pgBadger-
Global information
- Generated on Wed Dec 24 14:59:44 2025
- Log file: /home/postgres/pg_data/data/pg_log/postgresql-2025-12-24_160000.log
- Parsed 1,768,779 log entries in 43s
- Log start from 2025-12-24 16:00:00 to 2025-12-24 16:59:42
-
Overview
Global Stats
- 343 Number of unique normalized queries
- 211,349 Number of queries
- 1h56m52s Total query duration
- 2025-12-24 16:00:00 First query
- 2025-12-24 16:59:42 Last query
- 3,626 queries/s at 2025-12-24 16:00:04 Query peak
- 1h56m52s Total query duration
- 10s738ms Prepare/parse total duration
- 54s417ms Bind total duration
- 1h55m47s Execute total duration
- 0 Number of events
- 0 Number of unique normalized events
- 0 Max number of times the same event was reported
- 0 Number of cancellation
- 41 Total number of automatic vacuums
- 52 Total number of automatic analyzes
- 604 Number temporary file
- 122.50 MiB Max size of temporary file
- 8.25 MiB Average size of temporary file
- 4,998 Total number of sessions
- 22 sessions at 2025-12-24 16:52:14 Session peak
- 2d4h23m5s Total duration of sessions
- 37s732ms Average duration of sessions
- 42 Average queries per session
- 1s403ms Average queries duration per session
- 36s329ms Average idle time per session
- 5,000 Total number of connections
- 61 connections/s at 2025-12-24 16:50:08 Connection peak
- 3 Total number of databases
SQL Traffic
Key values
- 3,626 queries/s Query Peak
- 2025-12-24 16:00:04 Date
SELECT Traffic
Key values
- 1,717 queries/s Query Peak
- 2025-12-24 16:00:04 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 215 queries/s Query Peak
- 2025-12-24 16:46:07 Date
Queries duration
Key values
- 1h56m52s Total query duration
Prepared queries ratio
Key values
- 0.00 Ratio of bind vs prepare
- 0.00 % Ratio between prepared and "usual" statements
General Activity
↑ Back to the top of the General Activity tableDay Hour Count Min duration Max duration Avg duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Dec 24 16 211,349 0ms 41s561ms 32ms 4m15s 4m23s 4m51s Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Dec 24 16 51,668 26 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Dec 24 16 36,316 3,418 16 96 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Dec 24 16 30,277 69,776 2.30 31.15% Day Hour Count Average / Second Dec 24 16 5,000 1.39/s Day Hour Count Average Duration Average idle time Dec 24 16 4,998 37s732ms 36s342ms -
Connections
Established Connections
Key values
- 61 connections Connection Peak
- 2025-12-24 16:50:08 Date
Connections per database
Key values
- acaweb_fx Main Database
- 5,000 connections Total
Connections per user
Key values
- postgres Main User
- 5,000 connections Total
Connections per host
Key values
- 192.168.1.15 Main host with 2111 connections
- 5,000 Total connections
Host Count 127.0.0.1 114 192.168.0.114 3 192.168.0.216 101 192.168.0.74 267 192.168.1.145 28 192.168.1.15 2,111 192.168.1.20 58 192.168.1.239 1 192.168.1.90 52 192.168.2.126 62 192.168.2.182 24 192.168.2.82 48 192.168.3.199 36 192.168.4.116 4 192.168.4.137 4 192.168.4.142 1,356 192.168.4.150 10 192.168.4.226 4 192.168.4.238 16 192.168.4.33 89 192.168.4.47 1 192.168.4.98 330 52.214.24.33 7 [local] 274 -
Sessions
Simultaneous sessions
Key values
- 22 sessions Session Peak
- 2025-12-24 16:52:14 Date
Histogram of session times
Key values
- 4,080 0-500ms duration
Sessions per database
Key values
- acaweb_fx Main Database
- 4,998 sessions Total
Sessions per user
Key values
- postgres Main User
- 4,998 sessions Total
Sessions per host
Key values
- 192.168.1.15 Main Host
- 4,998 sessions Total
Host Count Total Duration Average Duration 127.0.0.1 114 11s659ms 102ms 192.168.0.114 3 21m10s 7m3s 192.168.0.216 101 1m23s 821ms 192.168.0.74 267 6h27m14s 1m27s 192.168.1.145 28 2h31m30s 5m24s 192.168.1.15 2,111 8h13m51s 14s36ms 192.168.1.20 58 14h22m30s 14m52s 192.168.1.239 1 6ms 6ms 192.168.1.90 52 33s110ms 636ms 192.168.2.126 62 6s545ms 105ms 192.168.2.182 24 4s483ms 186ms 192.168.2.82 48 21s970ms 457ms 192.168.3.199 36 1s371ms 38ms 192.168.4.116 4 33ms 8ms 192.168.4.137 4 22s866ms 5s716ms 192.168.4.142 1,356 17m19s 766ms 192.168.4.150 10 20h23s 2h2s 192.168.4.226 4 35ms 8ms 192.168.4.238 16 21s72ms 1s317ms 192.168.4.33 89 1m21s 919ms 192.168.4.47 1 190ms 190ms 192.168.4.98 330 21s655ms 65ms 52.214.24.33 5 18s538ms 3s707ms [local] 274 3m37s 792ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 36,607 buffers Checkpoint Peak
- 2025-12-24 16:06:33 Date
- 210.027 seconds Highest write time
- 0.011 seconds Sync time
Checkpoints Wal files
Key values
- 21 files Wal files usage Peak
- 2025-12-24 16:06:33 Date
Checkpoints distance
Key values
- 668.37 Mo Distance Peak
- 2025-12-24 16:06:33 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Dec 24 16 106,281 1,955.459s 0.052s 1,955.944s Day Hour Added Removed Recycled Synced files Longest sync Average sync Dec 24 16 0 0 58 2,034 0.005s 0s Day Hour Count Avg time (sec) Dec 24 16 0 0s Day Hour Mean distance Mean estimate Dec 24 16 79,228.33 kB 232,414.42 kB -
Temporary Files
Size of temporary files
Key values
- 184.87 MiB Temp Files size Peak
- 2025-12-24 16:00:07 Date
Number of temporary files
Key values
- 30 per second Temp Files Peak
- 2025-12-24 16:02:21 Date
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Dec 24 16 604 4.87 GiB 8.25 MiB Queries generating the most temporary files (N)
Rank Count Total size Min size Max size Avg size Query 1 28 1.66 GiB 7.16 MiB 121.09 MiB 60.78 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = ? ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = ? ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = ?) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, ?::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> ? ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = ?) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = ? where (ok.r is null or ok.r = ?) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = ?) and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > ? * ? and last.eventtimestamp > current_timestamp - interval ? and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval ?) and last.eventtimestamp > current_timestamp - interval ? and broker.r = ?;-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-12-24 16:00:07 Duration: 0ms
2 22 199.10 MiB 9.04 MiB 9.07 MiB 9.05 MiB jr.resultuid as resultuid, jr.direction as direction, jr.patternendtime as identified, jr.patternlengthbars as length, jr.patternstarttime as patternstarttime, case when jr.trendchangeid = ? then ? else ? end as trendchange, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, jp.patternname as pattern_name, dtt.timezone as timezone, ? as age, cps.pip, g.basegroupname from japsticks_results jr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = jr.symbolid inner join relevance_japsticks_results rar on rar.resultuid = jr.resultuid inner join symbols s on jr.symbolid = s.symbolid and s.nonliquid = ? inner join japsticks_patterns jp on jr.patternid = jp.id inner join downloadersymbolsettings dss on jr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where jr.gmttimefound > now() - interval ? and s.deleted = ? and (jr.simulation = ? or jr.simulation is null) and (rar.relevant = ?) --and (semicolon_age = ? or rar.age <= semicolon_age) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or jp.patternname in (...)) and (? = ? or jr.patternlengthbars <= ?) ), results as ( select distinct on (symbolid) * from all_results order by symbolid, resultuid ) select * from results order by identified desc, length desc ;-
jr.resultuid AS resultuid, jr.direction AS direction, jr.patternendtime AS identified, jr.patternlengthbars AS length, jr.patternstarttime AS patternstarttime, case when jr.trendchangeid = 1 then 'Continuation' else 'Reversal' end AS trendchange, s.exchange AS exchange, s.symbolid AS symbolid, coalesce(bim.code, s.symbol) AS symbol_code, s.longname AS symbol_name, s.timegranularity AS interval, jp.patternname AS pattern_name, dtt.timezone AS timezone, 0 AS age, cps.pip, g.basegroupname FROM japsticks_results jr INNER JOIN brokersymbollist bsl ON bsl.brokerid = $1 AND bsl.symbolid = jr.symbolid INNER JOIN relevance_japsticks_results rar ON rar.resultuid = jr.resultuid INNER JOIN symbols s ON jr.symbolid = s.symbolid AND s.nonliquid = 0 INNER JOIN japsticks_patterns jp ON jr.patternid = jp.id INNER JOIN downloadersymbolsettings dss ON jr.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname AND dtt.dayofweek = 3 INNER JOIN symbolgroup sg on s.symbolid = sg.symbolid INNER JOIN groups g ON sg.groupid = g.groupid INNER JOIN brokergroups bg on g.groupid = bg.groupid AND bsl.brokerid = bg.brokerid LEFT JOIN currencypips cps on cps.symbol = s.symbol LEFT OUTER JOIN brokerinstrumentmap bim ON dss.datafeedinstrumentid = bim.datafeedinstrumentid AND bim.brokerid = bsl.brokerid AND bim.TYPE = 'OUTBOUND' WHERE jr.gmttimefound > now() - INTERVAL '7 DAYS' AND s.deleted = 0 AND (jr.simulation = 0 OR jr.simulation IS NULL) AND (rar.relevant = 1) --AND (semicolon_age = 0 OR rar.age <= semicolon_age) AND ($2 = 0 OR s.timegranularity in ($3)) AND ($4 = 0 OR s.exchange in ($5)) AND ($6 = 0 OR coalesce(bim.code, s.symbol) in ($7)) AND ($8 = 0 OR jp.patternname in ($9)) AND ($10 = 0 OR jr.patternlengthbars <= $11)), results AS ( SELECT DISTINCT ON (symbolid) * FROM all_results ORDER BY symbolid, resultuid ) SELECT * from results ORDER BY identified DESC, length DESC;
