $264, $265, $266, $267, $268, $269, $270, $271, $272, $273, $274, $275, $276, $277, $278, $279, $280, $281, $282, $283, $284, $285, $286, $287, $288, $289, $290, $291, $292, $293, $294, $295, $296, $297, $298, $299, $300, $301, $302, $303, $304, $305, $306, $307, $308, $309, $310, $311, $312, $313, $314, $315, $316, $317, $318, $319, $320, $321, $322)) AND ($323 = 0 OR ccr.patternlengthbars <= $324)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $325 OR relevant = 1) AND ($326 = 0 OR age <= $327) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2026-01-16 11:01:05 Duration: 0ms
3 46 303.22 MiB 3.30 MiB 9.62 MiB 6.59 MiB jr.resultuid as resultuid, jr.direction as direction, jr.patternendtime as identified, jr.patternlengthbars as length, jr.patternstarttime as patternstarttime, case when jr.trendchangeid = ? then ? else ? end as trendchange, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, jp.patternname as pattern_name, dtt.timezone as timezone, ? as age, cps.pip, g.basegroupname from japsticks_results jr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = jr.symbolid inner join relevance_japsticks_results rar on rar.resultuid = jr.resultuid inner join symbols s on jr.symbolid = s.symbolid and s.nonliquid = ? inner join japsticks_patterns jp on jr.patternid = jp.id inner join downloadersymbolsettings dss on jr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where jr.gmttimefound > now() - interval ? and s.deleted = ? and (jr.simulation = ? or jr.simulation is null) and (rar.relevant = ?) --and (semicolon_age = ? or rar.age <= semicolon_age) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or jp.patternname in (...)) and (? = ? or jr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results order by symbolid, resultuid ) select * from results order by identified desc, length desc ;-
jr.resultuid AS resultuid, jr.direction AS direction, jr.patternendtime AS identified, jr.patternlengthbars AS length, jr.patternstarttime AS patternstarttime, case when jr.trendchangeid = 1 then 'Continuation' else 'Reversal' end AS trendchange, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, jp.patternname AS pattern_name, dtt.timezone AS timezone, 0 AS age, cps.pip, g.basegroupname FROM japsticks_results jr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = jr.symbolid INNER JOIN relevance_japsticks_results rar ON rar.resultuid = jr.resultuid INNER JOIN symbols s ON jr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN japsticks_patterns jp ON jr.patternid = jp.id INNER JOIN downloadersymbolsettings dss ON jr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE jr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (jr.simulation = 0 OR jr.simulation IS NULL) AND (rar.relevant = 1) --AND (semicolon_age = 0 OR rar.age <= semicolon_age) AND ($2 = 0 OR s.timegranularity in ($3)) AND ($4 = 0 OR s.exchange in ($5)) AND ($6 = 0 OR coalesce(bim.code, s.symbol) in ($7)) AND ($8 = 0 OR jp.patternname in ($9)) AND ($10 = 0 OR jr.patternlengthbars <= $11)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2026-01-16 11:02:55 Duration: 0ms
4 42 745.70 MiB 2.30 MiB 171.57 MiB 17.75 MiB create materialized view brokers_best5trades_pricing_mv as select distinct bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / ?::double precision as half_price from t15 p join symbols s on p.symbolid = s.symbolid join downloadersymbolsettings d on s.symbolid = d.symbolid join brokersymbollist bsl on bsl.symbolid = s.symbolid join mongo_config_live_brokers mclb on bsl.brokerid = mclb.broker_id::bigint join mongo_config_brokers_best5 mcb5 on mclb.broker_id = mcb5.broker_id where s.nonliquid = ? and d.enabled = ? and p.pricedatetime >= (current_timestamp - ?::interval) union select distinct bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / ?::double precision as half_price from t30 p join symbols s on p.symbolid = s.symbolid join downloadersymbolsettings d on s.symbolid = d.symbolid join brokersymbollist bsl on bsl.symbolid = s.symbolid join mongo_config_live_brokers mclb on bsl.brokerid = mclb.broker_id::bigint join mongo_config_brokers_best5 mcb5 on mclb.broker_id = mcb5.broker_id where s.nonliquid = ? and d.enabled = ? and p.pricedatetime >= (current_timestamp - ?::interval) union select distinct bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / ?::double precision as half_price from t60 p join symbols s on p.symbolid = s.symbolid join downloadersymbolsettings d on s.symbolid = d.symbolid join brokersymbollist bsl on bsl.symbolid = s.symbolid join mongo_config_live_brokers mclb on bsl.brokerid = mclb.broker_id::bigint join mongo_config_brokers_best5 mcb5 on mclb.broker_id = mcb5.broker_id where s.nonliquid = ? and d.enabled = ? and p.pricedatetime >= (current_timestamp - ?::interval) union select distinct bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / ?::double precision as half_price from t240 p join symbols s on p.symbolid = s.symbolid join downloadersymbolsettings d on s.symbolid = d.symbolid join brokersymbollist bsl on bsl.symbolid = s.symbolid join mongo_config_live_brokers mclb on bsl.brokerid = mclb.broker_id::bigint join mongo_config_brokers_best5 mcb5 on mclb.broker_id = mcb5.broker_id where s.nonliquid = ? and d.enabled = ? and p.pricedatetime >= (current_timestamp - ?::interval) union select distinct bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / ?::double precision as half_price from t1440 p join symbols s on p.symbolid = s.symbolid join downloadersymbolsettings d on s.symbolid = d.symbolid join brokersymbollist bsl on bsl.symbolid = s.symbolid join mongo_config_live_brokers mclb on bsl.brokerid = mclb.broker_id::bigint join mongo_config_brokers_best5 mcb5 on mclb.broker_id = mcb5.broker_id where s.nonliquid = ? and d.enabled = ? and p.pricedatetime >= (current_timestamp - ?::interval) order by ?, ?, ?;-
create materialized view brokers_best5trades_pricing_mv as SELECT DISTINCT bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t15 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '20 days'::interval) UNION SELECT DISTINCT bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t30 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '40 days'::interval) UNION SELECT DISTINCT bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t60 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '80 days'::interval) UNION SELECT DISTINCT bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t240 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '320 days'::interval) UNION SELECT DISTINCT bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t1440 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '720 days'::interval) ORDER BY 7, 6, 1;
Date: 2026-01-16 11:33:51 Duration: 0ms
5 28 1.67 GiB 3.42 MiB 190.91 MiB 60.93 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2026-01-16 11:10:06 Duration: 0ms
6 16 618.00 MiB 38.62 MiB 38.62 MiB 38.62 MiB update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2026-01-16 11:01:13 Duration: 0ms
7 16 1.11 GiB 70.91 MiB 70.92 MiB 70.92 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2026-01-16 11:01:16 Duration: 0ms
8 12 38.25 MiB 3.18 MiB 3.19 MiB 3.19 MiB select resultuid from relevance_autochartist_results order by resultuid desc limit ?), ar as ( select a.*, rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on sg.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc ;-
SELECT resultuid FROM relevance_autochartist_results ORDER BY resultuid DESC LIMIT 1), ar AS ( SELECT a.*, rr.age, rr.relevant from autochartist_results a LEFT OUTER JOIN relevance_autochartist_results rr on a.resultuid = rr.resultuid WHERE CASE WHEN FALSE = $1 THEN true ELSE a.resultuid > ( select min(resultuid) from relevance_autochartist_results) END), all_results AS ( SELECT ar.resultuid AS resultuid, ar.direction AS direction, ar.predictiontimeto AS predictiontimeto, ar.predictionpricefrom AS predictionpricefrom, ar.predictionpriceto AS predictionpriceto, cp.pip AS pip, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, ar.pattern AS pattern_name, ar.breakout AS breakout, ar.patternendtime AS identified, dtt.timezone AS timezone, ar.patternlengthbars AS length, g.basegroupname, newLevels.profit, newLevels.stop, newLevels.filtered, CASE WHEN ar.age IS NOT NULL THEN ar.age WHEN ar.resultuid <= rm.resultuid THEN 11 ELSE 0 END as age, CASE WHEN ar.relevant IS NOT NULL THEN ar.relevant WHEN ar.resultuid <= rm.resultuid THEN 0 ELSE 1 END as relevant FROM ar INNER JOIN symbols s ON ar.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN brokersymbollist bsl ON bsl.brokerid = $2 AND bsl.symbolid = s.symbolid INNER JOIN symbolgroup sg on bsl.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid INNER JOIN downloadersymbolsettings dss ON sg.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN rar_max rm ON 1 = 1 LEFT OUTER JOIN autochartist_symbolupdates au on dss.symbolid = au.symbolid LEFT OUTER JOIN currencypips cp ON s.symbol = cp.symbol LEFT JOIN LATERAL calc_cp_signal (ar.resultuid) newLevels on true LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE ar.gmttimefound > now() - INTERVAL '7 DAYS' AND dss.enabled = 1 AND s.deleted = 0 AND (ar.simulation = 0 OR ar.simulation IS NULL) AND ($3 = 0 OR s.timegranularity in ($4)) AND ($5 = 0 OR s.exchange in ($6)) AND ($7 = 0 OR coalesce(bim.code, s.symbol) in ($8)) AND ($9 = 0 OR ar.pattern in ($10)) AND ($11 = 0 OR ($12 = 1 AND ar.breakout >= 0) OR ($13 = 2 AND ar.breakout < 0)) AND ($14 = 0 OR ar.patternlengthbars <= $15) and newLevels.filtered = false AND ar.patternstarttime >= coalesce(au.earliestpricedatetime, '1900-01-01'::timestamp without time zone) -- To make sure patternstarttime is in our t-tables ), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $16 OR relevant = 1) AND ($17 = 0 OR age <= $18) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2026-01-16 11:00:16 Duration: 0ms
