-
Global information
- Generated on Thu Jan 15 07:59:53 2026
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2026-01-15_090000.log
- Parsed 2,233,232 log entries in 52s
- Log start from 2026-01-15 09:00:00 to 2026-01-15 09:59:51
-
Overview
Global Stats
- 327 Number of unique normalized queries
- 251,248 Number of queries
- 1h45m35s Total query duration
- 2026-01-15 09:00:00 First query
- 2026-01-15 09:59:51 Last query
- 4,262 queries/s at 2026-01-15 09:00:52 Query peak
- 1h45m35s Total query duration
- 6s325ms Prepare/parse total duration
- 42s298ms Bind total duration
- 1h44m46s Execute total duration
- 34 Number of events
- 1 Number of unique normalized events
- 34 Max number of times the same event was reported
- 0 Number of cancellation
- 42 Total number of automatic vacuums
- 55 Total number of automatic analyzes
- 865 Number temporary file
- 592.02 MiB Max size of temporary file
- 6.78 MiB Average size of temporary file
- 3,073 Total number of sessions
- 13 sessions at 2026-01-15 09:58:48 Session peak
- 14d7h28m1s Total duration of sessions
- 6m42s Average duration of sessions
- 81 Average queries per session
- 2s61ms Average queries duration per session
- 6m40s Average idle time per session
- 3,079 Total number of connections
- 40 connections/s at 2026-01-15 09:11:42 Connection peak
- 3 Total number of databases
SQL Traffic
Key values
- 4,262 queries/s Query Peak
- 2026-01-15 09:00:52 Date
SELECT Traffic
Key values
- 1,985 queries/s Query Peak
- 2026-01-15 09:00:52 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 239 queries/s Query Peak
- 2026-01-15 09:00:39 Date
Queries duration
Key values
- 1h45m35s 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 15 09 251,248 0ms 48s980ms 25ms 4m25s 5m17s 5m52s Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jan 15 09 77,524 26 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jan 15 09 31,576 3,140 16 96 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Jan 15 09 20,202 93,052 4.61 16.69% Day Hour Count Average / Second Jan 15 09 3,079 0.86/s Day Hour Count Average Duration Average idle time Jan 15 09 3,073 6m42s 6m40s -
Connections
Established Connections
Key values
- 40 connections Connection Peak
- 2026-01-15 09:11:42 Date
Connections per database
Key values
- acaweb_fx Main Database
- 3,079 connections Total
Connections per user
Key values
- postgres Main User
- 3,079 connections Total
Connections per host
Key values
- 192.168.4.142 Main host with 1274 connections
- 3,079 Total connections
Host Count 127.0.0.1 113 182.165.1.54 2 192.168.0.114 4 192.168.0.216 101 192.168.0.74 307 192.168.0.84 2 192.168.1.127 46 192.168.1.131 2 192.168.1.145 62 192.168.1.15 88 192.168.1.20 86 192.168.1.231 10 192.168.1.238 2 192.168.1.239 2 192.168.1.90 80 192.168.2.126 72 192.168.2.182 12 192.168.2.82 48 192.168.3.199 36 192.168.4.134 1 192.168.4.142 1,274 192.168.4.150 10 192.168.4.212 4 192.168.4.222 1 192.168.4.238 8 192.168.4.33 98 192.168.4.89 4 192.168.4.98 330 [local] 274 -
Sessions
Simultaneous sessions
Key values
- 13 sessions Session Peak
- 2026-01-15 09:58:48 Date
Histogram of session times
Key values
- 2,500 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 3,073 sessions Total
Sessions per user
Key values
- postgres Main User
- 3,073 sessions Total
Sessions per host
Key values
- 192.168.4.142 Main Host
- 3,073 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 113 6s970ms 61ms 182.165.1.54 2 18h8m 9h4m 192.168.0.114 4 20m1s 5m 192.168.0.216 101 1m2s 616ms 192.168.0.74 309 1d19h53m2s 8m31s 192.168.0.84 2 23h59m20s 11h59m40s 192.168.1.127 46 14s505ms 315ms 192.168.1.131 2 23h59m19s 11h59m39s 192.168.1.145 63 2d13h48m57s 58m52s 192.168.1.15 88 1d14h11s 25m54s 192.168.1.20 87 3d16h52m15s 1h1m17s 192.168.1.238 2 23h59m23s 11h59m41s 192.168.1.239 2 12ms 6ms 192.168.1.90 80 36s229ms 452ms 192.168.2.126 72 17s314ms 240ms 192.168.2.182 12 1s78ms 89ms 192.168.2.82 48 8s980ms 187ms 192.168.3.199 36 1s349ms 37ms 192.168.4.134 1 230ms 230ms 192.168.4.142 1,274 9m34s 450ms 192.168.4.150 10 20h7m26s 2h44s 192.168.4.212 4 24s472ms 6s118ms 192.168.4.222 1 40s138ms 40s138ms 192.168.4.238 8 9s853ms 1s231ms 192.168.4.33 98 3m32s 2s168ms 192.168.4.89 4 38ms 9ms 192.168.4.98 330 16s823ms 50ms [local] 274 2m54s 638ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 11,715 buffers Checkpoint Peak
- 2026-01-15 09:05:26 Date
- 209.928 seconds Highest write time
- 0.017 seconds Sync time
Checkpoints Wal files
Key values
- 5 files Wal files usage Peak
- 2026-01-15 09:05:26 Date
Checkpoints distance
Key values
- 149.98 Mo Distance Peak
- 2026-01-15 09:05:26 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Jan 15 09 59,848 2,018.543s 0.081s 2,018.933s Day Hour Added Removed Recycled Synced files Longest sync Average sync Jan 15 09 0 0 27 2,012 0.005s 0s Day Hour Count Avg time (sec) Jan 15 09 0 0s Day Hour Mean distance Mean estimate Jan 15 09 37,381.17 kB 146,531.00 kB -
Temporary Files
Size of temporary files
Key values
- 592.02 MiB Temp Files size Peak
- 2026-01-15 09:14:37 Date
Number of temporary files
Key values
- 62 per second Temp Files Peak
- 2026-01-15 09:47:08 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Jan 15 09 865 5.73 GiB 6.78 MiB Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 39 127.84 MiB 3.02 MiB 3.80 MiB 3.28 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)) AND ($226 = 0 OR ccr.patternlengthbars <= $227)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results WHERE (FALSE = $228 OR relevant = 1) AND ($229 = 0 OR age <= $230) ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2026-01-15 09:01:23 Duration: 0ms
2 26 1.65 GiB 11.34 MiB 166.44 MiB 64.85 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: 2026-01-15 09:10:05 Duration: 0ms
3 25 204.39 MiB 3.17 MiB 9.14 MiB 8.18 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: 2026-01-15 09:00:30 Duration: 0ms
4 16 617.88 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: 2026-01-15 09:01:13 Duration: 0ms
5 16 1.11 GiB 70.89 MiB 70.90 MiB 70.90 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: 2026-01-15 09:01:17 Duration: 0ms
6 11 33.22 MiB 3.02 MiB 3.02 MiB 3.02 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: 2026-01-15 09:04:11 Duration: 0ms
7 8 992.51 MiB 124.03 MiB 124.09 MiB 124.06 MiB select updateresultsmaterializedview ();-
select updateresultsmaterializedview ();
Date: 2026-01-15 09:02:20 Duration: 0ms
8 4 357.36 MiB 89.25 MiB 89.45 MiB 89.34 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2026-01-15 09:02:07 Duration: 0ms
9 1 3.02 MiB 3.02 MiB 3.02 MiB 3.02 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: 2026-01-15 09:16:09 Duration: 0ms
10 1 3.02 MiB 3.02 MiB 3.02 MiB 3.02 MiB 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 = ?;-
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 = $1 AND bsl.symbolid = s.symbolid LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = $2 AND bim.TYPE = 'OUTBOUND' WHERE s.symbolid = $3;
Date: 2026-01-15 09:13:03 Duration: 0ms