Date: 2025-12-24 16:02:47 Duration: 0ms
3 16 503.25 MiB 31.45 MiB 31.45 MiB 31.45 MiB update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type = ?) sub where result_uid = sub.resultuid;-
UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type = 'cp') sub WHERE result_uid = sub.resultuid;
Date: 2025-12-24 16:01:14 Duration: 0ms
4 16 1.10 GiB 70.65 MiB 70.66 MiB 70.65 MiB with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ?) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then ? else ? end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then ? else ? end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike ? inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike ?) sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike ?; update solr_relevance_old set newrelevant = ? where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike ? and a.resultuid is null); update solr_relevance_old set new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total from ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total from whatshot_probability where type in (...)) sub where result_uid = sub.resultuid;-
with max_ra as ( select resultuid from relevance_keylevels_results order by resultuid desc limit 1) update solr_relevance_old set newrelevant = sub.relevant, newage = sub.age from ( select so.uuid, case when ra.relevant is not null then ra.relevant when so.result_uid < max_ra.resultuid then 0 else 1 end as relevant, case when ra.age is not null then ra.age when so.result_uid < max_ra.resultuid then 11 else 0 end as age, so.result_uid from max_ra, solr_relevance_old so inner join keylevels_results k on so.result_uid = k.resultuid and so.uuid ilike 'kl_%' inner join downloadersymbolsettings dss on k.symbolid = dss.symbolid left outer join relevance_keylevels_results ra on so.result_uid = ra.resultuid and so.uuid ilike 'kl_%') sub where solr_relevance_old.result_uid = sub.result_uid and solr_relevance_old.uuid ilike 'kl_%'; update solr_relevance_old set newrelevant = 0 where result_uid in ( select result_uid from solr_relevance_old s left outer join keylevels_results a on a.resultuid = s.result_uid where s.uuid ilike 'kl_%' and a.resultuid is null); UPDATE solr_relevance_old SET new_hod_correct = sub.hod_correct, new_hod_percent = sub.hod_percent, new_hod_total = sub.hod_total, new_pattern_correct = sub.pattern_correct, new_pattern_percent = sub.pattern_percent, new_pattern_total = sub.pattern_total, new_percent = sub.percent, new_symbol_correct = sub.symbol_correct, new_symbol_percent = sub.symbol_percent, new_symbol_total = sub.symbol_total FROM ( select distinct resultuid, hod_correct, hod_percent, hod_total, hod, pattern_correct, pattern_percent, pattern_total, percent, symbol_correct, symbol_percent, symbol_total FROM whatshot_probability WHERE type in ('kl', 'ekl')) sub WHERE result_uid = sub.resultuid;
Date: 2025-12-24 16:01:18 Duration: 0ms
5 8 979.65 MiB 122.42 MiB 122.50 MiB 122.46 MiB select updateresultsmaterializedview ();-
select updateresultsmaterializedview ();
Date: 2025-12-24 16:02:27 Duration: 0ms
6 4 361.12 MiB 90.20 MiB 90.38 MiB 90.28 MiB select updateageforrelevantresults ();-
select updateageforrelevantresults ();
Date: 2025-12-24 16:02:15 Duration: 0ms
Queries generating the largest temporary files
Rank Size Query 1 122.50 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 16:47:14 ]
2 122.48 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 16:50:32 ]
3 122.46 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 16:35:32 ]
4 122.46 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 16:32:16 ]
5 122.45 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 16:02:27 ]
6 122.45 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 16:17:15 ]
7 122.42 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 16:20:33 ]
8 122.42 MiB select updateresultsmaterializedview ();[ Date: 2025-12-24 16:05:36 ]
9 121.09 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-12-24 16:20:04 ]
10 108.48 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: 2025-12-24 16:50:04 ]
11 108.23 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-12-24 16:30:04 ]
12 98.85 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 = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-12-24 16:50:05 ]
13 95.50 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-12-24 16:40:05 ]
14 91.92 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: 2025-12-24 16:40:04 ]
15 91.27 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-12-24 16:10:06 ]
16 90.38 MiB select updateageforrelevantresults ();[ Date: 2025-12-24 16:02:15 ]
17 90.27 MiB select updateageforrelevantresults ();[ Date: 2025-12-24 16:32:05 ]
18 90.27 MiB select updateageforrelevantresults ();[ Date: 2025-12-24 16:47:04 ]
19 90.20 MiB select updateageforrelevantresults ();[ Date: 2025-12-24 16:17:05 ]
20 88.27 MiB with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;[ Date: 2025-12-24 16:10:05 ]
-
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)
- 52 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_autochartist_results 4 acaweb_fx.public.relevance_fibonacci_results 4 acaweb_fx.pg_catalog.pg_type 3 acaweb_fx.public.latest_t15_candle_view 2 acaweb_fx.pg_catalog.pg_index 1 acaweb_fx.public.autochartist_symbolupdates 1 acaweb_fx.public.relevance_consecutivecandles_results 1 acaweb_fx.public.symbollatestupdatetime 1 acaweb_fx.pg_catalog.pg_depend 1 acaweb_fx.public.latest_candle_datetime_per_receng 1 Total 52 Vacuums per table
Key values
- public.solr_relevance_old (16) Main table vacuumed on database acaweb_fx
- 41 vacuums Total
Index Buffer usage Skipped WAL usage Table Vacuums scans hits misses dirtied pins frozen records full page bytes acaweb_fx.public.solr_relevance_old 16 16 13,847 0 52 0 0 10,201 16 1,768,352 acaweb_fx.public.datafeeds_latestrun 4 0 481 0 5 0 0 60 6 50,956 acaweb_fx.public.relevance_fibonacci_results 4 4 5,681 0 99 8 30 901 337 1,018,688 acaweb_fx.public.relevance_autochartist_results 3 3 10,491 0 256 7 646 2,267 832 2,232,313 acaweb_fx.pg_toast.pg_toast_2619 2 2 284 0 65 0 0 200 61 255,535 acaweb_fx.pg_catalog.pg_statistic 2 2 1,959 0 401 0 1,176 919 367 1,385,230 acaweb_fx.public.latest_t15_candle_view 2 2 138 0 2 0 0 12 2 18,050 acaweb_fx.public.relevance_keylevels_results 2 2 7,997 0 334 4 192 2,272 307 776,223 acaweb_fx.public.autochartist_results 1 1 866,925 0 187,593 1 201 231,356 185,588 476,156,869 acaweb_fx.pg_catalog.pg_type 1 1 128 0 22 0 0 45 16 108,528 acaweb_fx.public.autochartist_symbolupdates 1 1 26,436 0 5,120 4 36,568 10,966 4,017 2,525,134 acaweb_fx.pg_catalog.pg_attribute 1 1 754 0 160 0 67 330 143 864,377 acaweb_fx.public.solr_imports 1 1 43 0 2 0 0 6 2 15,939 acaweb_fx.pg_catalog.pg_class 1 1 476 0 55 0 0 150 53 282,781 Total 41 37 935,640 946,847 194,166 24 38,880 259,685 191,747 487,458,975 Tuples removed per table
Key values
- public.solr_relevance_old (65470) Main table with removed tuples on database acaweb_fx
- 99636 tuples Total removed
Index Tuples Pages Table Vacuums scans removed remain not yet removable removed remain acaweb_fx.public.solr_relevance_old 16 16 65,470 97,073 0 0 3,448 acaweb_fx.public.autochartist_results 1 1 20,154 543,461 0 0 37,624 acaweb_fx.public.autochartist_symbolupdates 1 1 6,182 62,047 0 0 40,691 acaweb_fx.public.relevance_keylevels_results 2 2 2,948 24,195 0 0 558 acaweb_fx.public.relevance_autochartist_results 3 3 1,764 29,131 2,244 0 1,140 acaweb_fx.pg_catalog.pg_statistic 2 2 1,095 7,487 0 0 2,388 acaweb_fx.pg_catalog.pg_attribute 1 1 786 11,171 252 0 259 acaweb_fx.public.relevance_fibonacci_results 4 4 540 6,228 601 0 408 acaweb_fx.public.datafeeds_latestrun 4 0 232 56 0 0 64 acaweb_fx.pg_catalog.pg_class 1 1 135 1,649 0 0 150 acaweb_fx.pg_toast.pg_toast_2619 2 2 127 371 31 0 102 acaweb_fx.public.latest_t15_candle_view 2 2 112 28 0 0 2 acaweb_fx.public.solr_imports 1 1 51 1 0 0 2 acaweb_fx.pg_catalog.pg_type 1 1 40 1,446 0 0 38 Total 41 37 99,636 784,344 3,128 0 86,874 Pages removed per table
Key values
- unknown (0) Main table with removed pages on database unknown
- 0 pages Total removed
Pages removed per tables
NO DATASET
Table Number of vacuums Index scans Tuples removed Pages removed acaweb_fx.pg_toast.pg_toast_2619 2 2 127 0 acaweb_fx.public.autochartist_results 1 1 20154 0 acaweb_fx.pg_catalog.pg_type 1 1 40 0 acaweb_fx.public.autochartist_symbolupdates 1 1 6182 0 acaweb_fx.public.datafeeds_latestrun 4 0 232 0 acaweb_fx.pg_catalog.pg_attribute 1 1 786 0 acaweb_fx.public.solr_imports 1 1 51 0 acaweb_fx.pg_catalog.pg_statistic 2 2 1095 0 acaweb_fx.public.latest_t15_candle_view 2 2 112 0 acaweb_fx.public.relevance_keylevels_results 2 2 2948 0 acaweb_fx.pg_catalog.pg_class 1 1 135 0 acaweb_fx.public.solr_relevance_old 16 16 65470 0 acaweb_fx.public.relevance_autochartist_results 3 3 1764 0 acaweb_fx.public.relevance_fibonacci_results 4 4 540 0 Total 41 37 99,636 0 Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Dec 24 16 41 52 - 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
- 51,668 Total read queries
- 45,530 Total write queries
Queries by database
Key values
- unknown Main database