9 8 1018.19 MiB 127.25 MiB 127.31 MiB 127.27 MiB select updateresultsmaterializedview ();-
select updateresultsmaterializedview ();
Date: 2026-01-16 11:02:19 Duration: 0ms
10 4 337.65 MiB 84.33 MiB 84.49 MiB 84.41 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2026-01-16 11:02:07 Duration: 0ms
11 1 3.18 MiB 3.18 MiB 3.18 MiB 3.18 MiB 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 = ?;-
SELECT resultuid FROM relevance_keylevels_results ORDER BY resultuid DESC LIMIT 1 ) SELECT CASE WHEN a.old_resultuid = $1 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 '0' END AS x3, CASE WHEN (x4 != '') THEN x4 ELSE '0' END AS x4, CASE WHEN (x5 != '') THEN x5 ELSE '0' END AS x5, CASE WHEN (x6 != '') THEN x6 ELSE '0' END AS x6, CASE WHEN (x7 != '') THEN x7 ELSE '0' END AS x7, CASE WHEN (x8 != '') THEN x8 ELSE '0' 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 11 ELSE 0 END as age, CASE WHEN rar.relevant IS NOT NULL THEN rar.relevant WHEN a.resultuid <= rm.resultuid THEN 0 ELSE 1 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 1 = 1 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 = $2 OR a.resultuid = $3) AND dtt.dayofweek = 3;
Date: 2026-01-16 11:14:16 Duration: 0ms
Queries generating the largest temporary files
Rank Size Query 1 190.91 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-01-16 11:00:05 ]
2 171.57 MiB create materialized view brokers_best5trades_pricing_mv as SELECT DISTINCT bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t15 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '20 days'::interval) UNION SELECT DISTINCT bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t30 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '40 days'::interval) UNION SELECT DISTINCT bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t60 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '80 days'::interval) UNION SELECT DISTINCT bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t240 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '320 days'::interval) UNION SELECT DISTINCT bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t1440 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '720 days'::interval) ORDER BY 7, 6, 1;[ Date: 2026-01-16 11:34:11 ]
3 171.55 MiB create materialized view brokers_best5trades_pricing_mv as SELECT DISTINCT bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t15 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '20 days'::interval) UNION SELECT DISTINCT bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t30 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '40 days'::interval) UNION SELECT DISTINCT bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t60 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '80 days'::interval) UNION SELECT DISTINCT bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t240 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '320 days'::interval) UNION SELECT DISTINCT bsl.brokerid, p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t1440 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '720 days'::interval) ORDER BY 7, 6, 1;[ Date: 2026-01-16 11:34:11 ]
4 127.31 MiB select updateresultsmaterializedview ();[ Date: 2026-01-16 11:32:33 ]
5 127.30 MiB select updateresultsmaterializedview ();[ Date: 2026-01-16 11:02:19 ]
6 127.28 MiB select updateresultsmaterializedview ();[ Date: 2026-01-16 11:47:25 ]
7 127.28 MiB select updateresultsmaterializedview ();[ Date: 2026-01-16 11:17:24 ]
8 127.27 MiB select updateresultsmaterializedview ();[ Date: 2026-01-16 11:35:35 ]
9 127.26 MiB select updateresultsmaterializedview ();[ Date: 2026-01-16 11:50:32 ]
10 127.25 MiB select updateresultsmaterializedview ();[ Date: 2026-01-16 11:20:33 ]
11 127.25 MiB select updateresultsmaterializedview ();[ Date: 2026-01-16 11:05:32 ]
12 120.77 MiB create materialized view brokers_best5trades_pricing_mv as SELECT DISTINCT p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t15 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '20 days'::interval) UNION SELECT DISTINCT p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t30 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '40 days'::interval) UNION SELECT DISTINCT p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t60 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '80 days'::interval) UNION SELECT DISTINCT p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t240 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '320 days'::interval) UNION SELECT DISTINCT p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t1440 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '720 days'::interval) ORDER BY 7, 6, 1;[ Date: 2026-01-16 11:29:33 ]
13 120.73 MiB create materialized view brokers_best5trades_pricing_mv as SELECT DISTINCT p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t15 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '20 days'::interval) UNION SELECT DISTINCT p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t30 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '40 days'::interval) UNION SELECT DISTINCT p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t60 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '80 days'::interval) UNION SELECT DISTINCT p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t240 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '320 days'::interval) UNION SELECT DISTINCT p.pricedatetime, p.open, p.high, p.low, p.close, s.timegranularity, s.symbol, (p.high + p.low) / 2::double precision AS half_price FROM t1440 p JOIN symbols s ON p.symbolid = s.symbolid JOIN downloadersymbolsettings d ON s.symbolid = d.symbolid JOIN brokersymbollist bsl ON bsl.symbolid = s.symbolid JOIN mongo_config_live_brokers mclb ON bsl.brokerid = mclb.broker_id::bigint JOIN mongo_config_brokers_best5 mcb5 ON mclb.broker_id = mcb5.broker_id WHERE s.nonliquid = 0 AND d.enabled = 1 AND p.pricedatetime >= (CURRENT_TIMESTAMP - '720 days'::interval) ORDER BY 7, 6, 1;[ Date: 2026-01-16 11:29:33 ]
14 117.15 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-01-16 11:30:05 ]
15 111.39 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-01-16 11:30:04 ]
16 96.57 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-01-16 11:50:04 ]
17 96.41 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: 2026-01-16 11:40:05 ]
18 93.49 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-01-16 11:40:05 ]
19 93.12 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-01-16 11:10:05 ]
20 90.17 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-01-16 11:20:04 ]
-
Vacuums
Vacuums / Analyzes Distribution
Key values
- 0 sec Highest CPU-cost vacuum
Table
Database - Date
- 0 sec Highest CPU-cost analyze
Table
Database - Date
Analyzes per table
Key values
- public.solr_relevance_old (16) Main table analyzed (database acaweb_fx)
- 58 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 16 acaweb_fx.pg_catalog.pg_attribute 6 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.pg_catalog.pg_depend 2 acaweb_fx.public.brokers_best5trades_pricing_mv 2 acaweb_fx.public.solr_imports 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.relevance_consecutivecandles_results 1 Total 58 Vacuums per table
Key values
- public.solr_relevance_old (16) 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 16 16 14,884 0 51 0 0 11,035 16 1,940,647 acaweb_fx.public.relevance_fibonacci_results 5 5 6,879 0 169 8 171 983 74 263,781 acaweb_fx.public.datafeeds_latestrun 4 0 464 0 9 0 0 60 9 51,895 acaweb_fx.public.relevance_autochartist_results 4 4 14,586 0 273 6 908 2,877 191 569,465 acaweb_fx.public.relevance_keylevels_results 3 3 12,010 0 441 7 146 3,448 301 863,881 acaweb_fx.pg_toast.pg_toast_2619 2 2 270 0 44 0 0 199 35 182,865 acaweb_fx.public.latest_t15_candle_view 2 2 137 0 2 0 0 12 2 18,068 acaweb_fx.pg_catalog.pg_class 2 2 917 0 83 0 0 288 83 420,546 acaweb_fx.public.brokers_best5trades_pricing_mv 2 0 50,669 0 42,358 0 0 46,438 2 2,756,494 acaweb_fx.pg_catalog.pg_index 1 1 107 0 16 0 0 28 13 96,831 acaweb_fx.public.autochartist_symbolupdates 1 1 25,811 0 711 2 37,893 7,672 478 659,253 acaweb_fx.pg_catalog.pg_attribute 1 1 773 0 168 0 67 377 127 747,180 acaweb_fx.pg_catalog.pg_depend 1 1 389 0 77 0 59 170 62 319,591 acaweb_fx.pg_catalog.pg_type 1 1 160 0 24 0 0 49 20 122,420 acaweb_fx.pg_catalog.pg_statistic 1 1 1,008 0 132 0 594 487 124 515,001 acaweb_fx.public.symbollatestupdatetime 1 1 1,629 0 250 0 642 1,092 240 621,698 Total 47 41 130,693 100,041 44,808 23 40,480 75,215 1,777 10,149,616 Tuples removed per table
Key values
- public.solr_relevance_old (78657) Main table with removed tuples on database acaweb_fx