11 1 3.02 MiB 3.02 MiB 3.02 MiB 3.02 MiB select row_number() over (partition by symbol, a.basegroupname order by resultuid desc) as rn, * from ( select whp.resultuid, g.basegroupname, whp.type, whid, whp.exchange, coalesce(bim.code, whp.symbol) as symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset as timezoneoffset, ar.patternlengthbars as length, ar.patternquality as quality, breakout, cps.pip from whatshot_probability whp inner join autochartist_results ar on whp.resultuid = ar.resultuid inner join relevance_autochartist_results rar on ar.resultuid = rar.resultuid inner join downloadersymbolsettings dss on ar.symbolid = dss.symbolid inner join datafeedstimetable dftt on dss.classname = dftt.classname inner join symbols s on whp.symbolid = s.symbolid inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join whatshot_groups whg on whg.groupid = g.groupid inner join brokersymbollist bsl on bsl.symbolid = sg.symbolid and bsl.brokerid = ? inner join brokergroups bg on bg.groupid = sg.groupid and 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 whid = ( select max(whid) from whatshot where brokerid = ?) and interval >= ? and percent >= ? and whp.type = ? and rar.relevant = ? and rar.age <= ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and ar.patternlengthbars < ? and dftt.dayofweek = ?) a), wh_patitioned2 as ( select row_number() over (partition by symbol, a2.basegroupname order by resultuid desc) as rn, * from ( select whp.resultuid, g.basegroupname, whp.type, whid, whp.exchange, coalesce(bim.code, whp.symbol) as symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality, ar.breakout, cps.pip from whatshot_probability whp inner join keylevels_results ar on whp.resultuid = ar.resultuid inner join relevance_keylevels_results rar on ar.resultuid = rar.resultuid inner join downloadersymbolsettings dss on ar.symbolid = dss.symbolid inner join datafeedstimetable dftt on dss.classname = dftt.classname inner join symbols s on whp.symbolid = s.symbolid inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join whatshot_groups whg on whg.groupid = g.groupid inner join brokersymbollist bsl on bsl.symbolid = sg.symbolid and bsl.brokerid = ? inner join brokergroups bg on bg.groupid = sg.groupid and 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 whid = ( select max(whid) from whatshot where brokerid = ?) and interval >= ? and percent >= ? and whp.type = ? and rar.relevant = ? and rar.age <= ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and ar.patternlengthbars < ? and dftt.dayofweek = ?) a2), wh_patitioned3 as ( select row_number() over (partition by symbol, a3.basegroupname order by resultuid desc) as rn, * from ( select whp.resultuid, g.basegroupname, whp.type, whid, whp.exchange, coalesce(bim.code, whp.symbol) as symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime as patternendtime, patternprice as predictionpricefrom, patternprice as predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality, ar.breakout, cps.pip from whatshot_probability whp inner join keylevels_results ar on whp.resultuid = ar.resultuid inner join relevance_keylevels_results rar on ar.resultuid = rar.resultuid inner join downloadersymbolsettings dss on ar.symbolid = dss.symbolid inner join datafeedstimetable dftt on dss.classname = dftt.classname inner join symbols s on whp.symbolid = s.symbolid inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join whatshot_groups whg on whg.groupid = g.groupid inner join brokersymbollist bsl on bsl.symbolid = sg.symbolid and bsl.brokerid = ? inner join brokergroups bg on bg.groupid = sg.groupid and 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 whid = ( select max(whid) from whatshot where brokerid = ?) and interval >= ? and percent >= ? and whp.type = ? and rar.relevant = ? and rar.age <= ? and s.nonliquid = ? and s.deleted = ? and dss.enabled = ? and ar.patternlengthbars < ? and dftt.dayofweek = ?) a3 ) select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, timezoneoffset, length, quality, breakout, pip from wh_patitioned where rn = ? union all select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality, breakout, pip from wh_patitioned2 where rn = ? union all select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality, breakout, pip from wh_patitioned3 where rn = ?;-
select row_number() over (partition by symbol, a.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, whp.type, whid, whp.exchange, coalesce(bim.code, whp.symbol) as symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset as timezoneoffset, ar.patternlengthbars as length, ar.patternquality as quality, breakout, cps.pip FROM whatshot_probability whp INNER JOIN autochartist_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_autochartist_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $1 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $2 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 whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $3) AND interval >= 60 AND percent >= 60 AND whp.type = 'cp' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND ar.patternlengthbars < 400 and dftt.dayofweek = 3) a), wh_patitioned2 as ( select row_number() over (partition by symbol, a2.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, whp.type, whid, whp.exchange, coalesce(bim.code, whp.symbol) as symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime as patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality, ar.breakout, cps.pip FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $4 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $5 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 whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $6) AND interval >= 60 AND percent >= 60 AND whp.type = 'kl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND ar.patternlengthbars < 400 and dftt.dayofweek = 3) a2), wh_patitioned3 as ( select row_number() over (partition by symbol, a3.basegroupname order by resultuid desc) as rn, * from ( SELECT whp.resultuid, g.basegroupname, whp.type, whid, whp.exchange, coalesce(bim.code, whp.symbol) as symbol, patternname, whp.direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime as patternendtime, patternprice as predictionpricefrom, patternprice as predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, rar.age, dftt.timezone, dftt.absolutetimezoneoffset, ar.patternlengthbars as length, ar.qtytp as quality, ar.breakout, cps.pip FROM whatshot_probability whp INNER JOIN keylevels_results ar ON whp.resultuid = ar.resultuid INNER JOIN relevance_keylevels_results rar ON ar.resultuid = rar.resultuid INNER JOIN downloadersymbolsettings dss ON ar.symbolid = dss.symbolid INNER JOIN datafeedstimetable dftt ON dss.classname = dftt.classname INNER JOIN symbols s on whp.symbolid = s.symbolid INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN whatshot_groups whg ON whg.groupid = g.groupid INNER JOIN brokersymbollist bsl ON bsl.symbolid = sg.symbolid AND bsl.brokerid = $7 INNER JOIN brokergroups bg ON bg.groupid = sg.groupid AND bg.brokerid = $8 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 whid = ( SELECT MAX(whid) FROM whatshot WHERE brokerid = $9) AND interval >= 60 AND percent >= 60 AND whp.type = 'ekl' AND rar.relevant = 1 AND rar.age <= 10 and s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND ar.patternlengthbars < 400 and dftt.dayofweek = 3) a3 ) select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, timezoneoffset, length, quality, breakout, pip from wh_patitioned where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality, breakout, pip from wh_patitioned2 where rn = 1 UNION ALL select resultuid, basegroupname, type, whid, exchange, symbol, patternname, direction, hod, interval, symbol_percent, pattern_percent, hod_percent, percent, new, patternendtime, predictionpricefrom, predictionpriceto, pattern_correct, pattern_total, hod_correct, hod_total, symbol_correct, symbol_total, age, timezone, absolutetimezoneoffset, length, quality, breakout, pip from wh_patitioned3 where rn = 1;
Date: 2026-01-15 09:08:26 Duration: 0ms
Queries generating the largest temporary files
Rank Size Query 1 166.44 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: 2026-01-15 09:00:05 ]
2 162.48 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: 2026-01-15 09:10:05 ]
3 162.22 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: 2026-01-15 09:40:04 ]
4 124.09 MiB select updateresultsmaterializedview ();[ Date: 2026-01-15 09:47:12 ]
5 124.09 MiB select updateresultsmaterializedview ();[ Date: 2026-01-15 09:02:20 ]