- 210,329 Requests
- 1h55m47s (unknown)
- Main time consuming database
Database Request type Count Duration acaweb_fx Total 929 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 214 0ms select 102 0ms tcl 331 0ms update 40 0ms socialmedia Total 91 0ms select 89 0ms tcl 2 0ms unknown Total 210,329 1h55m47s copy from 16 0ms cte 4,819 0ms ddl 1 0ms insert 36,316 0ms others 8,262 0ms select 51,477 0ms tcl 385 0ms update 3,378 0ms Queries by user
Key values
- unknown Main user
- 210,329 Requests
User Request type Count Duration postgres Total 1,020 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 214 0ms select 191 0ms tcl 333 0ms update 40 0ms unknown Total 210,329 1h55m47s copy from 16 0ms cte 4,819 0ms ddl 1 0ms insert 36,316 0ms others 8,262 0ms select 51,477 0ms tcl 385 0ms update 3,378 0ms Duration by user
Key values
- 1h55m47s (unknown) Main time consuming user
User Request type Count Duration postgres Total 1,020 0ms copy from 80 0ms copy to 26 0ms cte 104 0ms ddl 16 0ms delete 16 0ms others 214 0ms select 191 0ms tcl 333 0ms update 40 0ms unknown Total 210,329 1h55m47s copy from 16 0ms cte 4,819 0ms ddl 1 0ms insert 36,316 0ms others 8,262 0ms select 51,477 0ms tcl 385 0ms update 3,378 0ms Queries by host
Key values
- unknown Main host
- 211,349 Requests
- 1h55m47s (unknown)
- Main time consuming host
Queries by application
Key values
- unknown Main application
- 210,961 Requests
- 1h55m47s (unknown)
- Main time consuming application
Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2025-12-24 16:15:31 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 68,825 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 Dec 24 16 4 0ms 0ms 2 0ms 30 0ms 0ms 0ms select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Dec 24 16 30 0ms 0ms 3 0ms 1 0ms 0ms 0ms select ft.ftrelid as table_id, srv.srvname as table_server, ft.ftoptions as table_options, pg_catalog.pg_get_userbyid(cls.relowner) AS "owner" from pg_catalog.pg_foreign_table ft left outer join pg_catalog.pg_foreign_server srv on ft.ftserver = srv.oid join pg_catalog.pg_class cls on ft.ftrelid = cls.oid where cls.relnamespace = ?::oid and pg_catalog.age(ft.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) order by table_id;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Dec 24 16 1 0ms 0ms 4 0ms 2 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ) select bmr.symbolid, patternstarttime, patternendtime, timegranularity, ? as direction, case when bmr.old_resultuid = ? then bmr.old_resultuid else bmr.resultuid end as uid, s.exchange, s.symbol, s.longname, s.shortname, dtt.timezone, bmr.patternmovement, bmr.statisticalmovement, bmr.fromprice, bmr.toprice, bmr.percentile, bmr.patternlengthbars, case when rbr.age is not null then rbr.age when bmr.resultuid <= rm.resultuid then ? else ? end as age, case when rbr.relevant is not null then rbr.relevant when bmr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from bigmovement_results bmr inner join downloadersymbolsettings dss on bmr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on bmr.symbolid = s.symbolid inner join rar_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid left join currencypips cps on cps.symbol = s.symbol where (bmr.old_resultuid = ? or bmr.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Dec 24 16 2 0ms 0ms 5 0ms 2,180 0ms 0ms 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Dec 24 16 2,180 0ms 0ms 6 0ms 1 0ms 0ms 0ms select ind_head.indexrelid index_id, k col_idx, k <= indnkeyatts in_key, ind_head.indkey[k - 1] column_position, ind_head.indoption[k - 1] column_options, ind_head.indcollation[k - 1] as collation, colln.nspname as collation_schema, collname as collation_str, ind_head.indclass[k - 1] as opclass, case when opcdefault then null else opcn.nspname end as opclass_schema, case when opcdefault then null else opcname end as opclass_str, case when indexprs is null then null when ind_head.indkey[k - 1] = ? then chr(?) || pg_catalog.pg_get_indexdef(ind_head.indexrelid, k::int, true) else pg_catalog.pg_get_indexdef(ind_head.indexrelid, k::int, true) end as expression, amcanorder can_order from pg_catalog.pg_index ind_head join pg_catalog.pg_class ind_stor on ind_stor.oid = ind_head.indexrelid cross join unnest(ind_head.indkey) with ordinality u (u, k) left join pg_catalog.pg_collation on pg_collation.oid = ind_head.indcollation[k - 1] left join pg_catalog.pg_namespace colln on collnamespace = colln.oid cross join pg_catalog.pg_indexam_has_property(ind_stor.relam, ?) amcanorder left join pg_catalog.pg_opclass on pg_opclass.oid = ind_head.indclass[k - 1] left join pg_catalog.pg_namespace opcn on opcnamespace = opcn.oid where ind_stor.relnamespace = ?::oid and ind_stor.relkind in (...) and pg_catalog.age(ind_stor.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) order by index_id, k;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Dec 24 16 1 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 Dec 24 16 48 0ms 0ms 8 0ms 4 0ms 0ms 0ms select updaterelevantforrelevantresults ();Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Dec 24 16 4 0ms 0ms 9 0ms 1 0ms 0ms 0ms select oid from pg_catalog.pg_foreign_data_wrapper;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Dec 24 16 1 0ms 0ms 10 0ms 1 0ms 0ms 0ms select t.oid as type_id, t.xmin as type_state_number, t.typname as type_name, t.typtype as type_sub_kind, t.typcategory as type_category, t.typrelid as class_id, t.typbasetype as base_type_id, case when t.typtype in (...) then null else pg_catalog.format_type(t.typbasetype, t.typtypmod) end as type_def, t.typndims as dimensions_number, t.typdefault as default_expression, t.typnotnull as mandatory, pg_catalog.pg_get_userbyid(t.typowner) AS "owner" from pg_catalog.pg_type t left outer join pg_catalog.pg_class c on t.typrelid = c.oid where t.typnamespace = ?::oid and pg_catalog.age(t.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) and (t.typtype in (...) or c.relkind = ?::"char" or (t.typtype = ? and (t.typelem = ? or t.typcategory <> ?)) or t.typtype = ? and not t.typisdefined) order by ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Dec 24 16 1 0ms 0ms 11 0ms 1 0ms 0ms 0ms select t.relkind as table_kind, t.relname as table_name, t.oid as table_id, t.xmin as table_state_number, false as table_with_oids, t.reltablespace as tablespace_id, t.reloptions as options, t.relpersistence as persistence, ( select pg_catalog.array_agg(inhparent::bigint order by inhseqno)::varchar from pg_catalog.pg_inherits where t.oid = inhrelid) as ancestors, ( select pg_catalog.array_agg(inhrelid::bigint order by inhrelid)::varchar from pg_catalog.pg_inherits where t.oid = inhparent) as successors, t.relispartition as is_partition, pg_catalog.pg_get_partkeydef (t.oid) as partition_key, pg_catalog.pg_get_expr(t.relpartbound, t.oid) as partition_expression, t.relam am_id, pg_catalog.pg_get_userbyid(t.relowner) AS "owner" from pg_catalog.pg_class t where relnamespace = ?::oid and relkind in (...) and pg_catalog.age(t.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) order by table_kind, table_id;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Dec 24 16 1 0ms 0ms 12 0ms 18 0ms 0ms 0ms select cast(count(*) / cast(setting as numeric) * ? as int) from pg_stat_activity, pg_settings where name = ? group by setting;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Dec 24 16 18 0ms 0ms 13 0ms 359 0ms 0ms 0ms commit;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Dec 24 16 359 0ms 0ms 14 0ms 384 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Dec 24 16 384 0ms 0ms 15 0ms 1 0ms 0ms 0ms select e.oid as id, e.xmin as state_number, extname as name, extversion as version, extnamespace as schema_id, nspname as schema_name, array ( select unnest from unnest(available_versions) where unnest > extversion) as available_updates from pg_catalog.pg_extension e join pg_namespace n on e.extnamespace = n.oid left join ( select name, array_agg(version) as available_versions from pg_available_extension_versions() group by name) v on e.extname = v.name where pg_catalog.age(e.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?);Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Dec 24 16 1 0ms 0ms 16 0ms 239 0ms 0ms 0ms select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Dec 24 16 239 0ms 0ms 17 0ms 1 0ms 0ms 0ms select a.oid as access_method_id, a.xmin as state_number, a.amname as access_method_name, a.amhandler::oid as handler_id, pg_catalog.quote_ident(n.nspname) || ? || pg_catalog.quote_ident(p.proname) as handler_name, a.amtype as access_method_type from pg_am a join pg_proc p on a.amhandler::oid = p.oid join pg_namespace n on p.pronamespace = n.oid where pg_catalog.age(a.