- 111055 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 16 16 78,657 106,029 0 0 3,701 acaweb_fx.public.symbollatestupdatetime 1 1 18,515 92,136 118 0 1,714 acaweb_fx.public.autochartist_symbolupdates 1 1 5,956 51,140 7 0 40,691 acaweb_fx.public.relevance_keylevels_results 3 3 2,256 40,929 2,741 0 837 acaweb_fx.pg_catalog.pg_attribute 1 1 1,587 10,734 0 0 264 acaweb_fx.public.relevance_autochartist_results 4 4 1,574 40,275 3,096 0 1,520 acaweb_fx.pg_catalog.pg_depend 1 1 587 14,650 0 0 135 acaweb_fx.public.relevance_fibonacci_results 5 5 572 8,759 880 0 510 acaweb_fx.pg_catalog.pg_statistic 1 1 525 3,766 0 0 1,194 acaweb_fx.pg_catalog.pg_class 2 2 287 3,298 0 0 300 acaweb_fx.public.datafeeds_latestrun 4 0 244 56 0 0 64 acaweb_fx.pg_toast.pg_toast_2619 2 2 128 338 4 0 98 acaweb_fx.public.latest_t15_candle_view 2 2 115 28 0 0 2 acaweb_fx.pg_catalog.pg_type 1 1 50 1,446 0 0 38 acaweb_fx.pg_catalog.pg_index 1 1 2 825 12 0 22 acaweb_fx.public.brokers_best5trades_pricing_mv 2 0 0 3,913,112 0 0 46,436 Total 47 41 111,055 4,287,521 6,858 0 97,526 Pages removed per table
Key values
- unknown (0) Main table with removed pages on database unknown
- 0 pages Total removed
Pages removed per tables
NO DATASET
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_toast.pg_toast_2619 2 2 128 0 acaweb_fx.pg_catalog.pg_index 1 1 2 0 acaweb_fx.public.datafeeds_latestrun 4 0 244 0 acaweb_fx.public.autochartist_symbolupdates 1 1 5956 0 acaweb_fx.pg_catalog.pg_attribute 1 1 1587 0 acaweb_fx.public.latest_t15_candle_view 2 2 115 0 acaweb_fx.pg_catalog.pg_depend 1 1 587 0 acaweb_fx.public.relevance_keylevels_results 3 3 2256 0 acaweb_fx.pg_catalog.pg_class 2 2 287 0 acaweb_fx.public.relevance_fibonacci_results 5 5 572 0 acaweb_fx.pg_catalog.pg_type 1 1 50 0 acaweb_fx.pg_catalog.pg_statistic 1 1 525 0 acaweb_fx.public.brokers_best5trades_pricing_mv 2 0 0 0 acaweb_fx.public.symbollatestupdatetime 1 1 18515 0 acaweb_fx.public.solr_relevance_old 16 16 78657 0 acaweb_fx.public.relevance_autochartist_results 4 4 1574 0 Total 47 41 111,055 0 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Jan 16 11 47 58 - 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
- 46,290 Total read queries
- 41,976 Total write queries
Queries by database
Key values
- unknown Main database
- 184,232 Requests
- 2h53m13s (unknown)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 919 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 204 0ms select 103 0ms tcl 331 0ms update 39 0ms socialmedia Total 91 0ms select 89 0ms tcl 2 0ms unknown Total 184,232 2h53m13s copy from 16 0ms cte 3,684 0ms ddl 6 0ms insert 34,327 0ms others 4,168 0ms select 46,098 0ms tcl 345 0ms update 2,984 0ms Queries by user
Key values
- unknown Main user
- 184,232 Requests
User Request type Count Duration postgres Total 1,010 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 204 0ms select 192 0ms tcl 333 0ms update 39 0ms unknown Total 184,232 2h53m13s copy from 16 0ms cte 3,684 0ms ddl 6 0ms insert 34,327 0ms others 4,168 0ms select 46,098 0ms tcl 345 0ms update 2,984 0ms Duration by user
Key values
- 2h53m13s (unknown) Main time consuming user
User Request type Count Duration postgres Total 1,010 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 204 0ms select 192 0ms tcl 333 0ms update 39 0ms unknown Total 184,232 2h53m13s copy from 16 0ms cte 3,684 0ms ddl 6 0ms insert 34,327 0ms others 4,168 0ms select 46,098 0ms tcl 345 0ms update 2,984 0ms Queries by host
Key values
- unknown Main host
- 185,242 Requests
- 2h53m13s (unknown)
- Main time consuming host
Queries by application
Key values
- unknown Main application
- 184,854 Requests
- 2h53m13s (unknown)
- Main time consuming application
Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2026-01-16 11:25:53 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 58,694 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 select s.statsid, s.description, s.groupingname, cast(ss.percentage as integer) as cppercentage, cast(hss.percentage as integer) as klpercentage, cast(hass.percentage as integer) as aklpercentage, case when b.name ilike ? then ? else ? end as showaclogo from broker b inner join stats s on b.brokerid = s.brokerid left outer join stats_summary ss on ss.statsid = s.statsid left outer join stats_hrs_summary hss on hss.statsid = s.statsid left outer join stats_hrsapproaches_summary hass on hass.statsid = s.statsid where s.brokerid = ? and ss.total > ? and ss.category ilike ? and hss.category ilike ? and hass.category ilike ? group by s.statsid, s.description, s.brokerid, s.latestupdate, s.groupingname, s.calcfrom, s.calcto, ss.statsid, ss.percentage, hss.percentage, hass.percentage, b.name;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jan 16 11 1 0ms 0ms 2 0ms 3 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 #2
Day Hour Count Duration Avg duration Jan 16 11 3 0ms 0ms 3 0ms 2 0ms 0ms 0ms select o.oid as id, o.xmin as state_number, opfname as name, opfmethod as access_method_id, pg_catalog.pg_get_userbyid(o.opfowner) AS "owner" from pg_catalog.pg_opfamily o where opfnamespace = ?::oid -- and opfname in ( :[*f_names] ) and pg_catalog.age(xmin) <= coalesce(nullif(greatest(pg_catalog.age(?::varchar::xid), ?), ?), ?);Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jan 16 11 2 0ms 0ms 4 0ms 30 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 #4
Day Hour Count Duration Avg duration Jan 16 11 30 0ms 0ms 5 0ms 14 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ) select bmr.symbolid, patternstarttime, patternendtime, timegranularity, ? as direction, case when bmr.old_resultuid = ? then bmr.old_resultuid else bmr.resultuid end as uid, s.exchange, s.symbol, s.longname, s.shortname, dtt.timezone, bmr.patternmovement, bmr.statisticalmovement, bmr.fromprice, bmr.toprice, bmr.percentile, bmr.patternlengthbars, case when rbr.age is not null then rbr.age when bmr.resultuid <= rm.resultuid then ? else ? end as age, case when rbr.relevant is not null then rbr.relevant when bmr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from bigmovement_results bmr inner join downloadersymbolsettings dss on bmr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on bmr.symbolid = s.symbolid inner join rar_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid left join currencypips cps on cps.symbol = s.symbol where (bmr.old_resultuid = ? or bmr.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Jan 16 11 14 0ms 0ms 6 0ms 2,153 0ms 0ms 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Jan 16 11 2,153 0ms 0ms 7 0ms 48 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 #7
Day Hour Count Duration Avg duration Jan 16 11 48 0ms 0ms 8 0ms 4 0ms 0ms 0ms select updaterelevantforrelevantresults ();Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Jan 16 11 4 0ms 0ms 9 0ms 2 0ms 0ms 0ms select oid from pg_catalog.pg_foreign_data_wrapper;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jan 16 11 2 0ms 0ms 10 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 #10
Day Hour Count Duration Avg duration Jan 16 11 18 0ms 0ms 11 0ms 2 0ms 0ms 0ms select count(*) from ( select max(lastupdated) from sa_hist_bigmove where symbolid in ( select symbolid from t60 group by symbolid order by max(sastdatetimereceived) desc limit ?) group by symbolid having max(lastupdated) > current_timestamp - interval ? order by max(lastupdated) desc limit ?) as k;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jan 16 11 2 0ms 0ms 12 0ms 2 0ms 0ms 0ms with system_languages as ( select oid as lang from pg_catalog.pg_language where lanname in (...)) select oid as id, pg_catalog.pg_get_function_arguments(oid) as arguments_def, pg_catalog.pg_get_function_result(oid) as result_def, null as sqlbody_def, prosrc as source_text from pg_catalog.pg_proc where pronamespace = ?::oid -- and pg_proc.proname in ( :[*f_names] ) and pg_catalog.age(xmin) <= coalesce(nullif(greatest(pg_catalog.age(?::varchar::xid), ?), ?), ?) and not (prokind = ?) and prolang not in (select lang from system_languages) and prosrc is not null;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jan 16 11 2 0ms 0ms 13 0ms 339 0ms 0ms 0ms commit;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jan 16 11 339 0ms 0ms 14 0ms 399 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 #14
Day Hour Count Duration Avg duration Jan 16 11 399 0ms 0ms 15 0ms 2 0ms 0ms 0ms select e.oid as id, e.xmin as state_number, extname as name, extversion as version, extnamespace as schema_id, nspname as schema_name, array ( select unnest from unnest(available_versions) where unnest > extversion) as available_updates from pg_catalog.pg_extension e join pg_namespace n on e.extnamespace = n.oid left join ( select name, array_agg(version) as available_versions from pg_available_extension_versions() group by name) v on e.extname = v.name where pg_catalog.age(e.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?);Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Jan 16 11 2 0ms 0ms 16 0ms 238 0ms 0ms 0ms select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Jan 16 11 238 0ms 0ms 17 0ms 2 0ms 0ms 0ms select a.oid as access_method_id, a.xmin as state_number, a.amname as access_method_name, a.amhandler::oid as handler_id, pg_catalog.quote_ident(n.nspname) || ? || pg_catalog.quote_ident(p.proname) as handler_name, a.amtype as access_method_type from pg_am a join pg_proc p on a.amhandler::oid = p.oid join pg_namespace n on p.pronamespace = n.oid where pg_catalog.age(a.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?);Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Jan 16 11 2 0ms 0ms 18 0ms 238 0ms 0ms 0ms select system_identifier from pg_control_system ();Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Jan 16 11 238 0ms 0ms 19 0ms 9 0ms 0ms 0ms select groupid, exchange, groupname, symbol, longname from prfsymboltree where brokerid = ? order by groupname, symbol;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Jan 16 11 9 0ms 0ms 20 0ms 3 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 #20