6 124.08 MiB select updateresultsmaterializedview ();[ Date: 2026-01-15 09:32:14 ]
7 124.08 MiB select updateresultsmaterializedview ();[ Date: 2026-01-15 09:50:32 ]
8 124.06 MiB select updateresultsmaterializedview ();[ Date: 2026-01-15 09:35:32 ]
9 124.05 MiB select updateresultsmaterializedview ();[ Date: 2026-01-15 09:17:11 ]
10 124.04 MiB select updateresultsmaterializedview ();[ Date: 2026-01-15 09:20:32 ]
11 124.03 MiB select updateresultsmaterializedview ();[ Date: 2026-01-15 09:05:32 ]
12 119.99 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-01-15 09:30:05 ]
13 115.06 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: 2026-01-15 09:30:05 ]
14 103.65 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-01-15 09:50:05 ]
15 89.92 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: 2026-01-15 09:20:04 ]
16 89.45 MiB select updateageforrelevantresults ();[ Date: 2026-01-15 09:02:07 ]
17 89.36 MiB select updateageforrelevantresults ();[ Date: 2026-01-15 09:32:06 ]
18 89.30 MiB select updateageforrelevantresults ();[ Date: 2026-01-15 09:47:04 ]
19 89.25 MiB select updateageforrelevantresults ();[ Date: 2026-01-15 09:17:04 ]
20 88.52 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2026-01-15 09:50:04 ]
-
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)
- 55 analyzes Total
Table Number of analyzes acaweb_fx.public.solr_relevance_old 16 acaweb_fx.pg_catalog.pg_attribute 5 acaweb_fx.public.datafeeds_latestrun 4 acaweb_fx.public.relevance_keylevels_results 4 acaweb_fx.pg_catalog.pg_class 4 acaweb_fx.public.relevance_fibonacci_results 4 acaweb_fx.public.relevance_autochartist_results 4 acaweb_fx.pg_catalog.pg_type 3 acaweb_fx.pg_catalog.pg_index 2 acaweb_fx.public.autochartist_symbolupdates 2 acaweb_fx.public.latest_t15_candle_view 2 socialmedia.public.processes 1 acaweb_fx.public.patternresultsrelevance 1 acaweb_fx.pg_catalog.pg_depend 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 acaweb_fx.public.symbollatestupdatetime 1 Total 55 Vacuums per table
Key values
- public.solr_relevance_old (22) Main table vacuumed on database acaweb_fx
- 42 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 22 16 17,391 0 77 0 0 9,967 1,688 8,115,262 acaweb_fx.public.datafeeds_latestrun 4 0 482 0 11 0 0 60 10 52,260 acaweb_fx.pg_toast.pg_toast_2619 2 2 274 0 33 0 0 189 31 138,464 acaweb_fx.pg_catalog.pg_attribute 2 2 1,655 0 323 0 134 745 266 1,570,586 acaweb_fx.public.relevance_keylevels_results 2 2 7,898 0 311 4 86 2,569 297 900,921 acaweb_fx.public.relevance_autochartist_results 2 2 6,886 0 206 0 468 1,463 192 470,441 acaweb_fx.public.relevance_fibonacci_results 2 2 2,589 0 59 0 83 502 44 116,990 acaweb_fx.pg_catalog.pg_index 1 1 104 0 12 0 0 28 11 83,016 acaweb_fx.pg_catalog.pg_type 1 1 126 0 28 0 0 48 19 121,383 acaweb_fx.public.autochartist_symbolupdates 1 1 25,534 0 3,071 4 38,247 6,696 5,377 1,901,624 acaweb_fx.pg_catalog.pg_statistic 1 1 998 0 166 0 592 483 154 602,033 acaweb_fx.public.latest_t15_candle_view 1 1 66 0 4 0 0 6 1 8,142 acaweb_fx.pg_catalog.pg_class 1 1 453 0 39 0 0 140 37 209,125 Total 42 32 64,456 43,302 4,340 8 39,610 22,896 8,127 14,290,247 Tuples removed per table
Key values
- public.solr_relevance_old (66080) Main table with removed tuples on database acaweb_fx
- 80747 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 22 16 66,080 176,709 41,680 0 4,578 acaweb_fx.public.autochartist_symbolupdates 1 1 5,505 49,457 321 0 40,691 acaweb_fx.pg_catalog.pg_attribute 2 2 3,165 21,720 252 0 528 acaweb_fx.public.relevance_keylevels_results 2 2 3,069 25,724 0 0 558 acaweb_fx.public.relevance_autochartist_results 2 2 1,390 16,889 0 0 760 acaweb_fx.pg_catalog.pg_statistic 1 1 533 3,754 0 0 1,194 acaweb_fx.public.relevance_fibonacci_results 2 2 314 3,214 0 0 204 acaweb_fx.public.datafeeds_latestrun 4 0 239 56 0 0 64 acaweb_fx.pg_catalog.pg_class 1 1 149 1,649 0 0 150 acaweb_fx.pg_toast.pg_toast_2619 2 2 131 342 6 0 98 acaweb_fx.pg_catalog.pg_type 1 1 99 1,446 0 0 38 acaweb_fx.public.latest_t15_candle_view 1 1 50 28 14 0 1 acaweb_fx.pg_catalog.pg_index 1 1 23 813 0 0 22 Total 42 32 80,747 301,801 42,273 0 48,886 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_catalog.pg_index 1 1 23 0 acaweb_fx.pg_toast.pg_toast_2619 2 2 131 0 acaweb_fx.pg_catalog.pg_type 1 1 99 0 acaweb_fx.public.datafeeds_latestrun 4 0 239 0 acaweb_fx.public.autochartist_symbolupdates 1 1 5505 0 acaweb_fx.pg_catalog.pg_statistic 1 1 533 0 acaweb_fx.pg_catalog.pg_attribute 2 2 3165 0 acaweb_fx.public.latest_t15_candle_view 1 1 50 0 acaweb_fx.public.relevance_keylevels_results 2 2 3069 0 acaweb_fx.pg_catalog.pg_class 1 1 149 0 acaweb_fx.public.solr_relevance_old 22 16 66080 0 acaweb_fx.public.relevance_autochartist_results 2 2 1390 0 acaweb_fx.public.relevance_fibonacci_results 2 2 314 0 Total 42 32 80,747 0 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Jan 15 09 42 55 - 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
- 77,524 Total read queries
- 43,520 Total write queries
Queries by database
Key values
- unknown Main database
- 250,184 Requests
- 1h44m46s (unknown)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 917 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 203 0ms select 102 0ms tcl 331 0ms update 39 0ms socialmedia Total 147 0ms others 46 0ms select 98 0ms tcl 3 0ms unknown Total 250,184 1h44m46s copy from 16 0ms cte 7,812 0ms insert 31,576 0ms others 4,348 0ms select 77,324 0ms tcl 400 0ms update 3,101 0ms Queries by user
Key values
- unknown Main user
- 250,184 Requests
User Request type Count Duration postgres Total 1,064 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 249 0ms select 200 0ms tcl 334 0ms update 39 0ms unknown Total 250,184 1h44m46s copy from 16 0ms cte 7,812 0ms insert 31,576 0ms others 4,348 0ms select 77,324 0ms tcl 400 0ms update 3,101 0ms Duration by user
Key values
- 1h44m46s (unknown) Main time consuming user
User Request type Count Duration postgres Total 1,064 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 249 0ms select 200 0ms tcl 334 0ms update 39 0ms unknown Total 250,184 1h44m46s copy from 16 0ms cte 7,812 0ms insert 31,576 0ms others 4,348 0ms select 77,324 0ms tcl 400 0ms update 3,101 0ms Queries by host
Key values
- unknown Main host
- 251,248 Requests
- 1h44m46s (unknown)
- Main time consuming host
Queries by application
Key values
- unknown Main application
- 250,861 Requests
- 1h44m46s (unknown)
- Main time consuming application
Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2026-01-15 09:38:24 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 90,457 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 4 0ms 0ms 0ms insert into t30 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jan 15 09 4 0ms 0ms 2 0ms 41 0ms 0ms 0ms select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Jan 15 09 41 0ms 0ms 3 0ms 6 0ms 0ms 0ms select "public"."processparameters"."id" AS "id", "public"."processparameters"."processid" AS "processid", "public"."processparameters"."key" AS "key", "public"."processparameters"."value" AS "value" from "public"."processparameters" where "public"."processparameters"."id" = ? and "public"."processparameters"."id" = ? limit ? offset ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jan 15 09 6 0ms 0ms 4 0ms 2 0ms 0ms 0ms select distinct "public"."processes"."live" AS "live" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? order by ? asc;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Jan 15 09 2 0ms 0ms 5 0ms 57 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 15 09 57 0ms 0ms 6 0ms 2,342 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 15 09 2,342 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 15 09 48 0ms 0ms 8 0ms 4 0ms 0ms 0ms select updaterelevantforrelevantresults ();Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Jan 15 09 4 0ms 0ms 9 0ms 1 0ms 0ms 0ms update processparameters set value = null where key in (...) and processid = ?;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jan 15 09 1 0ms 0ms 10 0ms 46 0ms 0ms 0ms set datestyle = iso;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Jan 15 09 46 0ms 0ms 11 0ms 1 0ms 0ms 0ms update "public"."processes" set "locale" = ?, "region" = ?, "schedule" = ? where "id" = ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jan 15 09 1 0ms 0ms 12 0ms 46 0ms 0ms 0ms set client_encoding to ?;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jan 15 09 46 0ms 0ms 13 0ms 18 0ms 0ms 0ms select cast(count(*) / cast(setting as numeric) * ? as int) from pg_stat_activity, pg_settings where name = ? group by setting;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jan 15 09 18 0ms 0ms 14 0ms 2 0ms 0ms 0ms select distinct "public"."processes"."enabled" AS "enabled" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? order by ? asc;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Jan 15 09 2 0ms 0ms 15 0ms 367 0ms 0ms 0ms commit;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Jan 15 09 367 0ms 0ms 16 0ms 1 0ms 0ms 0ms select "public"."processes"."id" AS "id", "public"."processes"."locale" AS "locale", "public"."processes"."region" AS "region", "public"."processes"."schedule" AS "schedule", "public"."processes"."enabled" AS "enabled", "public"."processes"."live" AS "live", "public"."processes"."lastmodified" AS "lastmodified", "public"."processes"."lastrun" AS "lastrun", "public"."processes"."contenttypeid" AS "contenttypeid", "public"."processes"."brokerid" AS "brokerid", "public"."processes"."uuid" AS "uuid", "LT?"."name" AS "LA?", "LT?"."name" AS "LA?" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? and (brokerid = ?) order by "public"."processes"."id" asc limit ? offset ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Jan 15 09 1 0ms 0ms 17 0ms 254 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Jan 15 09 254 0ms 0ms 18 0ms 239 0ms 0ms 0ms select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Jan 15 09 239 0ms 0ms 19 0ms 239 0ms 0ms 0ms select system_identifier from pg_control_system ();Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Jan 15 09 239 0ms 0ms 20 0ms 4 0ms 0ms 0ms select groupid, exchange, groupname, symbol, longname from prfsymboltree where brokerid = ? order by groupname, symbol;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Jan 15 09 4 0ms 0ms Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 32,456 0ms 0ms 0ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jan 15 09 32,456 0ms 0ms 2 9,382 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 15 09 9,382 0ms 0ms 3 7,872 0ms 0ms 0ms 0ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jan 15 09 7,872 0ms 0ms 4 7,854 0ms 0ms 0ms 0ms select s.symbolid as id, s.symbol as name, s.exchange as exchange, s.timegranularity as interval, dtt.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join brokersymbollist bsl on bsl.symbolid = s.symbolid where bsl.brokerid = ? and (? = ? or s.timegranularity = ?) and (s.symbol = ? or dss.downloadersymbol = ?) and dss.enabled = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Jan 15 09 7,854 0ms 0ms 5 6,569 0ms 0ms 0ms 0ms insert into t15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Jan 15 09 6,569 0ms 0ms 6 5,126 0ms 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_summary where statsid = ? and category = lower(?) union select category, name, total, correct, percentage, "from", "to" from stats_hrs_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Jan 15 09 5,126 0ms 0ms 7 4,415 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 #7
Day Hour Count Duration Avg duration Jan 15 09 4,415 0ms 0ms 8 3,695 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 #8
Day Hour Count Duration Avg duration Jan 15 09 3,695 0ms 0ms 9 2,990 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 15 09 2,990 0ms 0ms 10 2,835 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 #10
Day Hour Count Duration Avg duration Jan 15 09 2,835 0ms 0ms 11 2,796 0ms 0ms 0ms 0ms select category, name, sum(total) as total, sum(correct) as correct, (cast(sum(correct) as float) / cast(sum(total) as float)) * ?.? as percentage, min("from") AS "from", max("to") AS "to" from ( select category, name, total, correct, percentage, "from", "to" from stats_hrsapproaches_summary where statsid = ? and category = lower(?) order by correct desc) as summdata group by category, name having sum(total) > ? order by name;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jan 15 09 2,796 0ms 0ms 12 2,545 0ms 0ms 0ms 0ms insert into fibonacci_results (bandwidth, pattern, gmttimefound, direction, patternstarttime, patternendtime, patternstartprice, patternendprice, qtytp, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, patternlengthbars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) values (?.?, ?, ?::timestamp without time zone, ?, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?, ?, ?, ?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jan 15 09 2,545 0ms 0ms 13 2,521 0ms 0ms 0ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jan 15 09 2,521 0ms 0ms 14 2,342 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 #14
Day Hour Count Duration Avg duration Jan 15 09 2,342 0ms 0ms 15 1,925 0ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Jan 15 09 1,925 0ms 0ms 16 1,911 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 #16
Day Hour Count Duration Avg duration Jan 15 09 1,911 0ms 0ms 17 1,890 0ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Jan 15 09 1,890 0ms 0ms 18 1,568 0ms 0ms 0ms 0ms select ew.processid, "Errors", "Warnings" from quantity_errors_warnings_perprocess ew;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Jan 15 09 1,568 0ms 0ms 19 1,362 0ms 0ms 0ms 0ms select case when a.old_resultuid = ? then a.old_resultuid else a.resultuid end as resultuid, s.symbol, pattern as patternname, timegranularity as interval, patternlengthbars as length, patternendtime, direction, breakout, predictiontimeto, predictionpricefrom, predictionpriceto, patternstartprice, resy1, supporty1, dtt.timezone, cps.pip, newlevels.profit from autochartist_results a inner join downloadersymbolsettings dss on a.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern left join currencypips cps on cps.symbol = s.symbol left join lateral calc_cp_signal (a.resultuid) newlevels on true where (a.old_resultuid = ? or a.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Jan 15 09 1,362 0ms 0ms 20 1,117 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 #20