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?);Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Dec 24 16 1 0ms 0ms 18 0ms 239 0ms 0ms 0ms select system_identifier from pg_control_system ();Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Dec 24 16 239 0ms 0ms 19 0ms 5 0ms 0ms 0ms select groupid, exchange, groupname, symbol, longname from prfsymboltree where brokerid = ? order by groupname, symbol;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Dec 24 16 5 0ms 0ms 20 0ms 1 0ms 0ms 0ms insert into t15 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Dec 24 16 1 0ms 0ms Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 20,004 0ms 0ms 0ms 0ms select ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Dec 24 16 20,004 0ms 0ms 2 13,165 0ms 0ms 0ms 0ms select distinct on (coalesce(bim.code, s.symbol) , s.exchange, s.timegranularity, df.timezone) s.symbolid as id, coalesce(bim.code, s.symbol) as name, s.symbol as symbol, dss.downloadersymbol as ticker, s.exchange as exchange, s.timegranularity as interval, df.timezone as timezone from symbols s inner join downloadersymbolsettings dss on dss.symbolid = s.symbolid inner join datafeedstimetable df on df.classname ilike dss.classname left join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = s.symbolid left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = ? and bim.type = ? where s.symbolid = ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Dec 24 16 13,165 0ms 0ms 3 8,261 0ms 0ms 0ms 0ms insert into executionlogs (executionid, status, message, details, detailtype) values (null, ?, ?, null, null);Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Dec 24 16 8,261 0ms 0ms 4 7,888 0ms 0ms 0ms 0ms insert into autochartist_results (resultid, symbolid, bandwidth, pattern, qtytp, gmttimefound, direction, initialtrend, breakout, volumeincrease, noise, symmetry, predictionpricefrom, predictionpriceto, predictiontimefrom, predictiontimeto, patternstarttime, patternendtime, patternstartprice, patternendprice, resx0, resx1, supportx0, supportx1, resy0, resy1, supporty0, supporty1, supportgradient, resgradient, riskreward, patternquality, trendchange, maxmovementafterbreakout, latestbaratbreakouttime, latestbaratbreakoutprice, patternlengthbars, temporarypattern, relevancestartdistance, simulation, writtendatetime) values (?, ?, ?.?, ?, ?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?, ?, ?.?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Dec 24 16 7,888 0ms 0ms 5 5,800 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 #5
Day Hour Count Duration Avg duration Dec 24 16 5,800 0ms 0ms 6 5,795 0ms 0ms 0ms 0ms insert into t15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Dec 24 16 5,795 0ms 0ms 7 3,892 0ms 0ms 0ms 0ms set extra_float_digits = ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Dec 24 16 3,892 0ms 0ms 8 3,873 0ms 0ms 0ms 0ms set application_name = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Dec 24 16 3,873 0ms 0ms 9 3,607 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 Dec 24 16 3,607 0ms 0ms 10 3,332 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 #10
Day Hour Count Duration Avg duration Dec 24 16 3,332 0ms 0ms 11 2,952 0ms 0ms 0ms 0ms insert into fibonacci_results (bandwidth, pattern, gmttimefound, direction, patternstarttime, patternendtime, patternstartprice, patternendprice, qtytp, pricex, timex, pricea, timea, priceb, timeb, pricec, timec, priced, timed, averagequality, timequality, errormargin, patternlengthbars, target10, target06, target16, target07, target12, target05, target03, symbolid, noise, ratiosfound, temporarypattern, uniqueindex, completed, simulation, writtendatetime) values (?.?, ?, ?::timestamp without time zone, ?, ?::timestamp without time zone, ?::timestamp without time zone, ?.?, ?.?, ?, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?::timestamp without time zone, ?.?, ?.?, ?.?, ?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?.?, ?, ?.?, ?, ?, ?, ?, ?, current_timestamp::timestamp without time zone) on conflict do nothing;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Dec 24 16 2,952 0ms 0ms 12 2,810 0ms 0ms 0ms 0ms update patternresultsrelevance set relevant = ?, saxo_relevant = ?, notrelevantpricedatetime = ?, reason = ? where uniqueindex = ? and relevant = ?;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Dec 24 16 2,810 0ms 0ms 13 2,180 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 #13
Day Hour Count Duration Avg duration Dec 24 16 2,180 0ms 0ms 14 1,679 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 #14
Day Hour Count Duration Avg duration Dec 24 16 1,679 0ms 0ms 15 1,131 0ms 0ms 0ms 0ms insert into t240 (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 #15
Day Hour Count Duration Avg duration Dec 24 16 1,131 0ms 0ms 16 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 #16
Day Hour Count Duration Avg duration Dec 24 16 1,117 0ms 0ms 17 631 0ms 0ms 0ms 0ms select downloadersymbol, spike_threshold from price_datafeed_spike_threshold where classname = ?;Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Dec 24 16 631 0ms 0ms 18 631 0ms 0ms 0ms 0ms select s.symbolid, dss.downloadfrequency, dss.downloadersymbol from downloadersymbolsettings dss inner join symbols s on dss.symbolid = s.symbolid where dss.classname = ? and s.deleted = ? and dss.enabled = ?;Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Dec 24 16 631 0ms 0ms 19 389 0ms 0ms 0ms 0ms select df.absolutetimezoneoffset from datafeedstimetable df inner join downloadersymbolsettings dss on df.classname = dss.classname where dss.symbolid = ? group by df.absolutetimezoneoffset limit ?;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Dec 24 16 389 0ms 0ms 20 384 0ms 0ms 0ms 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Dec 24 16 384 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 Dec 24 16 4 0ms 0ms 2 0ms 0ms 0ms 30 0ms select key, value from datasources ds inner join datasourceparams dsp on ds.id = dsp.datasourceid where ds.name = ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Dec 24 16 30 0ms 0ms 3 0ms 0ms 0ms 1 0ms select ft.ftrelid as table_id, srv.srvname as table_server, ft.ftoptions as table_options, pg_catalog.pg_get_userbyid(cls.relowner) AS "owner" from pg_catalog.pg_foreign_table ft left outer join pg_catalog.pg_foreign_server srv on ft.ftserver = srv.oid join pg_catalog.pg_class cls on ft.ftrelid = cls.oid where cls.relnamespace = ?::oid and pg_catalog.age(ft.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) order by table_id;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Dec 24 16 1 0ms 0ms 4 0ms 0ms 0ms 2 0ms with rar_max as ( select resultuid from relevance_bigmovement_results order by resultuid desc limit ? ) select bmr.symbolid, patternstarttime, patternendtime, timegranularity, ? as direction, case when bmr.old_resultuid = ? then bmr.old_resultuid else bmr.resultuid end as uid, s.exchange, s.symbol, s.longname, s.shortname, dtt.timezone, bmr.patternmovement, bmr.statisticalmovement, bmr.fromprice, bmr.toprice, bmr.percentile, bmr.patternlengthbars, case when rbr.age is not null then rbr.age when bmr.resultuid <= rm.resultuid then ? else ? end as age, case when rbr.relevant is not null then rbr.relevant when bmr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from bigmovement_results bmr inner join downloadersymbolsettings dss on bmr.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname inner join symbols s on bmr.symbolid = s.symbolid inner join rar_max rm on ? = ? left outer join relevance_bigmovement_results rbr on rbr.resultuid = bmr.resultuid left join currencypips cps on cps.symbol = s.symbol where (bmr.old_resultuid = ? or bmr.resultuid = ?) and dtt.dayofweek = ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Dec 24 16 2 0ms 0ms 5 0ms 0ms 0ms 2,180 0ms insert into t60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) on conflict (pricedatetime, symbolid) do update set open = ?, high = ?, low = ?, close = ?, volume = ?, bsf = ?, sastdatetimewritten = ?, sastdatetimereceived = ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Dec 24 16 2,180 0ms 0ms 6 0ms 0ms 0ms 1 0ms select ind_head.indexrelid index_id, k col_idx, k <= indnkeyatts in_key, ind_head.indkey[k - 1] column_position, ind_head.indoption[k - 1] column_options, ind_head.indcollation[k - 1] as collation, colln.nspname as collation_schema, collname as collation_str, ind_head.indclass[k - 1] as opclass, case when opcdefault then null else opcn.nspname end as opclass_schema, case when opcdefault then null else opcname end as opclass_str, case when indexprs is null then null when ind_head.indkey[k - 1] = ? then chr(?) || pg_catalog.pg_get_indexdef(ind_head.indexrelid, k::int, true) else pg_catalog.pg_get_indexdef(ind_head.indexrelid, k::int, true) end as expression, amcanorder can_order from pg_catalog.pg_index ind_head join pg_catalog.pg_class ind_stor on ind_stor.oid = ind_head.indexrelid cross join unnest(ind_head.indkey) with ordinality u (u, k) left join pg_catalog.pg_collation on pg_collation.oid = ind_head.indcollation[k - 1] left join pg_catalog.pg_namespace colln on collnamespace = colln.oid cross join pg_catalog.pg_indexam_has_property(ind_stor.relam, ?) amcanorder left join pg_catalog.pg_opclass on pg_opclass.oid = ind_head.indclass[k - 1] left join pg_catalog.pg_namespace opcn on opcnamespace = opcn.oid where ind_stor.relnamespace = ?::oid and ind_stor.relkind in (...) and pg_catalog.age(ind_stor.