Day Hour Count Duration Avg duration Jan 16 11 3 0ms 0ms Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 15,515 0ms 0ms 0ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jan 16 11 15,515 0ms 0ms 2 9,271 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 Jan 16 11 9,271 0ms 0ms 3 7,895 0ms 0ms 0ms 0ms select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jan 16 11 7,895 0ms 0ms 4 7,730 0ms 0ms 0ms 0ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Jan 16 11 7,730 0ms 0ms 5 7,552 0ms 0ms 0ms 0ms insert into autochartist_results (resultid, symbolid, bandwidth, pattern, qtytp, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, relevancestartdistance, simulation, writtendatetime) values (?, ?, ?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Jan 16 11 7,552 0ms 0ms 6 5,946 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 #6
Day Hour Count Duration Avg duration Jan 16 11 5,946 0ms 0ms 7 3,361 0ms 0ms 0ms 0ms insert into t30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Jan 16 11 3,361 0ms 0ms 8 3,335 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 #8
Day Hour Count Duration Avg duration Jan 16 11 3,335 0ms 0ms 9 2,772 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 #9
Day Hour Count Duration Avg duration Jan 16 11 2,772 0ms 0ms 10 2,437 0ms 0ms 0ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Jan 16 11 2,437 0ms 0ms 11 2,153 0ms 0ms 0ms 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jan 16 11 2,153 0ms 0ms 12 1,852 0ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jan 16 11 1,852 0ms 0ms 13 1,831 0ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jan 16 11 1,831 0ms 0ms 14 1,259 0ms 0ms 0ms 0ms select symbolid, pricedatetime, classname, downloadfrequency, downloadersymbol, open, high, low, close, volume, bsf, sastdatetimereceived from ( select pricedatetime, dss.classname, dss.downloadfrequency, dss.symbolid, dss.downloadersymbol, t.open, t.high, t.low, t.close, t.volume, t.bsf, t.sastdatetimereceived, row_number() over (partition by t.symbolid order by t.pricedatetime desc) as rn from t15 t, downloadersymbolsettings dss, symbols s where dss.classname = ? and dss.downloadfrequency = ? and dss.symbolid = t.symbolid and s.symbolid = dss.symbolid and dss.enabled = ? and s.deleted = ? and dss.downloadersymbol in (...) and t.pricedatetime > now() - interval ?) as ranked_candles_table where rn = ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Jan 16 11 1,259 0ms 0ms 15 676 0ms 0ms 0ms 0ms select downloadersymbol, spike_threshold from price_datafeed_spike_threshold where classname = ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Jan 16 11 676 0ms 0ms 16 676 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 #16
Day Hour Count Duration Avg duration Jan 16 11 676 0ms 0ms 17 481 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 #17
Day Hour Count Duration Avg duration Jan 16 11 481 0ms 0ms 18 399 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 #18
Day Hour Count Duration Avg duration Jan 16 11 399 0ms 0ms 19 398 0ms 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_autochartist_results order by resultuid desc limit ? ), ar as ( select a.*, rr.age, rr.relevant from autochartist_results a left outer join relevance_autochartist_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_autochartist_results) end ), all_results as ( select ar.resultuid as resultuid, ar.direction as direction, ar.predictiontimeto as predictiontimeto, ar.predictionpricefrom as predictionpricefrom, ar.predictionpriceto as predictionpriceto, cp.pip as pip, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, ar.pattern as pattern_name, ar.breakout as breakout, ar.patternendtime as identified, dtt.timezone as timezone, ar.patternlengthbars as length, g.basegroupname, newlevels.profit, newlevels.stop, newlevels.filtered, case when ar.age is not null then ar.age when ar.resultuid <= rm.resultuid then ? else ? end as age, case when ar.relevant is not null then ar.relevant when ar.resultuid <= rm.resultuid then ? else ? end as relevant from ar inner join symbols s on ar.symbolid = s.symbolid and s.nonliquid = ? inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid inner join symbolgroup sg on bsl.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join downloadersymbolsettings dss on sg.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join currencypips cp on s.symbol = cp.symbol left join lateral calc_cp_signal (ar.resultuid) newlevels on true left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where ar.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (ar.simulation = ? or ar.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or ar.pattern in (...)) and (? = ? or (? = ? and ar.breakout >= ?) or (? = ? and ar.breakout < ?)) and (? = ? or ar.patternlengthbars <= ?) and newlevels.filtered = false and ar.patternstarttime >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Jan 16 11 398 0ms 0ms 20 385 0ms 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ) select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as ruid, s.symbolid as sid, s.symbol as sym, longname, shortname, exchange as e, timegranularity as tg, a.patternid as pid, a.direction as d, a.patternprice as pp, atbaridentified as pet, case when (x9 != ?) then x9 when (x8 != ?) then x8 when (x7 != ?) then x7 when (x6 != ?) then x6 when (x5 != ?) then x5 when (x4 != ?) then x4 when (x3 != ?) then x3 when (x2 != ?) then x2 end as pst, patternprice as patp, x0, x1, x2, case when (x3 != ?) then x3 else ? end as x3, case when (x4 != ?) then x4 else ? end as x4, case when (x5 != ?) then x5 else ? end as x5, case when (x6 != ?) then x6 else ? end as x6, case when (x7 != ?) then x7 else ? end as x7, case when (x8 != ?) then x8 else ? end as x8, errormargin as erm, breakoutprice as pe, breakoutbars as be, breakout, atbaridentified as atbar, atpriceidentified as atprice, patternlengthbars as l, bandwidth as bw, qtytp as qtp, p.patternname as patternname, dtt.absolutetimezoneoffset as tzos, dtt.timezone as timezone, approachingtimestamp as apt, approachingregion as apr, predictionpricefrom as ppf, predictionpriceto as ppt, predictiontimefrom as ptf, predictiontimebars as ptb, furthestprice as fp, newlevels.filtered, a.uniquepointsvalue as upv, case when rar.age is not null then rar.age when a.resultuid <= rm.resultuid then ? else ? end as age, case when rar.relevant is not null then rar.relevant when a.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from keylevels_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join hrspatterns p on a.patternid = p.patternid inner join rar_max rm on ? = ? left outer join relevance_keylevels_results rar on a.resultuid = rar.resultuid left join lateral calc_kl_signal_filter (a.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Jan 16 11 385 0ms 0ms Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 0ms 0ms 0ms 1 0ms select s.statsid, s.description, s.groupingname, cast(ss.percentage as integer) as cppercentage, cast(hss.percentage as integer) as klpercentage, cast(hass.percentage as integer) as aklpercentage, case when b.name ilike ? then ? else ? end as showaclogo from broker b inner join stats s on b.brokerid = s.brokerid left outer join stats_summary ss on ss.statsid = s.statsid left outer join stats_hrs_summary hss on hss.statsid = s.statsid left outer join stats_hrsapproaches_summary hass on hass.statsid = s.statsid where s.brokerid = ? and ss.total > ? and ss.category ilike ? and hss.category ilike ? and hass.category ilike ? group by s.statsid, s.description, s.brokerid, s.latestupdate, s.groupingname, s.calcfrom, s.calcto, ss.statsid, ss.percentage, hss.percentage, hass.percentage, b.name;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jan 16 11 1 0ms 0ms 2 0ms 0ms 0ms 3 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 #2
Day Hour Count Duration Avg duration Jan 16 11 3 0ms 0ms 3 0ms 0ms 0ms 2 0ms select o.oid as id, o.xmin as state_number, opfname as name, opfmethod as access_method_id, pg_catalog.pg_get_userbyid(o.opfowner) AS "owner" from pg_catalog.pg_opfamily o where opfnamespace = ?::oid -- and opfname in ( :[*f_names] ) and pg_catalog.age(xmin) <= coalesce(nullif(greatest(pg_catalog.age(?::varchar::xid), ?), ?), ?);Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jan 16 11 2 0ms 0ms 4 0ms 0ms 0ms 30 0ms select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Jan 16 11 30 0ms 0ms 5 0ms 0ms 0ms 14 0ms with rar_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ) select bmr.symbolid, patternstarttime, patternendtime, timegranularity, ? as direction, case when bmr.old_resultuid = ? then bmr.old_resultuid else bmr.resultuid end as uid, s.exchange, s.symbol, s.longname, s.shortname, dtt.timezone, bmr.patternmovement, bmr.statisticalmovement, bmr.fromprice, bmr.toprice, bmr.percentile, bmr.patternlengthbars, case when rbr.age is not null then rbr.age when bmr.resultuid <= rm.resultuid then ? else ? end as age, case when rbr.relevant is not null then rbr.relevant when bmr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from bigmovement_results bmr inner join downloadersymbolsettings dss on bmr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on bmr.symbolid = s.symbolid inner join rar_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid left join currencypips cps on cps.symbol = s.symbol where (bmr.old_resultuid = ? or bmr.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Jan 16 11 14 0ms 0ms 6 0ms 0ms 0ms 2,153 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Jan 16 11 2,153 0ms 0ms 7 0ms 0ms 0ms 48 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 #7