Day Hour Count Duration Avg duration Jan 15 09 1,117 0ms 0ms Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 0ms 0ms 0ms 4 0ms insert into t30 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jan 15 09 4 0ms 0ms 2 0ms 0ms 0ms 41 0ms select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Jan 15 09 41 0ms 0ms 3 0ms 0ms 0ms 6 0ms select "public"."processparameters"."id" AS "id", "public"."processparameters"."processid" AS "processid", "public"."processparameters"."key" AS "key", "public"."processparameters"."value" AS "value" from "public"."processparameters" where "public"."processparameters"."id" = ? and "public"."processparameters"."id" = ? limit ? offset ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jan 15 09 6 0ms 0ms 4 0ms 0ms 0ms 2 0ms select distinct "public"."processes"."live" AS "live" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? order by ? asc;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Jan 15 09 2 0ms 0ms 5 0ms 0ms 0ms 57 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 15 09 57 0ms 0ms 6 0ms 0ms 0ms 2,342 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 15 09 2,342 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 15 09 48 0ms 0ms 8 0ms 0ms 0ms 4 0ms select updaterelevantforrelevantresults ();Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Jan 15 09 4 0ms 0ms 9 0ms 0ms 0ms 1 0ms update processparameters set value = null where key in (...) and processid = ?;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jan 15 09 1 0ms 0ms 10 0ms 0ms 0ms 46 0ms set datestyle = iso;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Jan 15 09 46 0ms 0ms 11 0ms 0ms 0ms 1 0ms update "public"."processes" set "locale" = ?, "region" = ?, "schedule" = ? where "id" = ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jan 15 09 1 0ms 0ms 12 0ms 0ms 0ms 46 0ms set client_encoding to ?;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jan 15 09 46 0ms 0ms 13 0ms 0ms 0ms 18 0ms select cast(count(*) / cast(setting as numeric) * ? as int) from pg_stat_activity, pg_settings where name = ? group by setting;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jan 15 09 18 0ms 0ms 14 0ms 0ms 0ms 2 0ms select distinct "public"."processes"."enabled" AS "enabled" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? order by ? asc;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Jan 15 09 2 0ms 0ms 15 0ms 0ms 0ms 367 0ms commit;Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Jan 15 09 367 0ms 0ms 16 0ms 0ms 0ms 1 0ms select "public"."processes"."id" AS "id", "public"."processes"."locale" AS "locale", "public"."processes"."region" AS "region", "public"."processes"."schedule" AS "schedule", "public"."processes"."enabled" AS "enabled", "public"."processes"."live" AS "live", "public"."processes"."lastmodified" AS "lastmodified", "public"."processes"."lastrun" AS "lastrun", "public"."processes"."contenttypeid" AS "contenttypeid", "public"."processes"."brokerid" AS "brokerid", "public"."processes"."uuid" AS "uuid", "LT?"."name" AS "LA?", "LT?"."name" AS "LA?" from "public"."processes" left outer join "public"."brokers" "LT?" on "LT?"."id" = "public"."processes"."brokerid" left outer join "public"."contenttypes" "LT?" on "LT?"."id" = "public"."processes"."contenttypeid" where "public"."processes"."id" = ? and "public"."processes"."id" = ? and (brokerid = ?) order by "public"."processes"."id" asc limit ? offset ?;Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Jan 15 09 1 0ms 0ms 17 0ms 0ms 0ms 254 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Jan 15 09 254 0ms 0ms 18 0ms 0ms 0ms 239 0ms select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Jan 15 09 239 0ms 0ms 19 0ms 0ms 0ms 239 0ms select system_identifier from pg_control_system ();Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Jan 15 09 239 0ms 0ms 20 0ms 0ms 0ms 4 0ms select groupid, exchange, groupname, symbol, longname from prfsymboltree where brokerid = ? order by groupname, symbol;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Jan 15 09 4 0ms 0ms Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 1s731ms 2,080 0ms 11ms 0ms WITH rar_max as ( ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Jan 15 09 2,080 1s731ms 0ms -
WITH rar_max as ( ;
Date: 2026-01-15 09:25:36 Duration: 11ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-01-15 09:25:36 Duration: 10ms Database: postgres
-
WITH rar_max as ( ;
Date: 2026-01-15 09:37:49 Duration: 9ms Database: postgres
2 1s631ms 1,242 0ms 4ms 1ms SELECT symbolid, ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 09 1,242 1s631ms 1ms -
SELECT symbolid, ;
Date: 2026-01-15 09:30:53 Duration: 4ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-01-15 09:45:03 Duration: 3ms Database: postgres
-
SELECT symbolid, ;
Date: 2026-01-15 09:15:45 Duration: 2ms Database: postgres
3 871ms 2,991 0ms 5ms 0ms SELECT ;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 09 2,991 871ms 0ms -
SELECT ;
Date: 2026-01-15 09:35:46 Duration: 5ms Database: postgres
-
SELECT ;
Date: 2026-01-15 09:40:03 Duration: 4ms Database: postgres
-
SELECT ;
Date: 2026-01-15 09:11:42 Duration: 3ms Database: postgres
4 515ms 512 0ms 1ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 09 512 515ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-01-15 09:01:16 Duration: 1ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-01-15 09:30:35 Duration: 1ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-01-15 09:31:04 Duration: 1ms Database: postgres
5 271ms 3,143 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 09 3,143 271ms 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: 2026-01-15 09:41:01 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: 2026-01-15 09:41:47 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: 2026-01-15 09:10:56 Duration: 0ms Database: postgres
6 241ms 1,925 0ms 2ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #6
Day Hour Count Duration Avg duration 09 1,925 241ms 0ms -
SET extra_float_digits = 3;
Date: 2026-01-15 09:54:33 Duration: 2ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-01-15 09:45:54 Duration: 1ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2026-01-15 09:45:54 Duration: 0ms Database: postgres
7 188ms 1,997 0ms 0ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 09 1,997 188ms 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: 2026-01-15 09:10:58 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: 2026-01-15 09:11:42 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: 2026-01-15 09:15:45 Duration: 0ms Database: postgres
8 166ms 1,143 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 09 1,143 166ms 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: 2026-01-15 09:32:10 Duration: 0ms Database: postgres
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-15 09:47:39 Duration: 0ms Database: postgres
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-15 09:02:46 Duration: 0ms Database: postgres
9 109ms 740 0ms 0ms 0ms select category, ;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 09 740 109ms 0ms -
select category, ;
Date: 2026-01-15 09:10:55 Duration: 0ms Database: postgres
-
select category, ;
Date: 2026-01-15 09:10:55 Duration: 0ms Database: postgres
-
select category, ;
Date: 2026-01-15 09:10:55 Duration: 0ms Database: postgres
10 59ms 1,394 0ms 2ms 0ms select 1;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 09 1,394 59ms 0ms -
select 1;
Date: 2026-01-15 09:51:56 Duration: 2ms Database: postgres
-
select 1;
Date: 2026-01-15 09:11:42 Duration: 1ms Database: postgres
-
select 1;
Date: 2026-01-15 09:27:53 Duration: 1ms Database: postgres
11 48ms 329 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 #11
Day Hour Count Duration Avg duration 09 329 48ms 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: 2026-01-15 09:13:22 Duration: 0ms Database: postgres
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-01-15 09:13:25 Duration: 0ms Database: postgres
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-01-15 09:13:22 Duration: 0ms Database: postgres
12 44ms 35 0ms 3ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 09 35 44ms 1ms -
WITH last_candle AS ( ;
Date: 2026-01-15 09:00:44 Duration: 3ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-01-15 09:56:00 Duration: 3ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2026-01-15 09:32:00 Duration: 3ms Database: postgres
13 43ms 18 1ms 2ms 2ms select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 09 18 43ms 2ms -
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-01-15 09:01:32 Duration: 2ms Database: postgres
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-01-15 09:11:01 Duration: 2ms Database: postgres
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2026-01-15 09:31:01 Duration: 2ms Database: postgres
14 41ms 8 4ms 6ms 5ms with sym_info as ( ;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 09 8 41ms 5ms -