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) order by index_id, k;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Dec 24 16 1 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 Dec 24 16 48 0ms 0ms 8 0ms 0ms 0ms 4 0ms select updaterelevantforrelevantresults ();Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Dec 24 16 4 0ms 0ms 9 0ms 0ms 0ms 1 0ms select oid from pg_catalog.pg_foreign_data_wrapper;Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Dec 24 16 1 0ms 0ms 10 0ms 0ms 0ms 1 0ms select t.oid as type_id, t.xmin as type_state_number, t.typname as type_name, t.typtype as type_sub_kind, t.typcategory as type_category, t.typrelid as class_id, t.typbasetype as base_type_id, case when t.typtype in (...) then null else pg_catalog.format_type(t.typbasetype, t.typtypmod) end as type_def, t.typndims as dimensions_number, t.typdefault as default_expression, t.typnotnull as mandatory, pg_catalog.pg_get_userbyid(t.typowner) AS "owner" from pg_catalog.pg_type t left outer join pg_catalog.pg_class c on t.typrelid = c.oid where t.typnamespace = ?::oid and pg_catalog.age(t.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) and (t.typtype in (...) or c.relkind = ?::"char" or (t.typtype = ? and (t.typelem = ? or t.typcategory <> ?)) or t.typtype = ? and not t.typisdefined) order by ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Dec 24 16 1 0ms 0ms 11 0ms 0ms 0ms 1 0ms select t.relkind as table_kind, t.relname as table_name, t.oid as table_id, t.xmin as table_state_number, false as table_with_oids, t.reltablespace as tablespace_id, t.reloptions as options, t.relpersistence as persistence, ( select pg_catalog.array_agg(inhparent::bigint order by inhseqno)::varchar from pg_catalog.pg_inherits where t.oid = inhrelid) as ancestors, ( select pg_catalog.array_agg(inhrelid::bigint order by inhrelid)::varchar from pg_catalog.pg_inherits where t.oid = inhparent) as successors, t.relispartition as is_partition, pg_catalog.pg_get_partkeydef (t.oid) as partition_key, pg_catalog.pg_get_expr(t.relpartbound, t.oid) as partition_expression, t.relam am_id, pg_catalog.pg_get_userbyid(t.relowner) AS "owner" from pg_catalog.pg_class t where relnamespace = ?::oid and relkind in (...) and pg_catalog.age(t.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?) order by table_kind, table_id;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Dec 24 16 1 0ms 0ms 12 0ms 0ms 0ms 18 0ms select cast(count(*) / cast(setting as numeric) * ? as int) from pg_stat_activity, pg_settings where name = ? group by setting;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Dec 24 16 18 0ms 0ms 13 0ms 0ms 0ms 359 0ms commit;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Dec 24 16 359 0ms 0ms 14 0ms 0ms 0ms 384 0ms with rar_max as ( select resultuid from relevance_keylevels_results order by resultuid desc limit ? ), kr as ( select a.*, rr.age, rr.relevant from keylevels_results a left outer join relevance_keylevels_results rr on a.resultuid = rr.resultuid where case when false = ? then true else a.resultuid > ( select min(resultuid) from relevance_keylevels_results) end ), all_results as ( select kr.resultuid as resultuid, kr.direction as direction, s.exchange as exchange, s.symbolid as symbolid, coalesce(bim.code, s.symbol) as symbol_code, s.longname as symbol_name, s.timegranularity as interval, p.patternname as pattern_name, kr.breakout as breakout, kr.atbaridentified as identified, dtt.timezone as timezone, kr.patternlengthbars as length, g.basegroupname, newlevels.filtered, case when kr.age is not null then kr.age when kr.resultuid <= rm.resultuid then ? else ? end as age, case when kr.relevant is not null then kr.relevant when kr.resultuid <= rm.resultuid then ? else ? end as relevant, cps.pip from kr inner join brokersymbollist bsl on bsl.brokerid = ? and bsl.symbolid = kr.symbolid inner join symbols s on bsl.symbolid = s.symbolid and s.nonliquid = ? inner join symbolgroup sg on s.symbolid = sg.symbolid inner join groups g on sg.groupid = g.groupid inner join brokergroups bg on g.groupid = bg.groupid and bsl.brokerid = bg.brokerid inner join hrspatterns p on kr.patternid = p.patternid inner join downloadersymbolsettings dss on s.symbolid = dss.symbolid inner join datafeedstimetable dtt on dss.classname = dtt.classname and dtt.dayofweek = ? inner join rar_max rm on ? = ? left outer join autochartist_symbolupdates au on dss.symbolid = au.symbolid left outer join relevance_keylevels_results rar on rar.resultuid = kr.resultuid left join lateral calc_kl_signal_filter (kr.resultuid) newlevels on true left join currencypips cps on cps.symbol = s.symbol left outer join brokerinstrumentmap bim on dss.datafeedinstrumentid = bim.datafeedinstrumentid and bim.brokerid = bsl.brokerid and bim.type = ? where kr.gmttimefound > now() - interval ? and dss.enabled = ? and s.deleted = ? and (kr.simulation = ? or kr.simulation is null) and (? = ? or s.timegranularity in (...)) and (? = ? or s.exchange in (...)) and (? = ? or coalesce(bim.code, s.symbol) in (...)) and (? = ? or p.patternname in (...)) and (? = ? or kr.patternclassid in (...)) and (? = ? or kr.patternlengthbars <= ?) and kr.patternstarttime::timestamp without time zone >= coalesce(au.earliestpricedatetime, ?::timestamp without time zone) -- to make sure patternstarttime is in our t-tables ), results as ( select distinct on (symbolid) * from all_results where (false = ? or relevant = ?) and (? = ? or age <= ?) order by symbolid, resultuid ) select * from results order by identified desc, length desc limit ?;Times Reported Time consuming queries #14
Day Hour Count Duration Avg duration Dec 24 16 384 0ms 0ms 15 0ms 0ms 0ms 1 0ms select e.oid as id, e.xmin as state_number, extname as name, extversion as version, extnamespace as schema_id, nspname as schema_name, array ( select unnest from unnest(available_versions) where unnest > extversion) as available_updates from pg_catalog.pg_extension e join pg_namespace n on e.extnamespace = n.oid left join ( select name, array_agg(version) as available_versions from pg_available_extension_versions() group by name) v on e.extname = v.name where pg_catalog.age(e.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?);Times Reported Time consuming queries #15
Day Hour Count Duration Avg duration Dec 24 16 1 0ms 0ms 16 0ms 0ms 0ms 239 0ms select count(*), sum(size), extract(epoch from now() - min(modification)) from pg_ls_waldir ();Times Reported Time consuming queries #16
Day Hour Count Duration Avg duration Dec 24 16 239 0ms 0ms 17 0ms 0ms 0ms 1 0ms select a.oid as access_method_id, a.xmin as state_number, a.amname as access_method_name, a.amhandler::oid as handler_id, pg_catalog.quote_ident(n.nspname) || ? || pg_catalog.quote_ident(p.proname) as handler_name, a.amtype as access_method_type from pg_am a join pg_proc p on a.amhandler::oid = p.oid join pg_namespace n on p.pronamespace = n.oid where pg_catalog.age(a.xmin) <= coalesce(nullif (greatest (pg_catalog.age(?::varchar::xid), ?), ?), ?);Times Reported Time consuming queries #17
Day Hour Count Duration Avg duration Dec 24 16 1 0ms 0ms 18 0ms 0ms 0ms 239 0ms select system_identifier from pg_control_system ();Times Reported Time consuming queries #18
Day Hour Count Duration Avg duration Dec 24 16 239 0ms 0ms 19 0ms 0ms 0ms 5 0ms select groupid, exchange, groupname, symbol, longname from prfsymboltree where brokerid = ? order by groupname, symbol;Times Reported Time consuming queries #19
Day Hour Count Duration Avg duration Dec 24 16 5 0ms 0ms 20 0ms 0ms 0ms 1 0ms insert into t15 (symbolid, pricedatetime, open, high, low, close, volume, bsf, sastdatetimereceived) values (?, ?::timestamp without time zone, ?, ?.?, ?.?, ?.?, ?, ?, ?::timestamp without time zone) on conflict (symbolid, pricedatetime) do nothing;Times Reported Time consuming queries #20
Day Hour Count Duration Avg duration Dec 24 16 1 0ms 0ms Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 3s708ms 5,390 0ms 15ms 0ms SELECT ;Times Reported Time consuming prepare #1
Day Hour Count Duration Avg duration Dec 24 16 5,390 3s708ms 0ms -
SELECT ;
Date: 2025-12-24 16:49:40 Duration: 15ms Database: postgres
-
SELECT ;
Date: 2025-12-24 16:50:54 Duration: 13ms Database: postgres
-
SELECT ;
Date: 2025-12-24 16:50:54 Duration: 10ms Database: postgres
2 2s942ms 2,710 0ms 12ms 1ms WITH rar_max as ( ;Times Reported Time consuming prepare #2
Day Hour Count Duration Avg duration 16 2,710 2s942ms 1ms -
WITH rar_max as ( ;
Date: 2025-12-24 16:49:40 Duration: 12ms Database: postgres
-
WITH rar_max as ( ;
Date: 2025-12-24 16:30:05 Duration: 12ms Database: postgres
-
WITH rar_max as ( ;
Date: 2025-12-24 16:30:05 Duration: 11ms Database: postgres
3 1s491ms 1,325 0ms 7ms 1ms SELECT symbolid, ;Times Reported Time consuming prepare #3
Day Hour Count Duration Avg duration 16 1,325 1s491ms 1ms -
SELECT symbolid, ;
Date: 2025-12-24 16:01:02 Duration: 7ms Database: postgres
-
SELECT symbolid, ;
Date: 2025-12-24 16:01:05 Duration: 3ms Database: postgres
-
SELECT symbolid, ;
Date: 2025-12-24 16:01:02 Duration: 2ms Database: postgres
4 614ms 631 0ms 1ms 0ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming prepare #4
Day Hour Count Duration Avg duration 16 631 614ms 0ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-12-24 16:45:58 Duration: 1ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-12-24 16:00:52 Duration: 1ms Database: postgres
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-12-24 16:01:12 Duration: 1ms Database: postgres
5 489ms 3,892 0ms 2ms 0ms SET extra_float_digits = 3;Times Reported Time consuming prepare #5
Day Hour Count Duration Avg duration 16 3,892 489ms 0ms -
SET extra_float_digits = 3;