Day Hour Count Duration Avg duration Jan 16 11 48 0ms 0ms 8 0ms 0ms 0ms 4 0ms select updaterelevantforrelevantresults ();Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Jan 16 11 4 0ms 0ms 9 0ms 0ms 0ms 2 0ms select oid from pg_catalog.pg_foreign_data_wrapper;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jan 16 11 2 0ms 0ms 10 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 #10
Day Hour Count Duration Avg duration Jan 16 11 18 0ms 0ms 11 0ms 0ms 0ms 2 0ms select count(*) from ( select max(lastupdated) from sa_hist_bigmove where symbolid in ( select symbolid from t60 group by symbolid order by max(sastdatetimereceived) desc limit ?) group by symbolid having max(lastupdated) > current_timestamp - interval ? order by max(lastupdated) desc limit ?) as k;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jan 16 11 2 0ms 0ms 12 0ms 0ms 0ms 2 0ms with system_languages as ( select oid as lang from pg_catalog.pg_language where lanname in (...)) select oid as id, pg_catalog.pg_get_function_arguments(oid) as arguments_def, pg_catalog.pg_get_function_result(oid) as result_def, null as sqlbody_def, prosrc as source_text from pg_catalog.pg_proc where pronamespace = ?::oid -- and pg_proc.proname in ( :[*f_names] ) and pg_catalog.age(xmin) <= coalesce(nullif(greatest(pg_catalog.age(?::varchar::xid), ?), ?), ?) and not (prokind = ?) and prolang not in (select lang from system_languages) and prosrc is not null;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jan 16 11 2 0ms 0ms 13 0ms 0ms 0ms 339 0ms commit;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jan 16 11 339 0ms 0ms 14 0ms 0ms 0ms 399 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 #14
Day Hour Count Duration Avg duration Jan 16 11 399 0ms 0ms 15 0ms 0ms 0ms 2 0ms select e.oid as id, e.xmin as state_number, extname as name, extversion as version, extnamespace as schema_id, nspname as schema_name, array ( select unnest from unnest(available_versions) where unnest > extversion) as available_updates from pg_catalog.pg_extension e join pg_namespace n on e.extnamespace = n.oid left join ( select name, array_agg(version) as available_versions from pg_available_extension_versions() group by name) v on e.extname = v.name where pg_catalog.age(e.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?);Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Jan 16 11 2 0ms 0ms 16 0ms 0ms 0ms 238 0ms select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Jan 16 11 238 0ms 0ms 17 0ms 0ms 0ms 2 0ms select a.oid as access_method_id, a.xmin as state_number, a.amname as access_method_name, a.amhandler::oid as handler_id, pg_catalog.quote_ident(n.nspname) || ? || pg_catalog.quote_ident(p.proname) as handler_name, a.amtype as access_method_type from pg_am a join pg_proc p on a.amhandler::oid = p.oid join pg_namespace n on p.pronamespace = n.oid where pg_catalog.age(a.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?);Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Jan 16 11 2 0ms 0ms 18 0ms 0ms 0ms 238 0ms select system_identifier from pg_control_system ();Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Jan 16 11 238 0ms 0ms 19 0ms 0ms 0ms 9 0ms select groupid, exchange, groupname, symbol, longname from prfsymboltree where brokerid = ? order by groupname, symbol;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Jan 16 11 9 0ms 0ms 20 0ms 0ms 0ms 3 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 #20
Day Hour Count Duration Avg duration Jan 16 11 3 0ms 0ms Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 1s746ms 1,376 0ms 3ms 1ms SELECT symbolid, ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Jan 16 11 1,376 1s746ms 1ms -
SELECT symbolid, ;
Date: 2026-01-16 11:47:06 Duration: 3ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-01-16 11:46:03 Duration: 2ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-01-16 11:32:10 Duration: 2ms Database: postgres
2 1s668ms 1,926 0ms 15ms 0ms WITH rar_max as ( ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 11 1,926 1s668ms 0ms -
WITH rar_max as ( ;
Date: 2026-01-16 11:02:36 Duration: 15ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-01-16 11:02:36 Duration: 14ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-01-16 11:25:31 Duration: 10ms Database: postgres
3 838ms 2,533 0ms 10ms 0ms SELECT ;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 11 2,533 838ms 0ms -
SELECT ;
Date: 2026-01-16 11:24:29 Duration: 10ms Database: postgres
-
SELECT ;
Date: 2026-01-16 11:02:36 Duration: 8ms Database: postgres
-
SELECT ;
Date: 2026-01-16 11:24:04 Duration: 7ms Database: postgres
4 680ms 676 0ms 1ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 11 676 680ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-01-16 11:32:03 Duration: 1ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-01-16 11:01:30 Duration: 1ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-01-16 11:31:04 Duration: 1ms Database: postgres
5 289ms 3,185 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 11 3,185 289ms 0ms -
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:01:29 Duration: 0ms Database: postgres
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:42:00 Duration: 0ms Database: postgres
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:41:56 Duration: 0ms Database: postgres
6 246ms 1,852 0ms 3ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #6
Day Hour Count Duration Avg duration 11 1,852 246ms 0ms -
SET extra_float_digits = 3;
Date: 2026-01-16 11:24:04 Duration: 3ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-01-16 11:24:57 Duration: 3ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-01-16 11:24:57 Duration: 1ms Database: postgres
7 195ms 1,974 0ms 0ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 11 1,974 195ms 0ms -
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:01:29 Duration: 0ms Database: postgres
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:03:00 Duration: 0ms Database: postgres
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:47:22 Duration: 0ms Database: postgres
8 189ms 1,279 0ms 0ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #8
Day Hour Count Duration Avg duration 11 1,279 189ms 0ms -
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:17:37 Duration: 0ms Database: postgres
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:42:00 Duration: 0ms Database: postgres
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INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:56:57 Duration: 0ms Database: postgres
9 77ms 12 4ms 7ms 6ms with sym_info as ( ;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 11 12 77ms 6ms -
with sym_info as ( ;
Date: 2026-01-16 11:51:43 Duration: 7ms Database: postgres
-
with sym_info as ( ;
Date: 2026-01-16 11:06:39 Duration: 7ms Database: postgres
-
with sym_info as ( ;
Date: 2026-01-16 11:06:50 Duration: 6ms Database: postgres
10 58ms 998 0ms 6ms 0ms select 1;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 11 998 58ms 0ms -
select 1;
Date: 2026-01-16 11:24:57 Duration: 6ms Database: postgres
-
select 1;
Date: 2026-01-16 11:16:17 Duration: 3ms Database: postgres
-
select 1;
Date: 2026-01-16 11:02:36 Duration: 3ms Database: postgres
11 46ms 18 1ms 4ms 2ms select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 11 18 46ms 2ms -
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-01-16 11:41:03 Duration: 4ms Database: postgres
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-01-16 11:11:02 Duration: 3ms Database: postgres
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-01-16 11:11:02 Duration: 2ms Database: postgres
12 42ms 36 0ms 1ms 1ms select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 11 36 42ms 1ms -
select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2026-01-16 11:21:13 Duration: 1ms Database: postgres
-
select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2026-01-16 11:58:48 Duration: 1ms Database: postgres
-
select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;
Date: 2026-01-16 11:06:27 Duration: 1ms Database: postgres
13 38ms 28 0ms 4ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 11 28 38ms 1ms -
WITH last_candle AS ( ;
Date: 2026-01-16 11:16:00 Duration: 4ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-01-16 11:16:00 Duration: 3ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-01-16 11:32:00 Duration: 3ms Database: postgres
14 33ms 36 0ms 1ms 0ms select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 11 36 33ms 0ms -
select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2026-01-16 11:36:32 Duration: 1ms Database: postgres
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select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2026-01-16 11:46:16 Duration: 1ms Database: postgres
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select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2026-01-16 11:51:16 Duration: 1ms Database: postgres