with sym_info as ( ;
Date: 2026-01-15 09:51:42 Duration: 6ms Database: postgres
-
with sym_info as ( ;
Date: 2026-01-15 09:51:45 Duration: 6ms Database: postgres
-
with sym_info as ( ;
Date: 2026-01-15 09:21:48 Duration: 4ms Database: postgres
15 30ms 27 0ms 1ms 1ms select distinct classname, to_char(created_datetime, 'yyyy-mm-dd HH24:MI'), to_char(cleared_datetime, 'yyyy-mm-dd HH24:MI'), action_to_take, description, created_datetime from datafeed_restarter_events where (is_current_entry = 1 OR cleared_datetime > current_timestamp - interval '17 hour') order by created_datetime desc;Times Reported Time consuming prepare #15
Day Hour Count Duration Avg duration 09 27 30ms 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: 2026-01-15 09:55:55 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: 2026-01-15 09:20:51 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: 2026-01-15 09:30:53 Duration: 1ms Database: postgres
16 25ms 17 0ms 4ms 1ms with wh_patitioned as ( ;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 09 17 25ms 1ms -
with wh_patitioned as ( ;
Date: 2026-01-15 09:01:49 Duration: 4ms Database: postgres
-
with wh_patitioned as ( ;
Date: 2026-01-15 09:05:01 Duration: 3ms Database: postgres
-
with wh_patitioned as ( ;
Date: 2026-01-15 09:50:02 Duration: 1ms Database: postgres
17 24ms 27 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 #17
Day Hour Count Duration Avg duration 09 27 24ms 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: 2026-01-15 09:51:00 Duration: 1ms Database: postgres
-
select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2026-01-15 09:15:50 Duration: 1ms Database: postgres
-
select feedname, to_char(latestrxtime, 'yyyy-mm-dd HH24:MI'), to_char(LatestDBWriteTime, 'yyyy-mm-dd HH24:MI'), to_char(LatestStartupTime, 'yyyy-mm-dd HH24:MI'), StartupTimeInMinutes, dm.source_type, dm.transport_type, case when latestrxtime < (CURRENT_TIMESTAMP - 5 * interval '1 minute') then 'X' else 'OK' end, case when (feedname ilike '%_EOD' OR feedname ilike 'IQFEED_DAILIES' or feedname ilike 'YAHOO%' or feedname ilike 'QUANDL_FUTURES%' or feedname ilike 'BAR_CHART') then case when LatestDBWriteTime < (CURRENT_TIMESTAMP - 24 * interval '1 hour') then 'X' else 'OK' end else case when (LatestDBWriteTime < (CURRENT_TIMESTAMP - 15 * interval '1 minute') and LatestStartupTime < (CURRENT_TIMESTAMP - 30 * interval '1 minute')) OR latestrxtime < CURRENT_TIMESTAMP - interval '2 hour' then 'X' else 'OK' end end as statusDB, comment from datafeeds_latestrun dlr left outer join datafeeds df on dlr.feedname ilike df.name inner join datafeeds_metadata dm on df.metadata_id = dm.id order by feedname;
Date: 2026-01-15 09:50:55 Duration: 1ms Database: postgres
18 23ms 40 0ms 1ms 0ms select distinct s.statsid as statsid, sy.exchange as name;Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 09 40 23ms 0ms -
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-01-15 09:10:55 Duration: 1ms Database: postgres
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-01-15 09:10:55 Duration: 1ms Database: postgres
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-01-15 09:10:55 Duration: 1ms Database: postgres
19 21ms 1,890 0ms 0ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 09 1,890 21ms 0ms -
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-01-15 09:25:36 Duration: 0ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-01-15 09:30:03 Duration: 0ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2026-01-15 09:47:04 Duration: 0ms Database: postgres
20 16ms 33 0ms 2ms 0ms WITH rcr_max as ( ;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 09 33 16ms 0ms -
WITH rcr_max as ( ;
Date: 2026-01-15 09:13:18 Duration: 2ms Database: postgres
-
WITH rcr_max as ( ;
Date: 2026-01-15 09:10:50 Duration: 1ms Database: postgres
-
WITH rcr_max as ( ;
Date: 2026-01-15 09:52:42 Duration: 0ms Database: postgres
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 24s595ms 6,896 0ms 46ms 3ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Jan 15 09 6,896 24s595ms 3ms -
WITH rar_max as ( ;
Date: 2026-01-15 09:27:53 Duration: 46ms Database: postgres parameters: $1 = '607506381714601301', $2 = '607506381714601301', $3 = '607506381714601301'
-
WITH rar_max as ( ;
Date: 2026-01-15 09:45:54 Duration: 46ms Database: postgres parameters: $1 = '607506668652931301', $2 = '607506668652931301', $3 = '607506668652931301'
-
WITH rar_max as ( ;
Date: 2026-01-15 09:41:24 Duration: 35ms Database: postgres parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '0', $10 = 't', $11 = '0', $12 = '0'
2 8s281ms 21,866 0ms 13ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 09 21,866 8s281ms 0ms -
SELECT ;
Date: 2026-01-15 09:37:49 Duration: 13ms Database: postgres parameters: $1 = '689', $2 = '689', $3 = '515840245907007300'
-
SELECT ;
Date: 2026-01-15 09:56:00 Duration: 7ms Database: postgres parameters: $1 = '515840233920750300'
-
SELECT ;
Date: 2026-01-15 09:30:04 Duration: 6ms Database: postgres parameters: $1 = '515840243239577300'
3 2s919ms 1,242 1ms 6ms 2ms SELECT symbolid, ;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 09 1,242 2s919ms 2ms -
SELECT symbolid, ;
Date: 2026-01-15 09:30:55 Duration: 6ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '15', $3 = 'NZDCAD', $4 = 'LTCUSD', $5 = 'NAS100', $6 = 'NZDJPY', $7 = 'NZDCHF', $8 = 'NOKJPY'
-
SELECT symbolid, ;
Date: 2026-01-15 09:45:45 Duration: 6ms Database: postgres parameters: $1 = 'PEPPERSTONE', $2 = '15', $3 = 'EURCZK', $4 = 'EURGBP', $5 = 'EURJPY', $6 = 'EURMXN', $7 = 'EURNZD', $8 = 'EURHUF', $9 = 'EURCAD', $10 = 'EURNOK', $11 = 'EURCHF'
-
SELECT symbolid, ;
Date: 2026-01-15 09:45:48 Duration: 5ms Database: postgres parameters: $1 = 'MILLENNIUMPF', $2 = '15', $3 = 'XAGUSD.ID'
4 1s56ms 189 0ms 21ms 5ms select distinct s.statsid as statsid, sy.exchange as name;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 09 189 1s56ms 5ms -
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-01-15 09:10:55 Duration: 21ms Database: postgres parameters: $1 = '489', $2 = '489'
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-01-15 09:10:55 Duration: 21ms Database: postgres parameters: $1 = '489', $2 = '489'
-
select distinct s.statsid as statsid, sy.exchange as name;
Date: 2026-01-15 09:10:55 Duration: 20ms Database: postgres parameters: $1 = '489', $2 = '489'
5 855ms 512 1ms 2ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 09 512 855ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-01-15 09:01:16 Duration: 2ms Database: postgres parameters: $1 = 'MILLENNIUMPF'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-01-15 09:31:01 Duration: 2ms Database: postgres parameters: $1 = 'PEPPERSTONE'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2026-01-15 09:46:19 Duration: 2ms Database: postgres parameters: $1 = 'PEPPERSTONEMT5'
6 643ms 8,854 0ms 1ms 0ms select category, ;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 09 8,854 643ms 0ms -
select category, ;