Date: 2025-12-24 16:06:46 Duration: 2ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2025-12-24 16:30:05 Duration: 1ms Database: postgres
-
SET extra_float_digits = 3;
Date: 2025-12-24 16:56:52 Duration: 1ms Database: postgres
6 282ms 3,130 0ms 1ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #6
Day Hour Count Duration Avg duration 16 3,130 282ms 0ms -
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:31:30 Duration: 1ms Database: postgres
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:01:01 Duration: 1ms Database: postgres
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:01:21 Duration: 0ms Database: postgres
7 234ms 4,576 0ms 4ms 0ms select 1;Times Reported Time consuming prepare #7
Day Hour Count Duration Avg duration 16 4,576 234ms 0ms -
select 1;
Date: 2025-12-24 16:55:51 Duration: 4ms Database: postgres
-
select 1;
Date: 2025-12-24 16:57:52 Duration: 2ms Database: postgres
-
select 1;
Date: 2025-12-24 16:44:26 Duration: 2ms Database: postgres
8 203ms 2,034 0ms 0ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #8
Day Hour Count Duration Avg duration 16 2,034 203ms 0ms -
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:02:31 Duration: 0ms Database: postgres
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:10:30 Duration: 0ms Database: postgres
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:10:28 Duration: 0ms Database: postgres
9 176ms 1,139 0ms 0ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #9
Day Hour Count Duration Avg duration 16 1,139 176ms 0ms -
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:11:55 Duration: 0ms Database: postgres
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:16:39 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: 2025-12-24 16:40:52 Duration: 0ms Database: postgres
10 111ms 977 0ms 0ms 0ms INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming prepare #10
Day Hour Count Duration Avg duration 16 977 111ms 0ms -
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:11:41 Duration: 0ms Database: postgres
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:10:38 Duration: 0ms Database: postgres
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:10:28 Duration: 0ms Database: postgres
11 97ms 16 4ms 10ms 6ms with sym_info as ( ;Times Reported Time consuming prepare #11
Day Hour Count Duration Avg duration 16 16 97ms 6ms -
with sym_info as ( ;
Date: 2025-12-24 16:06:42 Duration: 10ms Database: postgres
-
with sym_info as ( ;
Date: 2025-12-24 16:51:44 Duration: 7ms Database: postgres
-
with sym_info as ( ;
Date: 2025-12-24 16:36:43 Duration: 6ms Database: postgres
12 51ms 3,859 0ms 2ms 0ms SET application_name = 'PostgreSQL JDBC Driver';Times Reported Time consuming prepare #12
Day Hour Count Duration Avg duration 16 3,859 51ms 0ms -
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-12-24 16:30:05 Duration: 2ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-12-24 16:56:40 Duration: 1ms Database: postgres
-
SET application_name = 'PostgreSQL JDBC Driver';
Date: 2025-12-24 16:31:56 Duration: 0ms Database: postgres
13 51ms 35 0ms 9ms 1ms WITH last_candle AS ( ;Times Reported Time consuming prepare #13
Day Hour Count Duration Avg duration 16 35 51ms 1ms -
WITH last_candle AS ( ;
Date: 2025-12-24 16:04:02 Duration: 9ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2025-12-24 16:04:02 Duration: 8ms Database: postgres
-
WITH last_candle AS ( ;
Date: 2025-12-24 16:16:00 Duration: 3ms Database: postgres
14 47ms 18 1ms 5ms 2ms select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;Times Reported Time consuming prepare #14
Day Hour Count Duration Avg duration 16 18 47ms 2ms -
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-12-24 16:31:01 Duration: 5ms Database: postgres
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-12-24 16:10:03 Duration: 3ms Database: postgres
-
select cast(count(*) / cast(setting as numeric) * 100 as int) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by setting;
Date: 2025-12-24 16:01:04 Duration: 2ms Database: postgres
15 23ms 150 0ms 0ms 0ms SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;Times Reported Time consuming prepare #15
Day Hour Count Duration Avg duration 16 150 23ms 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: 2025-12-24 16:12:49 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: 2025-12-24 16:12:52 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: 2025-12-24 16:12:49 Duration: 0ms Database: postgres
16 23ms 4 3ms 7ms 5ms SELECT t.*;Times Reported Time consuming prepare #16
Day Hour Count Duration Avg duration 16 4 23ms 5ms -
SELECT t.*;
Date: 2025-12-24 16:25:08 Duration: 7ms Database: postgres
-
SELECT t.*;
Date: 2025-12-24 16:05:09 Duration: 6ms Database: postgres
-
SELECT t.*;
Date: 2025-12-24 16:05:09 Duration: 5ms Database: postgres
17 14ms 6 1ms 3ms 2ms with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;Times Reported Time consuming prepare #17
Day Hour Count Duration Avg duration 16 6 14ms 2ms -
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-12-24 16:50:02 Duration: 3ms Database: postgres
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-12-24 16:20:02 Duration: 3ms Database: postgres
-
with rankedmt4 as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors ), last_feed_entry as ( select * from rankedmt4 where r = 1 ), ok_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where status = 'OK' ), earliest_entry_after_ok as ( select m.datafeedname, min(m.eventtimestamp) as eventtimestamp from mt4datafeederrors m left outer join ( select datafeedname, eventtimestamp from ok_entries where r = 1) oo on m.datafeedname = oo.datafeedname where m.eventtimestamp > coalesce(oo.eventtimestamp, '1900-01-01'::timestamp without time zone) group by m.datafeedname ), notified_entries as ( select *, row_number() over (partition by datafeedname order by eventtimestamp desc) r from mt4datafeederrors where notified is not null and notified <> '' ), broker as ( select *, row_number() over (partition by feedname order by brokerid) r from ( select distinct b.brokerid, b.name as brokername, dss.classname as feedname from downloadersymbolsettings dss inner join brokersymbollist bsl on dss.symbolid = bsl.symbolid inner join broker b on bsl.brokerid = b.brokerid where dss.enabled = 1) a ) select last.id, last.datafeedname, last.eventtimestamp, last.status, last.errordescription, last.serveraddress, last.username, note.notified, note.eventtimestamp, broker.brokername from last_feed_entry last inner join earliest_entry_after_ok after_ok on last.datafeedname = after_ok.datafeedname inner join broker on last.datafeedname = broker.feedname left outer join ok_entries ok on ok.datafeedname = last.datafeedname left outer join notified_entries note on note.datafeedname = last.datafeedname and note.r = 1 where (ok.r is null or ok.r = 1) and last.datafeedname not in ( select distinct datafeedname from last_feed_entry where status = 'OK') and extract(epoch from (last.eventtimestamp - after_ok.eventtimestamp)) > 60 * 60 and last.eventtimestamp > current_timestamp - interval '1 day' and (note.eventtimestamp is null or note.eventtimestamp < current_timestamp - interval '10 hours') and last.eventtimestamp > current_timestamp - interval '1 hour' and broker.r = 1;
Date: 2025-12-24 16:40:02 Duration: 2ms Database: postgres
18 13ms 6 2ms 2ms 2ms select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;Times Reported Time consuming prepare #18
Day Hour Count Duration Avg duration 16 6 13ms 2ms -
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2025-12-24 16:20:04 Duration: 2ms Database: postgres
-
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2025-12-24 16:30:04 Duration: 2ms Database: postgres
-
select client_addr, count(1) from pg_stat_activity, pg_settings WHERE name = 'max_connections' group by client_addr, setting having (client_addr is not null OR (client_addr is null and count(1) > (cast(setting as numeric) / 3 * 2))) order by count desc;
Date: 2025-12-24 16:50:04 Duration: 2ms Database: postgres
19 13ms 24 0ms 0ms 0ms select count(*) from datafeed_restarter_events where is_current_entry = 1;Times Reported Time consuming prepare #19
Day Hour Count Duration Avg duration 16 24 13ms 0ms -
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-12-24 16:50:02 Duration: 0ms Database: postgres
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-12-24 16:40:03 Duration: 0ms Database: postgres
-
select count(*) from datafeed_restarter_events where is_current_entry = 1;
Date: 2025-12-24 16:20:02 Duration: 0ms Database: postgres
20 13ms 8 0ms 3ms 1ms WITH pre_symbols AS ( /* find relevant symbols */ ;Times Reported Time consuming prepare #20
Day Hour Count Duration Avg duration 16 8 13ms 1ms -
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-12-24 16:12:49 Duration: 3ms Database: postgres
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-12-24 16:12:49 Duration: 3ms Database: postgres
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-12-24 16:12:49 Duration: 2ms Database: postgres
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 33s806ms 3,849 0ms 38ms 8ms WITH rar_max as ( ;Times Reported Time consuming bind #1
Day Hour Count Duration Avg duration Dec 24 16 3,849 33s806ms 8ms -
WITH rar_max as ( ;