15 31ms 175 0ms 0ms 0ms SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;Times Reported Time consuming prepare #15
Day Hour Count Duration Avg duration 11 175 31ms 0ms -
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-01-16 11:13:20 Duration: 0ms Database: postgres
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-01-16 11:13:21 Duration: 0ms Database: postgres
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-01-16 11:13:20 Duration: 0ms Database: postgres
16 30ms 217 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 #16
Day Hour Count Duration Avg duration 11 217 30ms 0ms -
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:30:46 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: 2026-01-16 11:01:02 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: 2026-01-16 11:02:03 Duration: 0ms Database: postgres
17 22ms 1,821 0ms 0ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 11 1,821 22ms 0ms -
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-01-16 11:24:29 Duration: 0ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-01-16 11:24:29 Duration: 0ms Database: postgres
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SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-01-16 11:46:15 Duration: 0ms Database: postgres
18 15ms 6 2ms 3ms 2ms select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 11 6 15ms 2ms -
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2026-01-16 11:10:04 Duration: 3ms Database: postgres
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select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2026-01-16 11:40:05 Duration: 3ms Database: postgres
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select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2026-01-16 11:00:05 Duration: 2ms Database: postgres
19 14ms 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 #19
Day Hour Count Duration Avg duration 11 6 14ms 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: 2026-01-16 11:20:02 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: 2026-01-16 11:40:02 Duration: 2ms 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: 2026-01-16 11:00:02 Duration: 2ms Database: postgres
20 13ms 24 0ms 0ms 0ms select count(*) from datafeed_restarter_events where is_current_entry = 1;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 11 24 13ms 0ms -
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2026-01-16 11:00:03 Duration: 0ms Database: postgres
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2026-01-16 11:50:05 Duration: 0ms Database: postgres
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2026-01-16 11:25:00 Duration: 0ms Database: postgres
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 33s413ms 2,742 0ms 61ms 12ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Jan 16 11 2,742 33s413ms 12ms -
WITH rar_max as ( ;
Date: 2026-01-16 11:47:17 Duration: 61ms Database: postgres parameters: $1 = '627', $2 = '7', $3 = '15', $4 = '30', $5 = '60', $6 = '120', $7 = '240', $8 = '480', $9 = '1440', $10 = '0', $11 = '', $12 = '213', $13 = '#ADBE', $14 = '#ALVG', $15 = '#AMZN', $16 = '#APPL', $17 = '#BA', $18 = '#BABA', $19 = '#BAYGn', $20 = '#BMWG', $21 = '#BNPP', $22 = '#CAT', $23 = '#CBKG', $24 = '#DAIGn', $25 = '#DIS', $26 = '#EA', $27 = '#FB', $28 = '#FDX', $29 = '#GE', $30 = '#GM', $31 = '#GOOGL', $32 = '#GS', $33 = '#INTC', $34 = '#JPM', $35 = '#KO', $36 = '#META', $37 = '#MSFT', $38 = '#NFLX', $39 = '#TSLA', $40 = '#VOWG', $41 = '#WMT', $42 = '#XOM', $43 = 'AUDCAD', $44 = 'AUDCHF', $45 = 'AUDJPY', $46 = 'AUDNZD', $47 = 'AUDUSD', $48 = 'AUS_200', $49 = 'BTCEUR', $50 = 'BTCGBP', $51 = 'BTCUSD', $52 = 'CADCHF', $53 = 'CADJPY', $54 = 'CHFJPY', $55 = 'CL_BRENT', $56 = 'DASHUSD', $57 = 'EOSUSD', $58 = 'ESP_35', $59 = 'ETHEUR', $60 = 'ETHGBP', $61 = 'ETHUSD', $62 = 'EURAUD', $63 = 'EURCAD', $64 = 'EURCHF', $65 = 'EURGBP', $66 = 'EURJPY', $67 = 'EURMXN', $68 = 'EURNOK', $69 = 'EURNZD', $70 = 'EURPLN', $71 = 'EURSEK', $72 = 'EURTRY', $73 = 'EURUSD', $74 = 'EUR_50', $75 = 'FRA_40', $76 = 'GBPAUD', $77 = 'GBPCAD', $78 = 'GBPCHF', $79 = 'GBPJPY', $80 = 'GBPNZD', $81 = 'GBPUSD', $82 = 'GBPZAR', $83 = 'GBR_100', $84 = 'HKDJPY', $85 = 'HKG_50', $86 = 'IOTAUSD', $87 = 'LTCEUR', $88 = 'LTCUSD', $89 = 'NAS100', $90 = 'NEOUSD', $91 = 'NOKJPY', $92 = 'NZDCAD', $93 = 'NZDCHF', $94 = 'NZDJPY', $95 = 'NZDUSD', $96 = 'OMGUSD', $97 = 'SPX500', $98 = 'TRXUSD', $99 = 'US30', $100 = 'USDCAD', $101 = 'USDCHF', $102 = 'USDCNH', $103 = 'USDDKK', $104 = 'USDJPY', $105 = 'USDMXN', $106 = 'USDNOK', $107 = 'USDPLN', $108 = 'USDSEK', $109 = 'USDSGD', $110 = 'USDZAR', $111 = 'USOIL', $112 = 'XAGUSD', $113 = 'XAUEUR', $114 = 'XAUUSD', $115 = 'XMRUSD', $116 = 'XPTUSD', $117 = 'XRPUSD', $118 = 'ZARJPY', $119 = 'ZECUSD', $120 = 'AUDCAD', $121 = 'AUDCHF', $122 = 'AUDJPY', $123 = 'AUDNZD', $124 = 'AUDUSD', $125 = 'CADCHF', $126 = 'CADJPY', $127 = 'CHFJPY', $128 = 'EURAUD', $129 = 'EURCAD', $130 = 'EURCHF', $131 = 'EURGBP', $132 = 'EURJPY', $133 = 'EURMXN', $134 = 'EURNOK', $135 = 'EURNZD', $136 = 'EURPLN', $137 = 'EURSEK', $138 = 'EURTRY', $139 = 'EURUSD', $140 = 'GBPAUD', $141 = 'GBPCAD', $142 = 'GBPCHF', $143 = 'GBPJPY', $144 = 'GBPNZD', $145 = 'GBPUSD', $146 = 'GBPZAR', $147 = 'HKDJPY', $148 = 'NOKJPY', $149 = 'NZDCAD', $150 = 'NZDCHF', $151 = 'NZDJPY', $152 = 'NZDUSD', $153 = 'USDCAD', $154 = 'USDCHF', $155 = 'USDCNH', $156 = 'USDDKK', $157 = 'USDJPY', $158 = 'USDMXN', $159 = 'USDNOK', $160 = 'USDPLN', $161 = 'USDSEK', $162 = 'USDSGD', $163 = 'USDZAR', $164 = 'ZARJPY', $165 = 'BTCEUR', $166 = 'BTCGBP', $167 = 'BTCUSD', $168 = 'DASHUSD', $169 = 'EOSUSD', $170 = 'ETHEUR', $171 = 'ETHGBP', $172 = 'ETHUSD', $173 = 'IOTAUSD', $174 = 'LTCEUR', $175 = 'LTCUSD', $176 = 'NEOUSD', $177 = 'OMGUSD', $178 = 'TRXUSD', $179 = 'XMRUSD', $180 = 'XRPUSD', $181 = 'ZECUSD', $182 = 'XAGUSD', $183 = 'XAUEUR', $184 = 'XAUUSD', $185 = 'XPTUSD', $186 = 'CL_BRENT', $187 = 'USOIL', $188 = '#ALVG', $189 = '#BAYGn', $190 = '#BMWG', $191 = '#BNPP', $192 = '#CBKG', $193 = '#DAIGn', $194 = '#VOWG', $195 = 'AUS_200', $196 = 'ESP_35', $197 = 'EUR_50', $198 = 'FRA_40', $199 = 'GBR_100', $200 = 'HKG_50', $201 = 'NAS100', $202 = 'SPX500', $203 = 'US30', $204 = '#ADBE', $205 = '#AMZN', $206 = '#APPL', $207 = '#BA', $208 = '#BABA', $209 = '#CAT', $210 = '#DIS', $211 = '#EA', $212 = '#FB', $213 = '#FDX', $214 = '#GE', $215 = '#GM', $216 = '#GOOGL', $217 = '#GS', $218 = '#INTC', $219 = '#JPM', $220 = '#KO', $221 = '#MSFT', $222 = '#NFLX', $223 = '#TSLA', $224 = '#WMT', $225 = '#XOM', $226 = '500', $227 = '500', $228 = 't', $229 = '10', $230 = '10'
-
WITH rar_max as ( ;
Date: 2026-01-16 11:20:53 Duration: 53ms Database: postgres parameters: $1 = 't', $2 = '621', $3 = '7', $4 = '15', $5 = '30', $6 = '60', $7 = '120', $8 = '240', $9 = '480', $10 = '1440', $11 = '0', $12 = '', $13 = '1', $14 = 'EURUSD', $15 = '0', $16 = '', $17 = '0', $18 = '0', $19 = '0', $20 = '0', $21 = '0', $22 = 't', $23 = '10', $24 = '10'
-
WITH rar_max as ( ;
Date: 2026-01-16 11:46:58 Duration: 53ms 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'
2 7s777ms 19,552 0ms 17ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 11 19,552 7s777ms 0ms -
SELECT ;
Date: 2026-01-16 11:25:31 Duration: 17ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840249414796300'
-
SELECT ;
Date: 2026-01-16 11:47:43 Duration: 16ms Database: postgres parameters: $1 = '538', $2 = '0', $3 = '0', $4 = 'USDCZK', $5 = 'USDCZK'
-
SELECT ;
Date: 2026-01-16 11:25:01 Duration: 15ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840233384199300'
3 3s172ms 1,376 0ms 32ms 2ms SELECT symbolid, ;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 11 1,376 3s172ms 2ms -
SELECT symbolid, ;
Date: 2026-01-16 11:16:05 Duration: 32ms Database: postgres parameters: $1 = 'ATFX', $2 = '15', $3 = '#BAYN'
-
SELECT symbolid, ;
Date: 2026-01-16 11:32:39 Duration: 5ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'BTCUSD', $4 = 'BTCUSO'
-
SELECT symbolid, ;
Date: 2026-01-16 11:16:06 Duration: 4ms Database: postgres parameters: $1 = 'GLOBALGTMT5', $2 = '15', $3 = 'LTCUSD', $4 = 'MATUSD'
4 1s136ms 676 1ms 3ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 11 676 1s136ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-01-16 11:32:03 Duration: 3ms Database: postgres parameters: $1 = 'PEPPERSTONEMT5'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-01-16 11:31:04 Duration: 2ms Database: postgres parameters: $1 = 'ATFX'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-01-16 11:31:04 Duration: 2ms Database: postgres parameters: $1 = 'FPMARKETS'
5 556ms 12 28ms 92ms 46ms with sym_info as ( ;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 11 12 556ms 46ms -
with sym_info as ( ;
Date: 2026-01-16 11:06:41 Duration: 92ms Database: postgres parameters: $1 = '617', $2 = 'Forex', $3 = 'Forex', $4 = '617', $5 = 'Forex', $6 = '617', $7 = '617', $8 = 'Forex', $9 = '617'
-
with sym_info as ( ;
Date: 2026-01-16 11:51:55 Duration: 46ms Database: postgres parameters: $1 = '692', $2 = 'Forex', $3 = 'Forex', $4 = '692', $5 = 'Forex', $6 = '692', $7 = '692', $8 = 'Forex', $9 = '692'
-
with sym_info as ( ;
Date: 2026-01-16 11:06:39 Duration: 45ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
6 532ms 71 4ms 14ms 7ms WITH last_candle AS ( ;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 11 71 532ms 7ms -