Date: 2026-01-15 09:50:34 Duration: 1ms Database: postgres parameters: $1 = '515852059313898307', $2 = 'symbol', $3 = 'BTCUSD', $4 = 'AUDJPY', $5 = 'USDMXN', $6 = 'USDZAR', $7 = 'CADJPY', $8 = 'GBPJPY', $9 = 'USDTHB', $10 = 'NZDJPY', $11 = 'USDJPY', $12 = 'USDHUF', $13 = 'EURZAR', $14 = 'CHFJPY', $15 = 'EURJPY', $16 = 'SGDJPY', $17 = 'SEKJPY', $18 = 'EURTRY', $19 = 'EURHKD', $20 = 'NOKJPY', $21 = 'USDSEK', $22 = 'USDCZK', $23 = 'EURNOK', $24 = 'USDDKK', $25 = 'GBPSEK', $26 = 'USDNOK', $27 = 'USDPLN', $28 = 'EURSEK', $29 = 'GBPDKK', $30 = 'GBPNOK', $31 = 'BTCUSD', $32 = 'GBPAUD', $33 = 'EURPLN', $34 = 'GBPNZD', $35 = 'EURNZD', $36 = 'EURAUD', $37 = 'USDCNH', $38 = 'USDTRY', $39 = 'GBPCAD', $40 = 'EURGBP', $41 = 'GBPNOK', $42 = 'SEKJPY', $43 = 'GBPSGD', $44 = 'USDZAR', $45 = 'USDHUF', $46 = 'EURCAD', $47 = 'GBPCAD', $48 = 'GBPUSD', $49 = 'USDCAD', $50 = 'GBPDKK', $51 = 'EURNOK', $52 = 'GBPSGD', $53 = '515852059313898307', $54 = 'symbol', $55 = 'BTCUSD', $56 = 'AUDJPY', $57 = 'USDMXN', $58 = 'USDZAR', $59 = 'CADJPY', $60 = 'GBPJPY', $61 = 'USDTHB', $62 = 'NZDJPY', $63 = 'USDJPY', $64 = 'USDHUF', $65 = 'EURZAR', $66 = 'CHFJPY', $67 = 'EURJPY', $68 = 'SGDJPY', $69 = 'SEKJPY', $70 = 'EURTRY', $71 = 'EURHKD', $72 = 'NOKJPY', $73 = 'USDSEK', $74 = 'USDCZK', $75 = 'EURNOK', $76 = 'USDDKK', $77 = 'GBPSEK', $78 = 'USDNOK', $79 = 'USDPLN', $80 = 'EURSEK', $81 = 'GBPDKK', $82 = 'GBPNOK', $83 = 'BTCUSD', $84 = 'GBPAUD', $85 = 'EURPLN', $86 = 'GBPNZD', $87 = 'EURNZD', $88 = 'EURAUD', $89 = 'USDCNH', $90 = 'USDTRY', $91 = 'GBPCAD', $92 = 'EURGBP', $93 = 'GBPNOK', $94 = 'SEKJPY', $95 = 'GBPSGD', $96 = 'USDZAR', $97 = 'USDHUF', $98 = 'EURCAD', $99 = 'GBPCAD', $100 = 'GBPUSD', $101 = 'USDCAD', $102 = 'GBPDKK', $103 = 'EURNOK', $104 = 'GBPSGD'
-
select category, ;
Date: 2026-01-15 09:10:55 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307', $2 = 'symbol', $3 = 'AUDJPY', $4 = 'XAUUSD', $5 = 'DOW30', $6 = 'GBPJPY', $7 = 'OIL', $8 = 'NASDAQ100', $9 = 'USDJPY', $10 = 'XAGUSD', $11 = 'EURJPY', $12 = 'NZDJPY', $13 = 'SP500', $14 = 'CHFJPY', $15 = 'GBPAUD', $16 = 'EURAUD', $17 = 'EURCAD', $18 = 'EURCHF', $19 = 'GBPCHF', $20 = 'EURGBP', $21 = 'XAGUSD', $22 = 'GBPUSD', $23 = 'OIL', $24 = 'RK_SSI', $25 = 'R_SSI', $26 = 'USDCAD', $27 = 'DOW30', $28 = 'EURCAD', $29 = 'NZDUSD', $30 = 'EURUSD', $31 = 'SP500', $32 = 'GBPJPY', $33 = 'EURUSD', $34 = 'USDCHF', $35 = 'AUDJPY', $36 = 'EURJPY', $37 = 'USDCAD', $38 = 'GBPUSD', $39 = 'CHFJPY', $40 = 'GBPAUD', $41 = 'AUDUSD', $42 = 'XAUUSD', $43 = 'EURAUD', $44 = 'AUDNZD', $45 = 'NZDUSD', $46 = 'NZDJPY', $47 = 'NASDAQ100', $48 = 'USDJPY', $49 = 'AUDUSD', $50 = 'USDCHF', $51 = 'GBPCHF', $52 = 'EURCHF', $53 = '515852059317765307', $54 = 'symbol', $55 = 'AUDJPY', $56 = 'XAUUSD', $57 = 'DOW30', $58 = 'GBPJPY', $59 = 'OIL', $60 = 'NASDAQ100', $61 = 'USDJPY', $62 = 'XAGUSD', $63 = 'EURJPY', $64 = 'NZDJPY', $65 = 'SP500', $66 = 'CHFJPY', $67 = 'GBPAUD', $68 = 'EURAUD', $69 = 'EURCAD', $70 = 'EURCHF', $71 = 'GBPCHF', $72 = 'EURGBP', $73 = 'XAGUSD', $74 = 'GBPUSD', $75 = 'OIL', $76 = 'RK_SSI', $77 = 'R_SSI', $78 = 'USDCAD', $79 = 'DOW30', $80 = 'EURCAD', $81 = 'NZDUSD', $82 = 'EURUSD', $83 = 'SP500', $84 = 'GBPJPY', $85 = 'EURUSD', $86 = 'USDCHF', $87 = 'AUDJPY', $88 = 'EURJPY', $89 = 'USDCAD', $90 = 'GBPUSD', $91 = 'CHFJPY', $92 = 'GBPAUD', $93 = 'AUDUSD', $94 = 'XAUUSD', $95 = 'EURAUD', $96 = 'AUDNZD', $97 = 'NZDUSD', $98 = 'NZDJPY', $99 = 'NASDAQ100', $100 = 'USDJPY', $101 = 'AUDUSD', $102 = 'USDCHF', $103 = 'GBPCHF', $104 = 'EURCHF'
-
select category, ;
Date: 2026-01-15 09:10:55 Duration: 1ms Database: postgres parameters: $1 = '515852059317765307', $2 = 'symbol', $3 = 'AUDJPY', $4 = 'XAUUSD', $5 = 'DOW30', $6 = 'GBPJPY', $7 = 'OIL', $8 = 'NASDAQ100', $9 = 'USDJPY', $10 = 'XAGUSD', $11 = 'EURJPY', $12 = 'NZDJPY', $13 = 'SP500', $14 = 'CHFJPY', $15 = 'GBPAUD', $16 = 'EURAUD', $17 = 'EURCAD', $18 = 'EURCHF', $19 = 'GBPCHF', $20 = 'EURGBP', $21 = 'XAGUSD', $22 = 'GBPUSD', $23 = 'OIL', $24 = 'RK_SSI', $25 = 'R_SSI', $26 = 'USDCAD', $27 = 'DOW30', $28 = 'EURCAD', $29 = 'NZDUSD', $30 = 'EURUSD', $31 = 'SP500', $32 = 'GBPJPY', $33 = 'EURUSD', $34 = 'USDCHF', $35 = 'AUDJPY', $36 = 'EURJPY', $37 = 'USDCAD', $38 = 'GBPUSD', $39 = 'CHFJPY', $40 = 'GBPAUD', $41 = 'AUDUSD', $42 = 'XAUUSD', $43 = 'EURAUD', $44 = 'AUDNZD', $45 = 'NZDUSD', $46 = 'NZDJPY', $47 = 'NASDAQ100', $48 = 'USDJPY', $49 = 'AUDUSD', $50 = 'USDCHF', $51 = 'GBPCHF', $52 = 'EURCHF', $53 = '515852059317765307', $54 = 'symbol', $55 = 'AUDJPY', $56 = 'XAUUSD', $57 = 'DOW30', $58 = 'GBPJPY', $59 = 'OIL', $60 = 'NASDAQ100', $61 = 'USDJPY', $62 = 'XAGUSD', $63 = 'EURJPY', $64 = 'NZDJPY', $65 = 'SP500', $66 = 'CHFJPY', $67 = 'GBPAUD', $68 = 'EURAUD', $69 = 'EURCAD', $70 = 'EURCHF', $71 = 'GBPCHF', $72 = 'EURGBP', $73 = 'XAGUSD', $74 = 'GBPUSD', $75 = 'OIL', $76 = 'RK_SSI', $77 = 'R_SSI', $78 = 'USDCAD', $79 = 'DOW30', $80 = 'EURCAD', $81 = 'NZDUSD', $82 = 'EURUSD', $83 = 'SP500', $84 = 'GBPJPY', $85 = 'EURUSD', $86 = 'USDCHF', $87 = 'AUDJPY', $88 = 'EURJPY', $89 = 'USDCAD', $90 = 'GBPUSD', $91 = 'CHFJPY', $92 = 'GBPAUD', $93 = 'AUDUSD', $94 = 'XAUUSD', $95 = 'EURAUD', $96 = 'AUDNZD', $97 = 'NZDUSD', $98 = 'NZDJPY', $99 = 'NASDAQ100', $100 = 'USDJPY', $101 = 'AUDUSD', $102 = 'USDCHF', $103 = 'GBPCHF', $104 = 'EURCHF'
7 601ms 23 0ms 46ms 26ms with wh_patitioned as ( ;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 09 23 601ms 26ms -
with wh_patitioned as ( ;
Date: 2026-01-15 09:01:49 Duration: 46ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
-
with wh_patitioned as ( ;
Date: 2026-01-15 09:05:01 Duration: 42ms 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: 2026-01-15 09:56:48 Duration: 40ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
8 512ms 32,342 0ms 1ms 0ms select 1;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 09 32,342 512ms 0ms -
select 1;
Date: 2026-01-15 09:47:05 Duration: 1ms Database: postgres
-
select 1;
Date: 2026-01-15 09:27:53 Duration: 1ms Database: postgres
-
select 1;
Date: 2026-01-15 09:45:04 Duration: 1ms Database: postgres
9 341ms 29 0ms 19ms 11ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 09 29 341ms 11ms -
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-01-15 09:17:05 Duration: 19ms Database: postgres parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-01-15 09:46:30 Duration: 19ms Database: postgres parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2026-01-15 09:21:34 Duration: 19ms Database: postgres parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
10 340ms 47 4ms 12ms 7ms WITH last_candle AS ( ;Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 09 47 340ms 7ms -
WITH last_candle AS ( ;
Date: 2026-01-15 09:16:00 Duration: 12ms Database: postgres parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2026-01-15 09:32:00 Duration: 12ms Database: postgres parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2026-01-15 09:56:00 Duration: 12ms Database: postgres parameters: $1 = '558', $2 = '558'
11 309ms 466 0ms 2ms 0ms SELECT absolutetimezoneoffset;Times Reported Time consuming bind #11
Day Hour Count Duration Avg duration 09 466 309ms 0ms -
SELECT absolutetimezoneoffset;
Date: 2026-01-15 09:01:17 Duration: 2ms Database: postgres parameters: $1 = '914', $2 = 'Metals'
-
SELECT absolutetimezoneoffset;
Date: 2026-01-15 09:01:16 Duration: 1ms Database: postgres parameters: $1 = '914', $2 = 'Energies'
-
SELECT absolutetimezoneoffset;
Date: 2026-01-15 09:10:57 Duration: 1ms Database: postgres parameters: $1 = '538', $2 = 'Shares EU'
12 282ms 6,569 0ms 1ms 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 #12
Day Hour Count Duration Avg duration 09 6,569 282ms 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: 2026-01-15 09:30:55 Duration: 1ms Database: postgres parameters: $1 = '2026-01-15 09:15:00', $2 = '0.45969', $3 = '0.4598', $4 = '0.45962', $5 = '0.45973', $6 = '669', $7 = '515840248023238300', $8 = '0', $9 = '2026-01-15 09:30:55.963', $10 = '2026-01-15 09:30:55.721', $11 = '0.45969', $12 = '0.4598', $13 = '0.45962', $14 = '0.45973', $15 = '669', $16 = '0', $17 = '2026-01-15 09:30:55.963', $18 = '2026-01-15 09:30:55.721'
-
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: 2026-01-15 09:31:02 Duration: 1ms Database: postgres parameters: $1 = '2026-01-15 09:15:00', $2 = '89.75', $3 = '89.988', $4 = '89.547', $5 = '89.85', $6 = '2016', $7 = '515840247971792300', $8 = '0', $9 = '2026-01-15 09:31:02.088', $10 = '2026-01-15 09:31:01.856', $11 = '89.75', $12 = '89.988', $13 = '89.547', $14 = '89.85', $15 = '2016', $16 = '0', $17 = '2026-01-15 09:31:02.088', $18 = '2026-01-15 09:31:01.856'