Date: 2025-12-24 16:30:05 Duration: 38ms Database: postgres parameters: $1 = '607378760893348301', $2 = '607378760893348301', $3 = '607378760893348301'
-
WITH rar_max as ( ;
Date: 2025-12-24 16:50:38 Duration: 37ms Database: postgres parameters: $1 = '607345734315104301', $2 = '607345734315104301', $3 = '607345734315104301'
-
WITH rar_max as ( ;
Date: 2025-12-24 16:51:44 Duration: 36ms Database: postgres parameters: $1 = '607379709145931301', $2 = '607379709145931301', $3 = '607379709145931301'
2 12s383ms 21,254 0ms 29ms 0ms SELECT ;Times Reported Time consuming bind #2
Day Hour Count Duration Avg duration 16 21,254 12s383ms 0ms -
SELECT ;
Date: 2025-12-24 16:52:15 Duration: 29ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840218033513300'
-
SELECT ;
Date: 2025-12-24 16:49:40 Duration: 23ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840217496798300'
-
SELECT ;
Date: 2025-12-24 16:58:39 Duration: 22ms Database: postgres parameters: $1 = '958', $2 = '958', $3 = '515840248630020300'
3 2s791ms 1,325 0ms 5ms 2ms SELECT symbolid, ;Times Reported Time consuming bind #3
Day Hour Count Duration Avg duration 16 1,325 2s791ms 2ms -
SELECT symbolid, ;
Date: 2025-12-24 16:01:02 Duration: 5ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '30', $3 = 'ZECUSD'
-
SELECT symbolid, ;
Date: 2025-12-24 16:01:00 Duration: 4ms Database: postgres parameters: $1 = 'BDSWISS', $2 = '60', $3 = 'USOIL', $4 = 'XAUEUR', $5 = 'XPTUSD', $6 = 'XRPUSD', $7 = 'ZARJPY', $8 = 'XAGUSD', $9 = 'XMRUSD', $10 = 'USDZAR', $11 = 'XAUUSD'
-
SELECT symbolid, ;
Date: 2025-12-24 16:16:01 Duration: 4ms Database: postgres parameters: $1 = 'PEPPERSTONE', $2 = '15', $3 = 'USDPLN', $4 = 'USDTHB', $5 = 'USDX', $6 = 'USDSGD', $7 = 'USDTRY', $8 = 'USDNOK', $9 = 'USDSEK'
4 1s32ms 631 1ms 2ms 1ms SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;Times Reported Time consuming bind #4
Day Hour Count Duration Avg duration 16 631 1s32ms 1ms -
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-12-24 16:45:58 Duration: 2ms Database: postgres parameters: $1 = 'PEPPERSTONE'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-12-24 16:01:04 Duration: 2ms Database: postgres parameters: $1 = 'ICMARKETS-AU-MT5'
-
SELECT s.symbolid, dss.downloadfrequency, dss.downloadersymbol;
Date: 2025-12-24 16:01:12 Duration: 2ms Database: postgres parameters: $1 = 'ICMARKETS-AU-MT5'
5 649ms 16 28ms 60ms 40ms with sym_info as ( ;Times Reported Time consuming bind #5
Day Hour Count Duration Avg duration 16 16 649ms 40ms -
with sym_info as ( ;
Date: 2025-12-24 16:51:44 Duration: 60ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
-
with sym_info as ( ;
Date: 2025-12-24 16:06:42 Duration: 60ms Database: postgres parameters: $1 = '620', $2 = 'Forex', $3 = 'Forex', $4 = '620', $5 = 'Forex', $6 = '620', $7 = '620', $8 = 'Forex', $9 = '620'
-
with sym_info as ( ;
Date: 2025-12-24 16:06:50 Duration: 44ms Database: postgres parameters: $1 = '627', $2 = 'Forex', $3 = 'Forex', $4 = '627', $5 = 'Forex', $6 = '627', $7 = '627', $8 = 'Forex', $9 = '627'
6 528ms 75 4ms 20ms 7ms WITH last_candle AS ( ;Times Reported Time consuming bind #6
Day Hour Count Duration Avg duration 16 75 528ms 7ms -
WITH last_candle AS ( ;
Date: 2025-12-24 16:04:02 Duration: 20ms Database: postgres parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2025-12-24 16:04:02 Duration: 20ms Database: postgres parameters: $1 = '558', $2 = '558'
-
WITH last_candle AS ( ;
Date: 2025-12-24 16:16:01 Duration: 12ms Database: postgres parameters: $1 = '558', $2 = '558'
7 509ms 24 0ms 31ms 21ms with wh_patitioned as ( ;Times Reported Time consuming bind #7
Day Hour Count Duration Avg duration 16 24 509ms 21ms -
with wh_patitioned as ( ;
Date: 2025-12-24 16:35:01 Duration: 31ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
-
with wh_patitioned as ( ;
Date: 2025-12-24 16:20:03 Duration: 30ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
-
with wh_patitioned as ( ;
Date: 2025-12-24 16:45:03 Duration: 30ms Database: postgres parameters: $1 = '558', $2 = '558', $3 = '558', $4 = '558', $5 = '558', $6 = '558', $7 = '558', $8 = '558', $9 = '558'
8 476ms 19,877 0ms 9ms 0ms select 1;Times Reported Time consuming bind #8
Day Hour Count Duration Avg duration 16 19,877 476ms 0ms -
select 1;
Date: 2025-12-24 16:42:20 Duration: 9ms Database: postgres
-
select 1;
Date: 2025-12-24 16:49:40 Duration: 6ms Database: postgres
-
select 1;
Date: 2025-12-24 16:52:38 Duration: 2ms Database: postgres
9 414ms 62 0ms 21ms 6ms WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;Times Reported Time consuming bind #9
Day Hour Count Duration Avg duration 16 62 414ms 6ms -
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-12-24 16:53:43 Duration: 21ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-12-24 16:38:36 Duration: 21ms Database: postgres parameters: $1 = '667', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
-
WITH /*Latest.JapSticks*/ all_results AS ( SELECT ;
Date: 2025-12-24 16:07:47 Duration: 18ms Database: postgres parameters: $1 = '689', $2 = '0', $3 = '0', $4 = '0', $5 = '', $6 = '0', $7 = '', $8 = '0', $9 = '', $10 = '0', $11 = '0'
10 343ms 4 57ms 168ms 85ms SELECT t.*;Times Reported Time consuming bind #10
Day Hour Count Duration Avg duration 16 4 343ms 85ms -
SELECT t.*;
Date: 2025-12-24 16:25:08 Duration: 168ms Database: postgres
-
SELECT t.*;
Date: 2025-12-24 16:05:09 Duration: 59ms Database: postgres
-
SELECT t.*;
Date: 2025-12-24 16:25:08 Duration: 58ms Database: postgres
11 271ms 5,795 0ms 3ms 0ms INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #11
Day Hour Count Duration Avg duration 16 5,795 271ms 0ms -
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:30:05 Duration: 3ms Database: postgres parameters: $1 = '2025-12-24 16:15:00', $2 = '210.62', $3 = '210.701', $4 = '210.495', $5 = '210.528', $6 = '2176', $7 = '515840243917260300', $8 = '0', $9 = '2025-12-24 16:30:05.192', $10 = '2025-12-24 16:30:05.078', $11 = '210.62', $12 = '210.701', $13 = '210.495', $14 = '210.528', $15 = '2176', $16 = '0', $17 = '2025-12-24 16:30:05.192', $18 = '2025-12-24 16:30:05.078'
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:11:55 Duration: 0ms Database: postgres parameters: $1 = '2025-12-24 15:45:00', $2 = '25589.8', $3 = '25600.3', $4 = '25581.67', $5 = '25584.05', $6 = '2231', $7 = '515840248038958300', $8 = '0', $9 = '2025-12-24 16:11:55.066', $10 = '2025-12-24 16:11:54.94', $11 = '25589.8', $12 = '25600.3', $13 = '25581.67', $14 = '25584.05', $15 = '2231', $16 = '0', $17 = '2025-12-24 16:11:55.066', $18 = '2025-12-24 16:11:54.94'
-
INSERT INTO T15 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:16:39 Duration: 0ms Database: postgres parameters: $1 = '2025-12-24 05:00:00', $2 = '8757.86', $3 = '8763.86', $4 = '8755.86', $5 = '8757.86', $6 = '99', $7 = '515840238058964300', $8 = '0', $9 = '2025-12-24 16:16:39.172', $10 = '2025-12-24 16:16:39.107', $11 = '8757.86', $12 = '8763.86', $13 = '8755.86', $14 = '8757.86', $15 = '99', $16 = '0', $17 = '2025-12-24 16:16:39.172', $18 = '2025-12-24 16:16:39.107'
12 248ms 3,332 0ms 0ms 0ms INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #12
Day Hour Count Duration Avg duration 16 3,332 248ms 0ms -
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:01:04 Duration: 0ms Database: postgres parameters: $1 = '2025-12-24 16:30:00', $2 = '1.75839', $3 = '1.75887', $4 = '1.75744', $5 = '1.75745', $6 = '4903', $7 = '515840249382937300', $8 = '0', $9 = '2025-12-24 16:01:04.992', $10 = '2025-12-24 16:01:04.866', $11 = '1.75839', $12 = '1.75887', $13 = '1.75744', $14 = '1.75745', $15 = '4903', $16 = '0', $17 = '2025-12-24 16:01:04.992', $18 = '2025-12-24 16:01:04.866'
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:11:41 Duration: 0ms Database: postgres parameters: $1 = '2025-12-24 04:30:00', $2 = '8750.4', $3 = '8757.95', $4 = '8746.9', $5 = '8752.05', $6 = '2741', $7 = '515840248015340300', $8 = '0', $9 = '2025-12-24 16:11:41.016', $10 = '2025-12-24 16:11:40.812', $11 = '8750.4', $12 = '8757.95', $13 = '8746.9', $14 = '8752.05', $15 = '2741', $16 = '0', $17 = '2025-12-24 16:11:41.016', $18 = '2025-12-24 16:11:40.812'
-
INSERT INTO T30 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:01:02 Duration: 0ms Database: postgres parameters: $1 = '2025-12-24 15:30:00', $2 = '389.035', $3 = '389.281', $4 = '388.836', $5 = '388.91', $6 = '7081', $7 = '500991628207424200', $8 = '0', $9 = '2025-12-24 16:01:02.49', $10 = '2025-12-24 16:01:02.265', $11 = '389.035', $12 = '389.281', $13 = '388.836', $14 = '388.91', $15 = '7081', $16 = '0', $17 = '2025-12-24 16:01:02.49', $18 = '2025-12-24 16:01:02.265'
13 170ms 2,180 0ms 1ms 0ms INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #13
Day Hour Count Duration Avg duration 16 2,180 170ms 0ms -
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:01:03 Duration: 1ms Database: postgres parameters: $1 = '2025-12-24 15:00:00', $2 = '114.018', $3 = '114.051', $4 = '113.961', $5 = '114.041', $6 = '6899', $7 = '500991627559405200', $8 = '0', $9 = '2025-12-24 16:01:03.036', $10 = '2025-12-24 16:01:02.967', $11 = '114.018', $12 = '114.051', $13 = '113.961', $14 = '114.041', $15 = '6899', $16 = '0', $17 = '2025-12-24 16:01:03.036', $18 = '2025-12-24 16:01:02.967'