WITH last_candle AS ( ;
Date: 2026-01-16 11:36:05 Duration: 14ms Database: postgres parameters: $1 = '667', $2 = '667'
-
WITH last_candle AS ( ;
Date: 2026-01-16 11:32:00 Duration: 13ms Database: postgres parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2026-01-16 11:32:00 Duration: 13ms Database: postgres parameters: $1 = '558', $2 = '558'
7 522ms 23 0ms 102ms 22ms with wh_patitioned as ( ;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 11 23 522ms 22ms -
with wh_patitioned as ( ;
Date: 2026-01-16 11:16:04 Duration: 102ms Database: postgres parameters: $1 = '627', $2 = '627', $3 = '627', $4 = '627', $5 = '627', $6 = '627', $7 = '627', $8 = '627', $9 = '627'
-
with wh_patitioned as ( ;
Date: 2026-01-16 11:26:37 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: 2026-01-16 11:12:15 Duration: 40ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
8 370ms 49 0ms 21ms 7ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 11 49 370ms 7ms -
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-01-16 11:16:25 Duration: 21ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-01-16 11:06:48 Duration: 20ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-01-16 11:22:46 Duration: 18ms Database: postgres parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
9 338ms 15,404 0ms 2ms 0ms select 1;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 11 15,404 338ms 0ms -
select 1;
Date: 2026-01-16 11:24:04 Duration: 2ms Database: postgres
-
select 1;
Date: 2026-01-16 11:32:09 Duration: 1ms Database: postgres
-
select 1;
Date: 2026-01-16 11:48:04 Duration: 1ms Database: postgres
10 279ms 5,946 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 #10
Day Hour Count Duration Avg duration 11 5,946 279ms 0ms -
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:30:46 Duration: 0ms Database: postgres parameters: $1 = '2026-01-16 11:15:00', $2 = '332.328', $3 = '332.416', $4 = '332.016', $5 = '332.091', $6 = '1394', $7 = '515840243222660300', $8 = '0', $9 = '2026-01-16 11:30:46.574', $10 = '2026-01-16 11:30:45.561', $11 = '332.328', $12 = '332.416', $13 = '332.016', $14 = '332.091', $15 = '1394', $16 = '0', $17 = '2026-01-16 11:30:46.574', $18 = '2026-01-16 11:30:45.561'
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:32:29 Duration: 0ms Database: postgres parameters: $1 = '2026-01-16 11:00:00', $2 = '8898.7', $3 = '8898.7', $4 = '8894.3', $5 = '8898.7', $6 = '50', $7 = '515840245910095300', $8 = '0', $9 = '2026-01-16 11:32:29.702', $10 = '2026-01-16 11:32:29.604', $11 = '8898.7', $12 = '8898.7', $13 = '8894.3', $14 = '8898.7', $15 = '50', $16 = '0', $17 = '2026-01-16 11:32:29.702', $18 = '2026-01-16 11:32:29.604'
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:42:00 Duration: 0ms Database: postgres parameters: $1 = '2026-01-16 11:15:00', $2 = '49481.54', $3 = '49503.79', $4 = '49478.29', $5 = '49490.29', $6 = '1827', $7 = '515840248000537300', $8 = '0', $9 = '2026-01-16 11:42:00.173', $10 = '2026-01-16 11:42:00.093', $11 = '49481.54', $12 = '49503.79', $13 = '49478.29', $14 = '49490.29', $15 = '1827', $16 = '0', $17 = '2026-01-16 11:42:00.173', $18 = '2026-01-16 11:42:00.093'
11 266ms 3,361 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 #11
Day Hour Count Duration Avg duration 11 3,361 266ms 0ms -
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:30:46 Duration: 0ms Database: postgres parameters: $1 = '2026-01-16 11:00:00', $2 = '16.386705', $3 = '16.39293', $4 = '16.37769', $5 = '16.386805', $6 = '5973', $7 = '605679104113726300', $8 = '0', $9 = '2026-01-16 11:30:46.349', $10 = '2026-01-16 11:30:46.348', $11 = '16.386705', $12 = '16.39293', $13 = '16.37769', $14 = '16.386805', $15 = '5973', $16 = '0', $17 = '2026-01-16 11:30:46.349', $18 = '2026-01-16 11:30:46.348'
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:42:00 Duration: 0ms Database: postgres parameters: $1 = '2026-01-16 11:00:00', $2 = '49495.34', $3 = '49503.79', $4 = '49474.84', $5 = '49490.29', $6 = '3886', $7 = '515840248000726300', $8 = '0', $9 = '2026-01-16 11:42:00.193', $10 = '2026-01-16 11:42:00.099', $11 = '49495.34', $12 = '49503.79', $13 = '49474.84', $14 = '49490.29', $15 = '3886', $16 = '0', $17 = '2026-01-16 11:42:00.193', $18 = '2026-01-16 11:42:00.099'
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INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:41:56 Duration: 0ms Database: postgres parameters: $1 = '2026-01-16 10:00:00', $2 = '26776.3', $3 = '26834.8', $4 = '26771.3', $5 = '26792.8', $6 = '6389', $7 = '515840247933633300', $8 = '0', $9 = '2026-01-16 11:41:56.128', $10 = '2026-01-16 11:41:56.04', $11 = '26776.3', $12 = '26834.8', $13 = '26771.3', $14 = '26792.8', $15 = '6389', $16 = '0', $17 = '2026-01-16 11:41:56.128', $18 = '2026-01-16 11:41:56.04'
12 180ms 2,153 0ms 2ms 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 11 2,153 180ms 0ms -
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:32:02 Duration: 2ms Database: postgres parameters: $1 = '2026-01-15 22:00:00', $2 = '491.18', $3 = '493.07', $4 = '491.18', $5 = '492.585', $6 = '1842', $7 = '605633962164073300', $8 = '0', $9 = '2026-01-16 11:32:02.025', $10 = '2026-01-16 11:32:02.024', $11 = '491.18', $12 = '493.07', $13 = '491.18', $14 = '492.585', $15 = '1842', $16 = '0', $17 = '2026-01-16 11:32:02.025', $18 = '2026-01-16 11:32:02.024'
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:01:37 Duration: 0ms Database: postgres parameters: $1 = '2026-01-16 10:00:00', $2 = '4606.84', $3 = '4610.75', $4 = '4601.4', $5 = '4603.3', $6 = '8410', $7 = '515840230627943300', $8 = '0', $9 = '2026-01-16 11:01:37.524', $10 = '2026-01-16 11:01:37.523', $11 = '4606.84', $12 = '4610.75', $13 = '4601.4', $14 = '4603.3', $15 = '8410', $16 = '0', $17 = '2026-01-16 11:01:37.524', $18 = '2026-01-16 11:01:37.523'
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INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:15:46 Duration: 0ms Database: postgres parameters: $1 = '2026-01-15 19:00:00', $2 = '54290', $3 = '54315', $4 = '54230', $5 = '54230', $6 = '756', $7 = '515840230561416300', $8 = '0', $9 = '2026-01-16 11:15:46.769', $10 = '2026-01-16 11:15:46.757', $11 = '54290', $12 = '54315', $13 = '54230', $14 = '54230', $15 = '756', $16 = '0', $17 = '2026-01-16 11:15:46.769', $18 = '2026-01-16 11:15:46.757'
13 85ms 92 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 #13
Day Hour Count Duration Avg duration 11 92 85ms 0ms -
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2026-01-16 11:30:57 Duration: 1ms Database: postgres parameters: $1 = '632', $2 = 'GBPUSD', $3 = '632'
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SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2026-01-16 11:32:27 Duration: 1ms Database: postgres parameters: $1 = '689', $2 = 'AUDUSD.c', $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: 2026-01-16 11:31:50 Duration: 1ms Database: postgres parameters: $1 = '689', $2 = 'XAUUSD', $3 = '689'
14 80ms 175 0ms 2ms 0ms SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 11 175 80ms 0ms -
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-01-16 11:13:20 Duration: 2ms Database: postgres
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-01-16 11:13:21 Duration: 1ms Database: postgres
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-01-16 11:13:20 Duration: 1ms Database: postgres
15 51ms 437 0ms 1ms 0ms select category, ;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 11 437 51ms 0ms -
select category, ;
Date: 2026-01-16 11:21:34 Duration: 1ms Database: postgres parameters: $1 = '604104683406582307', $2 = 'symbol', $3 = 'AUDJPY', $4 = 'CADJPY', $5 = 'GBPJPY', $6 = 'NZDJPY', $7 = 'CHFJPY', $8 = 'EURJPY', $9 = 'GBPAUD', $10 = 'GBPNZD', $11 = 'EURNZD', $12 = 'EURAUD', $13 = 'GBPCAD', $14 = 'EURGBP', $15 = 'EURCAD', $16 = 'GBPCAD', $17 = 'USDSGD', $18 = 'CADJPY', $19 = 'EURNZD', $20 = 'CADCHF', $21 = 'AUDNZD', $22 = 'EURCAD', $23 = 'GBPCHF', $24 = 'AUDJPY', $25 = 'NZDUSD', $26 = 'NZDJPY', $27 = 'EURCHF', $28 = 'EURJPY', $29 = 'AUDCHF', $30 = 'GBPJPY', $31 = 'GBPCHF', $32 = 'NZDCHF', $33 = 'AUDCAD', $34 = 'NZDCAD', $35 = 'NZDCAD', $36 = 'GBPAUD', $37 = 'CHFJPY', $38 = 'GBPNZD', $39 = 'EURAUD', $40 = 'USDSGD', $41 = 'AUDCAD', $42 = 'NZDUSD', $43 = 'AUDCHF', $44 = 'EURCHF', $45 = 'CADCHF', $46 = 'NZDCHF', $47 = 'AUDNZD', $48 = 'EURGBP', $49 = '604104683406582307', $50 = 'symbol', $51 = 'AUDJPY', $52 = 'CADJPY', $53 = 'GBPJPY', $54 = 'NZDJPY', $55 = 'CHFJPY', $56 = 'EURJPY', $57 = 'GBPAUD', $58 = 'GBPNZD', $59 = 'EURNZD', $60 = 'EURAUD', $61 = 'GBPCAD', $62 = 'EURGBP', $63 = 'EURCAD', $64 = 'GBPCAD', $65 = 'USDSGD', $66 = 'CADJPY', $67 = 'EURNZD', $68 = 'CADCHF', $69 = 'AUDNZD', $70 = 'EURCAD', $71 = 'GBPCHF', $72 = 'AUDJPY', $73 = 'NZDUSD', $74 = 'NZDJPY', $75 = 'EURCHF', $76 = 'EURJPY', $77 = 'AUDCHF', $78 = 'GBPJPY', $79 = 'GBPCHF', $80 = 'NZDCHF', $81 = 'AUDCAD', $82 = 'NZDCAD', $83 = 'NZDCAD', $84 = 'GBPAUD', $85 = 'CHFJPY', $86 = 'GBPNZD', $87 = 'EURAUD', $88 = 'USDSGD', $89 = 'AUDCAD', $90 = 'NZDUSD', $91 = 'AUDCHF', $92 = 'EURCHF', $93 = 'CADCHF', $94 = 'NZDCHF', $95 = 'AUDNZD', $96 = 'EURGBP'
-
select category, ;