-
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: 2026-01-15 09:46:25 Duration: 0ms Database: postgres parameters: $1 = '2026-01-15 09:30:00', $2 = '1.162735', $3 = '1.16325', $4 = '1.16272', $5 = '1.16298', $6 = '456', $7 = '515840230405260300', $8 = '0', $9 = '2026-01-15 09:46:25.047', $10 = '2026-01-15 09:46:24.935', $11 = '1.162735', $12 = '1.16325', $13 = '1.16272', $14 = '1.16298', $15 = '456', $16 = '0', $17 = '2026-01-15 09:46:25.047', $18 = '2026-01-15 09:46:24.935'
13 261ms 8 28ms 44ms 32ms with sym_info as ( ;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 09 8 261ms 32ms -
with sym_info as ( ;
Date: 2026-01-15 09:51:43 Duration: 44ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
-
with sym_info as ( ;
Date: 2026-01-15 09:51:45 Duration: 43ms 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: 2026-01-15 09:21:45 Duration: 30ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
14 255ms 3,695 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 #14
Day Hour Count Duration Avg duration 09 3,695 255ms 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: 2026-01-15 09:15:59 Duration: 0ms Database: postgres parameters: $1 = '2026-01-15 09:30:00', $2 = '144.5301', $3 = '144.5658', $4 = '144.0869', $5 = '144.2183', $6 = '1688', $7 = '515840249476302300', $8 = '0', $9 = '2026-01-15 09:15:59.368', $10 = '2026-01-15 09:15:59.25', $11 = '144.5301', $12 = '144.5658', $13 = '144.0869', $14 = '144.2183', $15 = '1688', $16 = '0', $17 = '2026-01-15 09:15:59.368', $18 = '2026-01-15 09:15:59.25'
-
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: 2026-01-15 09:41:01 Duration: 0ms Database: postgres parameters: $1 = '2026-01-15 02:00:00', $2 = '702.37', $3 = '704.25', $4 = '702.37', $5 = '703.13', $6 = '43', $7 = '515840247953810300', $8 = '0', $9 = '2026-01-15 09:41:01.563', $10 = '2026-01-15 09:41:01.482', $11 = '702.37', $12 = '704.25', $13 = '702.37', $14 = '703.13', $15 = '43', $16 = '0', $17 = '2026-01-15 09:41:01.563', $18 = '2026-01-15 09:41:01.482'
-
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: 2026-01-15 09:41:47 Duration: 0ms Database: postgres parameters: $1 = '2026-01-15 02:00:00', $2 = '2484.31', $3 = '2484.93', $4 = '2483.14', $5 = '2483.14', $6 = '33', $7 = '515840247940195300', $8 = '0', $9 = '2026-01-15 09:41:47.945', $10 = '2026-01-15 09:41:47.865', $11 = '2484.31', $12 = '2484.93', $13 = '2483.14', $14 = '2483.14', $15 = '33', $16 = '0', $17 = '2026-01-15 09:41:47.945', $18 = '2026-01-15 09:41:47.865'
15 176ms 2,342 0ms 0ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #15
Day Hour Count Duration Avg duration 09 2,342 176ms 0ms -
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2026-01-15 09:10:58 Duration: 0ms Database: postgres parameters: $1 = '2026-01-15 07:00:00', $2 = '49098.4', $3 = '49154.02', $4 = '49098.4', $5 = '49126.9', $6 = '10621', $7 = '515840248000890300', $8 = '0', $9 = '2026-01-15 09:10:58.459', $10 = '2026-01-15 09:10:58.337', $11 = '49098.4', $12 = '49154.02', $13 = '49098.4', $14 = '49126.9', $15 = '10621', $16 = '0', $17 = '2026-01-15 09:10:58.459', $18 = '2026-01-15 09:10:58.337'
-
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: 2026-01-15 09:02:11 Duration: 0ms Database: postgres parameters: $1 = '2026-01-14 20:00:00', $2 = '17676.7', $3 = '17701.2', $4 = '17670.7', $5 = '17700.7', $6 = '2840', $7 = '500991628288378200', $8 = '0', $9 = '2026-01-15 09:02:11.289', $10 = '2026-01-15 09:02:11.088', $11 = '17676.7', $12 = '17701.2', $13 = '17670.7', $14 = '17700.7', $15 = '2840', $16 = '0', $17 = '2026-01-15 09:02:11.289', $18 = '2026-01-15 09:02:11.088'
-
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: 2026-01-15 09:30:37 Duration: 0ms Database: postgres parameters: $1 = '2026-01-15 08:00:00', $2 = '6925.5', $3 = '6938.6', $4 = '6924.7', $5 = '6933.8', $6 = '5970', $7 = '515840245924571300', $8 = '0', $9 = '2026-01-15 09:30:37.091', $10 = '2026-01-15 09:30:37.09', $11 = '6925.5', $12 = '6938.6', $13 = '6924.7', $14 = '6933.8', $15 = '5970', $16 = '0', $17 = '2026-01-15 09:30:37.091', $18 = '2026-01-15 09:30:37.09'
16 125ms 329 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 #16
Day Hour Count Duration Avg duration 09 329 125ms 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: 2026-01-15 09:13:22 Duration: 2ms Database: postgres
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-01-15 09:13:25 Duration: 0ms Database: postgres
-
SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2026-01-15 09:13:23 Duration: 0ms Database: postgres
17 75ms 14 3ms 9ms 5ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 09 14 75ms 5ms -
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-01-15 09:01:23 Duration: 9ms Database: postgres parameters: $1 = '627', $2 = '627'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-01-15 09:10:50 Duration: 9ms Database: postgres parameters: $1 = '627', $2 = '627'
-
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2026-01-15 09:11:00 Duration: 7ms Database: postgres parameters: $1 = '627', $2 = '627'
18 64ms 34 1ms 9ms 1ms WITH rcr_max as ( ;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 09 34 64ms 1ms -
WITH rcr_max as ( ;
Date: 2026-01-15 09:10:50 Duration: 9ms Database: postgres parameters: $1 = '607506382634058305', $2 = '607506382634058305', $3 = '607506382634058305'
-
WITH rcr_max as ( ;
Date: 2026-01-15 09:13:18 Duration: 4ms Database: postgres parameters: $1 = '607506382094440305', $2 = '607506382094440305', $3 = '607506382094440305'
-
WITH rcr_max as ( ;
Date: 2026-01-15 09:41:19 Duration: 2ms Database: postgres parameters: $1 = '607506382634058305', $2 = '607506382634058305', $3 = '607506382634058305'
19 50ms 12 1ms 8ms 4ms WITH pre_symbols AS ( /* find relevant symbols */ ;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 09 12 50ms 4ms -
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2026-01-15 09:13:21 Duration: 8ms 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: 2026-01-15 09:13:21 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'
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2026-01-15 09:00:50 Duration: 6ms Database: postgres parameters: $1 = '619', $2 = 'AXIORY', $3 = 'EURUSD', $4 = 'USDJPY', $5 = 'GBPUSD', $6 = 'AUDUSD', $7 = 'USDCHF', $8 = 'USDCAD', $9 = 'NZDUSD', $10 = 'GBPJPY', $11 = 'EURJPY', $12 = 'EURCHF', $13 = 'GBPCHF', $14 = 'EURCAD', $15 = 'GBPCAD', $16 = 'EURNZD', $17 = 'GBPNZD', $18 = 'CADJPY', $19 = 'CADCHF', $20 = 'CHFJPY', $21 = 'NZDJPY', $22 = 'XAUUSD', $23 = 'XAGUSD', $24 = 'EURUSD', $25 = 'USDJPY', $26 = 'GBPUSD', $27 = 'AUDUSD', $28 = 'USDCHF', $29 = 'USDCAD', $30 = 'NZDUSD', $31 = 'GBPJPY', $32 = 'EURJPY', $33 = 'EURCHF', $34 = 'GBPCHF', $35 = 'EURCAD', $36 = 'GBPCAD', $37 = 'EURNZD', $38 = 'GBPNZD', $39 = 'CADJPY', $40 = 'CADCHF', $41 = 'CHFJPY', $42 = 'NZDJPY', $43 = 'XAUUSD', $44 = 'XAGUSD', $45 = '5'
20 49ms 57 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 #20
Day Hour Count Duration Avg duration 09 57 49ms 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: 2026-01-15 09:16:54 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'XAUUSD', $3 = '558'
-
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2026-01-15 09:09:35 Duration: 1ms Database: postgres parameters: $1 = '667', $2 = 'BTCUSD', $3 = '667'
-
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: 2026-01-15 09:51:12 Duration: 1ms Database: postgres parameters: $1 = '632', $2 = 'GBPUSD', $3 = '632'
-
Events
Log levels
Key values
- 488,881 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 34 ERROR entries
- 0 WARNING entries
Most Frequent Errors/Events
Key values
- 34 Max number of times the same event was reported
- 34 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 15 09 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: 2026-01-15 09:06:01