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:31:06 Duration: 0ms Database: postgres parameters: $1 = '2025-12-23 22:00:00', $2 = '93.08', $3 = '93.14', $4 = '92.88', $5 = '93.11', $6 = '645', $7 = '515840233360148300', $8 = '0', $9 = '2025-12-24 16:31:06.644', $10 = '2025-12-24 16:31:06.644', $11 = '93.08', $12 = '93.14', $13 = '92.88', $14 = '93.11', $15 = '645', $16 = '0', $17 = '2025-12-24 16:31:06.644', $18 = '2025-12-24 16:31:06.644'
-
INSERT INTO T60 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:10:28 Duration: 0ms Database: postgres parameters: $1 = '2025-12-23 21:00:00', $2 = '271.78', $3 = '272.4', $4 = '271.7', $5 = '272.06', $6 = '2964', $7 = '515840247917405300', $8 = '0', $9 = '2025-12-24 16:10:28.085', $10 = '2025-12-24 16:10:28.006', $11 = '271.78', $12 = '272.4', $13 = '271.7', $14 = '272.06', $15 = '2964', $16 = '0', $17 = '2025-12-24 16:10:28.085', $18 = '2025-12-24 16:10:28.006'
14 109ms 1,131 0ms 0ms 0ms INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;Times Reported Time consuming bind #14
Day Hour Count Duration Avg duration 16 1,131 109ms 0ms -
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:01:04 Duration: 0ms Database: postgres parameters: $1 = '2025-12-24 12:00:00', $2 = '2.014245', $3 = '2.015355', $4 = '2.012425', $5 = '2.01383', $6 = '17729', $7 = '515840230479349300', $8 = '0', $9 = '2025-12-24 16:01:04.39', $10 = '2025-12-24 16:01:04.389', $11 = '2.014245', $12 = '2.015355', $13 = '2.012425', $14 = '2.01383', $15 = '17729', $16 = '0', $17 = '2025-12-24 16:01:04.39', $18 = '2025-12-24 16:01:04.389'
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:11:41 Duration: 0ms Database: postgres parameters: $1 = '2025-12-24 00:00:00', $2 = '8781.45', $3 = '8781.6', $4 = '8735.4', $5 = '8750.15', $6 = '21098', $7 = '515840248015766300', $8 = '0', $9 = '2025-12-24 16:11:41.054', $10 = '2025-12-24 16:11:40.834', $11 = '8781.45', $12 = '8781.6', $13 = '8735.4', $14 = '8750.15', $15 = '21098', $16 = '0', $17 = '2025-12-24 16:11:41.054', $18 = '2025-12-24 16:11:40.834'
-
INSERT INTO T240 (pricedatetime, open, high, low, close, volume, symbolid, bsf, sastdatetimewritten, sastdatetimereceived) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10) ON CONFLICT (pricedatetime, symbolid) DO UPDATE SET open = $11, high = $12, low = $13, close = $14, volume = $15, bsf = $16, sastdatetimewritten = $17, sastdatetimereceived = $18;
Date: 2025-12-24 16:10:38 Duration: 0ms Database: postgres parameters: $1 = '2025-12-23 16:00:00', $2 = '118.42', $3 = '119.95', $4 = '118.2', $5 = '119.83', $6 = '6697', $7 = '515840247963632300', $8 = '0', $9 = '2025-12-24 16:10:38.296', $10 = '2025-12-24 16:10:38.199', $11 = '118.42', $12 = '119.95', $13 = '118.2', $14 = '119.83', $15 = '6697', $16 = '0', $17 = '2025-12-24 16:10:38.296', $18 = '2025-12-24 16:10:38.199'
15 69ms 78 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 #15
Day Hour Count Duration Avg duration 16 78 69ms 0ms -
SELECT timegranularity FROM brokersymbollist bsl INNER JOIN symbols s ON bsl.symbolid = s.symbolid INNER JOIN downloadersymbolsettings dss on s.symbolid = dss.symbolid LEFT OUTER JOIN brokerinstrumentmapping bdfi ON bdfi.brokerid = $1 AND dss.datafeedinstrumentid = bdfi.datafeedinstrumentid WHERE s.nonliquid = 0 and s.deleted = 0 and dss.enabled = 1 AND s.symbol ILIKE $2 AND bsl.brokerid = $3 AND timegranularity >= 15 ORDER BY timegranularity LIMIT 1;
Date: 2025-12-24 16:01:05 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'XAUUSD.a', $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: 2025-12-24 16:06:05 Duration: 1ms Database: postgres parameters: $1 = '558', $2 = 'NOKSEK', $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: 2025-12-24 16:22:01 Duration: 1ms Database: postgres parameters: $1 = '538', $2 = 'CADJPYr', $3 = '538'
16 61ms 150 0ms 3ms 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 16 150 61ms 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: 2025-12-24 16:12:49 Duration: 3ms Database: postgres
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-12-24 16:12:52 Duration: 0ms Database: postgres
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SELECT NULL AS TABLE_CAT, n.nspname AS TABLE_SCHEM, c.relname AS TABLE_NAME, CASE n.nspname ~ '^pg_' OR n.nspname = 'information_schema' WHEN true THEN CASE WHEN n.nspname = 'pg_catalog' OR n.nspname = 'information_schema' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TABLE' WHEN 'v' THEN 'SYSTEM VIEW' WHEN 'i' THEN 'SYSTEM INDEX' ELSE NULL END WHEN n.nspname = 'pg_toast' THEN CASE c.relkind WHEN 'r' THEN 'SYSTEM TOAST TABLE' WHEN 'i' THEN 'SYSTEM TOAST INDEX' ELSE NULL END ELSE CASE c.relkind WHEN 'r' THEN 'TEMPORARY TABLE' WHEN 'p' THEN 'TEMPORARY TABLE' WHEN 'i' THEN 'TEMPORARY INDEX' WHEN 'S' THEN 'TEMPORARY SEQUENCE' WHEN 'v' THEN 'TEMPORARY VIEW' ELSE NULL END END WHEN false THEN CASE c.relkind WHEN 'r' THEN 'TABLE' WHEN 'p' THEN 'PARTITIONED TABLE' WHEN 'i' THEN 'INDEX' WHEN 'S' THEN 'SEQUENCE' WHEN 'v' THEN 'VIEW' WHEN 'c' THEN 'TYPE' WHEN 'f' THEN 'FOREIGN TABLE' WHEN 'm' THEN 'MATERIALIZED VIEW' ELSE NULL END ELSE NULL END AS TABLE_TYPE, d.description AS REMARKS, '' as TYPE_CAT, '' as TYPE_SCHEM, '' as TYPE_NAME, '' AS SELF_REFERENCING_COL_NAME, '' AS REF_GENERATION FROM pg_catalog.pg_namespace n, pg_catalog.pg_class c LEFT JOIN pg_catalog.pg_description d ON (c.oid = d.objoid AND d.objsubid = 0) LEFT JOIN pg_catalog.pg_class dc ON (d.classoid = dc.oid AND dc.relname = 'pg_class') LEFT JOIN pg_catalog.pg_namespace dn ON (dn.oid = dc.relnamespace AND dn.nspname = 'pg_catalog') WHERE c.relnamespace = n.oid AND c.relname LIKE 'PROBABLYNOT' AND (false OR (c.relkind = 'r' AND n.nspname !~ '^pg_' AND n.nspname <> 'information_schema')) ORDER BY TABLE_TYPE, TABLE_SCHEM, TABLE_NAME;
Date: 2025-12-24 16:12:49 Duration: 0ms Database: postgres
17 58ms 12 3ms 7ms 4ms SELECT DISTINCT ON (basegroupname, symbol) ;Times Reported Time consuming bind #17
Day Hour Count Duration Avg duration 16 12 58ms 4ms -
SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-12-24 16:52:47 Duration: 7ms Database: postgres parameters: $1 = '689', $2 = '689'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-12-24 16:06:45 Duration: 6ms Database: postgres parameters: $1 = '667', $2 = '667'
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SELECT DISTINCT ON (basegroupname, symbol) ;
Date: 2025-12-24 16:36:00 Duration: 6ms Database: postgres parameters: $1 = '627', $2 = '627'
18 39ms 8 2ms 7ms 4ms WITH pre_symbols AS ( /* find relevant symbols */ ;Times Reported Time consuming bind #18
Day Hour Count Duration Avg duration 16 8 39ms 4ms -
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-12-24 16:12:49 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'
-
WITH pre_symbols AS ( /* find relevant symbols */ ;
Date: 2025-12-24 16:12:49 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: 2025-12-24 16:12:49 Duration: 6ms 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'
19 32ms 353 0ms 2ms 0ms /*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;Times Reported Time consuming bind #19
Day Hour Count Duration Avg duration 16 353 32ms 0ms -
/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2025-12-24 16:03:43 Duration: 2ms Database: postgres parameters: $1 = '607383577883629301'
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2025-12-24 16:03:43 Duration: 1ms Database: postgres parameters: $1 = '607383222077271301'
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/*server.CPResult*/ SELECT patternid, resy0, resy1, supporty0, supporty1, predictiontimeto, patternstarttime, s.symbolid, resx0, resx1, supportx0, supportx1, symbol, longname, shortname, timegranularity, patternendtime, pattern, a.direction, trendchange, patternlengthbars, patternquality, resultuid as uid, breakout, initialtrend, volumeincrease, symmetry as uniformity, predictionpricefrom, predictionpriceto, noise, exchange, breakout, dtt.absolutetimezoneoffset as tzOs, dtt.timezone as tz FROM autochartist_results a INNER JOIN downloadersymbolsettings dss on a.symbolid = dss.symbolid INNER JOIN datafeedstimetable dtt ON dss.classname = dtt.classname inner join symbols s on a.symbolid = s.symbolid inner join patterns p on p.patternname = a.pattern where resultuid = $1;
Date: 2025-12-24 16:05:09 Duration: 1ms Database: postgres parameters: $1 = '607383700462707301'
20 31ms 1 31ms 31ms 31ms with maxwhid as ( ;Times Reported Time consuming bind #20
Day Hour Count Duration Avg duration 16 1 31ms 31ms -
with maxwhid as ( ;
Date: 2025-12-24 16:13:14 Duration: 31ms Database: postgres parameters: $1 = '335', $2 = '621', $3 = '637', $4 = '642', $5 = '660', $6 = '666', $7 = '643', $8 = '630', $9 = '680', $10 = '641', $11 = '431', $12 = '622', $13 = '489', $14 = '529', $15 = '576', $16 = '665', $17 = '667', $18 = '558', $19 = '620', $20 = '125', $21 = '488', $22 = '567', $23 = '689', $24 = '700', $25 = '758', $26 = '763', $27 = '765', $28 = '817', $29 = '914', $30 = '972'
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Events
Log levels
Key values
- 411,698 Log entries
Events distribution
Key values
- 0 PANIC entries
- 0 FATAL entries
- 0 ERROR entries
- 0 WARNING entries
Errors per 5 minutes
NO DATASET
Most Frequent Errors/Events
Key values
- 0 Max number of times the same event was reported
- 0 Total events found
Rank Times reported Error NO DATASET