Date: 2026-01-16 11:48:01 Duration: 0ms Database: postgres parameters: $1 = '605633814906094307', $2 = 'symbol', $3 = 'INTC.US', $4 = 'BABA.US', $5 = 'TSLA.US', $6 = 'PYPL.US', $7 = 'AMD.US', $8 = 'AMZN.US', $9 = 'V.US', $10 = 'NVDA.US', $11 = 'NKE.US', $12 = 'MSFT.US', $13 = 'META.US', $14 = 'BRK.B.US', $15 = 'NFLX.US', $16 = 'AAPL.US', $17 = 'GOOG.US', $18 = 'NVDA.US', $19 = 'BRK.B.US', $20 = 'INTC.US', $21 = 'NKE.US', $22 = 'AMZN.US', $23 = 'NFLX.US', $24 = 'BABA.US', $25 = 'PYPL.US', $26 = 'TSLA.US', $27 = 'GOOG.US', $28 = 'AMD.US', $29 = 'META.US', $30 = 'AAPL.US', $31 = 'V.US', $32 = 'MSFT.US', $33 = '605633814906094307', $34 = 'symbol', $35 = 'INTC.US', $36 = 'BABA.US', $37 = 'TSLA.US', $38 = 'PYPL.US', $39 = 'AMD.US', $40 = 'AMZN.US', $41 = 'V.US', $42 = 'NVDA.US', $43 = 'NKE.US', $44 = 'MSFT.US', $45 = 'META.US', $46 = 'BRK.B.US', $47 = 'NFLX.US', $48 = 'AAPL.US', $49 = 'GOOG.US', $50 = 'NVDA.US', $51 = 'BRK.B.US', $52 = 'INTC.US', $53 = 'NKE.US', $54 = 'AMZN.US', $55 = 'NFLX.US', $56 = 'BABA.US', $57 = 'PYPL.US', $58 = 'TSLA.US', $59 = 'GOOG.US', $60 = 'AMD.US', $61 = 'META.US', $62 = 'AAPL.US', $63 = 'V.US', $64 = 'MSFT.US'
-
select category, ;
Date: 2026-01-16 11:48:13 Duration: 0ms Database: postgres parameters: $1 = '605634061978417307', $2 = 'symbol', $3 = 'AUDJPY', $4 = 'USDJPY', $5 = 'EURMXN', $6 = 'EURJPY', $7 = 'GBPJPY', $8 = 'USDMXN', $9 = 'GBPUSD', $10 = 'EURAUD', $11 = 'USDCAD', $12 = 'EURUSD', $13 = 'NZDUSD', $14 = 'AUDUSD', $15 = 'EURCHF', $16 = 'USDCHF', $17 = 'AUDCAD', $18 = 'USDCAD', $19 = 'EURGBP', $20 = 'EURGBP', $21 = 'NZDUSD', $22 = 'GBPUSD', $23 = 'USDMXN', $24 = 'GBPJPY', $25 = 'EURCHF', $26 = 'AUDCAD', $27 = 'USDCHF', $28 = 'EURJPY', $29 = 'EURMXN', $30 = 'AUDUSD', $31 = 'USDJPY', $32 = 'EURAUD', $33 = 'AUDJPY', $34 = 'EURUSD', $35 = '605634061978417307', $36 = 'symbol', $37 = 'AUDJPY', $38 = 'USDJPY', $39 = 'EURMXN', $40 = 'EURJPY', $41 = 'GBPJPY', $42 = 'USDMXN', $43 = 'GBPUSD', $44 = 'EURAUD', $45 = 'USDCAD', $46 = 'EURUSD', $47 = 'NZDUSD', $48 = 'AUDUSD', $49 = 'EURCHF', $50 = 'USDCHF', $51 = 'AUDCAD', $52 = 'USDCAD', $53 = 'EURGBP', $54 = 'EURGBP', $55 = 'NZDUSD', $56 = 'GBPUSD', $57 = 'USDMXN', $58 = 'GBPJPY', $59 = 'EURCHF', $60 = 'AUDCAD', $61 = 'USDCHF', $62 = 'EURJPY', $63 = 'EURMXN', $64 = 'AUDUSD', $65 = 'USDJPY', $66 = 'EURAUD', $67 = 'AUDJPY', $68 = 'EURUSD'
16 49ms 11 3ms 5ms 4ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #16
Day Hour Count Duration Avg duration 11 11 49ms 4ms -
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-01-16 11:06:03 Duration: 5ms Database: postgres parameters: $1 = '627', $2 = '627'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-01-16 11:27:45 Duration: 5ms Database: postgres parameters: $1 = '538', $2 = '538'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-01-16 11:47:43 Duration: 5ms Database: postgres parameters: $1 = '538', $2 = '538'
17 45ms 8 2ms 10ms 5ms WITH pre_symbols AS ( /* find relevant symbols */ ;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 11 8 45ms 5ms -
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2026-01-16 11:13:19 Duration: 10ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2026-01-16 11:13:19 Duration: 9ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2026-01-16 11:13:19 Duration: 7ms Database: postgres parameters: $1 = '1018', $2 = 'ICMARKETS-AU-MT5', $3 = 'AAPL.NAS', $4 = 'ABBV.NYSE', $5 = 'AMCR.NYSE', $6 = 'AMP.NYSE', $7 = 'AMZN.NAS', $8 = 'ANZ.ASX', $9 = 'AUDJPY', $10 = 'AUDUSD', $11 = 'AUS200', $12 = 'BABA.NYSE', $13 = 'BIIB.NAS', $14 = 'BXB.ASX', $15 = 'CBA.ASX', $16 = 'CHINA50', $17 = 'CSL.ASX', $18 = 'DE30', $19 = 'ES35', $20 = 'EURCHF', $21 = 'EURGBP', $22 = 'EURUSD', $23 = 'F40', $24 = 'FMG.ASX', $25 = 'GBPJPY', $26 = 'GBPUSD', $27 = 'GOOG.NAS', $28 = 'HK50', $29 = 'IT40', $30 = 'JP225', $31 = 'KO.NYSE', $32 = 'MQG.ASX', $33 = 'MSFT.NAS', $34 = 'NAB.ASX', $35 = 'NFLX.NAS', $36 = 'PYPL.NAS', $37 = 'QBE.ASX', $38 = 'STOXX50', $39 = 'SUN.ASX', $40 = 'TCL.ASX', $41 = 'TLS.ASX', $42 = 'TSLA.NAS', $43 = 'UK100', $44 = 'UNH.NYSE', $45 = 'US2000', $46 = 'US30', $47 = 'US500', $48 = 'USDCAD', $49 = 'USDCHF', $50 = 'USDCNH', $51 = 'USDJPY', $52 = 'USTEC', $53 = 'WBC.ASX', $54 = 'WES.ASX', $55 = 'WOW.ASX', $56 = 'WPL.ASX', $57 = 'XAUEUR', $58 = 'XAUUSD', $59 = 'XBRUSD', $60 = 'XTIUSD', $61 = 'AAPL.NAS', $62 = 'ABBV.NYSE', $63 = 'AMCR.NYSE', $64 = 'AMP.NYSE', $65 = 'AMZN.NAS', $66 = 'ANZ.ASX', $67 = 'AUDJPY', $68 = 'AUDUSD', $69 = 'AUS200', $70 = 'BABA.NYSE', $71 = 'BIIB.NAS', $72 = 'BXB.ASX', $73 = 'CBA.ASX', $74 = 'CHINA50', $75 = 'CSL.ASX', $76 = 'DE30', $77 = 'ES35', $78 = 'EURCHF', $79 = 'EURGBP', $80 = 'EURUSD', $81 = 'F40', $82 = 'FMG.ASX', $83 = 'GBPJPY', $84 = 'GBPUSD', $85 = 'GOOG.NAS', $86 = 'HK50', $87 = 'IT40', $88 = 'JP225', $89 = 'KO.NYSE', $90 = 'MQG.ASX', $91 = 'MSFT.NAS', $92 = 'NAB.ASX', $93 = 'NFLX.NAS', $94 = 'PYPL.NAS', $95 = 'QBE.ASX', $96 = 'STOXX50', $97 = 'SUN.ASX', $98 = 'TCL.ASX', $99 = 'TLS.ASX', $100 = 'TSLA.NAS', $101 = 'UK100', $102 = 'UNH.NYSE', $103 = 'US2000', $104 = 'US30', $105 = 'US500', $106 = 'USDCAD', $107 = 'USDCHF', $108 = 'USDCNH', $109 = 'USDJPY', $110 = 'USTEC', $111 = 'WBC.ASX', $112 = 'WES.ASX', $113 = 'WOW.ASX', $114 = 'WPL.ASX', $115 = 'XAUEUR', $116 = 'XAUUSD', $117 = 'XBRUSD', $118 = 'XTIUSD', $119 = '5'
18 42ms 1 42ms 42ms 42ms with maxwhid as ( ;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 11 1 42ms 42ms -
with maxwhid as ( ;
Date: 2026-01-16 11:13:39 Duration: 42ms 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'
19 35ms 2 13ms 22ms 17ms with saved_age as ( select greatest (pg_catalog.age($1::varchar::xid), pg_catalog.age($2::varchar::xid)) as "value");Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 11 2 35ms 17ms -
with saved_age as ( select greatest (pg_catalog.age($1::varchar::xid), pg_catalog.age($2::varchar::xid)) as "value");
Date: 2026-01-16 11:29:45 Duration: 22ms Database: postgres parameters: $1 = '768814720', $2 = '768814720', $3 = '2200', $4 = '2200', $5 = '2200', $6 = '2200', $7 = '2200', $8 = '2200', $9 = '2200', $10 = '2200', $11 = '2200', $12 = '2200', $13 = '2200', $14 = '2200', $15 = '2200', $16 = '2200', $17 = '2200', $18 = '2200', $19 = '2200'
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with saved_age as ( select greatest (pg_catalog.age($1::varchar::xid), pg_catalog.age($2::varchar::xid)) as "value");
Date: 2026-01-16 11:34:21 Duration: 13ms Database: postgres parameters: $1 = '776979023', $2 = '776979023', $3 = '2200', $4 = '2200', $5 = '2200', $6 = '2200', $7 = '2200', $8 = '2200', $9 = '2200', $10 = '2200', $11 = '2200', $12 = '2200', $13 = '2200', $14 = '2200', $15 = '2200', $16 = '2200', $17 = '2200', $18 = '2200', $19 = '2200'
20 34ms 217 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 #20
Day Hour Count Duration Avg duration 11 217 34ms 0ms -
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:01:36 Duration: 0ms Database: postgres parameters: $1 = '2026-01-16 08:00:00', $2 = '15075517', $3 = '15172282.5', $4 = '15074677', $5 = '15135276', $6 = '18432', $7 = '515840249393808300', $8 = '0', $9 = '2026-01-16 11:01:36.7', $10 = '2026-01-16 11:01:36.699', $11 = '15075517', $12 = '15172282.5', $13 = '15074677', $14 = '15135276', $15 = '18432', $16 = '0', $17 = '2026-01-16 11:01:36.7', $18 = '2026-01-16 11:01:36.699'
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INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:15:46 Duration: 0ms Database: postgres parameters: $1 = '2026-01-15 16:00:00', $2 = '54380', $3 = '54430', $4 = '54185', $5 = '54230', $6 = '3968', $7 = '515840230561612300', $8 = '0', $9 = '2026-01-16 11:15:46.764', $10 = '2026-01-16 11:15:46.764', $11 = '54380', $12 = '54430', $13 = '54185', $14 = '54230', $15 = '3968', $16 = '0', $17 = '2026-01-16 11:15:46.764', $18 = '2026-01-16 11:15:46.764'
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INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-16 11:01:26 Duration: 0ms Database: postgres parameters: $1 = '2026-01-16 08:00:00', $2 = '90.8755', $3 = '91.891', $4 = '89.889', $5 = '91.19', $6 = '35199', $7 = '515840249469200300', $8 = '0', $9 = '2026-01-16 11:01:26.653', $10 = '2026-01-16 11:01:26.653', $11 = '90.8755', $12 = '91.891', $13 = '89.889', $14 = '91.19', $15 = '35199', $16 = '0', $17 = '2026-01-16 11:01:26.653', $18 = '2026-01-16 11:01:26.653'
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Events
Log levels
Key values
- 351,943 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 37 ERROR entries
- 0 WARNING entries
Most Frequent Errors/Events
Key values
- 34 Max number of times the same event was reported
- 37 Total events found
Rank Times reported Error 1 34 ERROR: function fixcandlegaps(...) is not unique
Times Reported Most Frequent Error / Event #1
Day Hour Count Jan 16 11 34 - ERROR: function fixcandlegaps(unknown, boolean) is not unique at character 8
Hint: Could not choose a best candidate function. You might need to add explicit type casts.
Statement: select fixcandlegaps('GLOBALFXMT5', false);Date: 2026-01-16 11:06:01
2 2 ERROR: relation "..." does not exist
Times Reported Most Frequent Error / Event #2
Day Hour Count Jan 16 11 2 - ERROR: relation "t0" does not exist at character 83
Statement: SELECT * FROM ( SELECT PriceDateTime, Open, High, Low, Close, Volume, BSF FROM T0 WHERE symbolid = $1 AND (BSF = 0 OR BSF IS NULL) ORDER BY PriceDateTime DESC LIMIT 1050 ) a ORDER BY PriceDateTime ASC
Date: 2026-01-16 11:10:12
3 1 ERROR: role "..." does not exist
Times Reported Most Frequent Error / Event #3
Day Hour Count Jan 16 11 1 - ERROR: role "readaccess_options" does not exist
Statement: grant select on brokers_best5trades_pricing_mv to readaccess_options
Date: 2026-01-16 11:29:34